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9,286,270 | 1 | 5 |
1. A computerized method comprising: receiving multiple documents from at least one machine-readable media, the multiple documents having a hierarchical relationship relative to each other, the multiple documents including a first document and a second document, the hierarchical relationship between the first document and the second document being such that the second document is the child of the first document in the hierarchy and is associated with a specific subsection of the first document and the second document includes a replacement or addition for the specific subsection of the first document and an entirety of the second document is included in the first document as an enhancement to the first document; and simultaneously displaying the multiple documents on a display screen such that the multiple documents are distinct and are arranged according to the hierarchical relationship, wherein the position at which the second document is displayed is entirely within the first document and that the position of the second document within the first document is based on the specific subsection of the first document that the second document is associated with.
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1. A computerized method comprising: receiving multiple documents from at least one machine-readable media, the multiple documents having a hierarchical relationship relative to each other, the multiple documents including a first document and a second document, the hierarchical relationship between the first document and the second document being such that the second document is the child of the first document in the hierarchy and is associated with a specific subsection of the first document and the second document includes a replacement or addition for the specific subsection of the first document and an entirety of the second document is included in the first document as an enhancement to the first document; and simultaneously displaying the multiple documents on a display screen such that the multiple documents are distinct and are arranged according to the hierarchical relationship, wherein the position at which the second document is displayed is entirely within the first document and that the position of the second document within the first document is based on the specific subsection of the first document that the second document is associated with. 5. The computerized method of claim 1 , wherein a third document of the multiple documents is a different enhancement to the second document, wherein the different enhancement is at least one of a replacement of part of the second document or an addition to the second document.
| 0.657635 |
9,400,919 | 1 | 16 |
1. A computer-implemented method for training a pyramid convolutional neural network (CNN) comprising at least N shared layers where N≧2 and at least one unshared network coupled to the Nth shared layer, the method comprising: training CNN levels 1 to N in that order, wherein CNN level n comprises an input for receiving face images, the first n shared layers of the pyramid CNN, the unshared network of the pyramid CNN, and an output producing representations of the face images; wherein the input is coupled to a first of the n shared layers; each shared layer includes convolution, non-linearity and down-sampling; an nth of the n shared layers is coupled to the unshared network; and the unshared network is coupled to the output; wherein training CNN level n comprises: presenting face images to the input, each face image producing a corresponding representation at the output; processing the representations to produce estimates of a metric, for which actual values of the metric are known; and adapting the nth shared layer and the unshared network based on the estimates of the metric compared to the actual values of the metric.
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1. A computer-implemented method for training a pyramid convolutional neural network (CNN) comprising at least N shared layers where N≧2 and at least one unshared network coupled to the Nth shared layer, the method comprising: training CNN levels 1 to N in that order, wherein CNN level n comprises an input for receiving face images, the first n shared layers of the pyramid CNN, the unshared network of the pyramid CNN, and an output producing representations of the face images; wherein the input is coupled to a first of the n shared layers; each shared layer includes convolution, non-linearity and down-sampling; an nth of the n shared layers is coupled to the unshared network; and the unshared network is coupled to the output; wherein training CNN level n comprises: presenting face images to the input, each face image producing a corresponding representation at the output; processing the representations to produce estimates of a metric, for which actual values of the metric are known; and adapting the nth shared layer and the unshared network based on the estimates of the metric compared to the actual values of the metric. 16. The computer-implemented method of claim 1 wherein N is less than 5.
| 0.936842 |
9,348,872 | 19 | 21 |
19. The system of claim 18 , wherein the first magnitude is determined based on a field attribute associated with the first plurality of text items.
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19. The system of claim 18 , wherein the first magnitude is determined based on a field attribute associated with the first plurality of text items. 21. The system of claim 19 , wherein the field attribute includes a web page address field.
| 0.835145 |
8,495,050 | 7 | 8 |
7. An apparatus for identifying universal resource locator rewriting rules, the apparatus comprising: a communications fabric; a memory connected to the communications fabric, wherein the memory includes computer executable program code; a communications unit connected to the communications fabric; an input/output unit connected to the communications fabric; a display connected to the communications fabric; and a processor unit connected to the communications fabric, wherein the processor unit is configured to execute the computer executable program code to direct the apparatus to: receive input of universal resource locators of an application, to form received universal resource locators; represent the received universal resource locators in a graph; apply analysis algorithms and heuristics to properties of the graph; identify universal resource locator rewriting patterns using the graph to form detected patterns, including if a switch has a complexity value greater than a predetermined value “Q”, grouping identified switches into Left Switches and Right Switches according to a connection set; and generate rewrite rules corresponding to the detected patterns.
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7. An apparatus for identifying universal resource locator rewriting rules, the apparatus comprising: a communications fabric; a memory connected to the communications fabric, wherein the memory includes computer executable program code; a communications unit connected to the communications fabric; an input/output unit connected to the communications fabric; a display connected to the communications fabric; and a processor unit connected to the communications fabric, wherein the processor unit is configured to execute the computer executable program code to direct the apparatus to: receive input of universal resource locators of an application, to form received universal resource locators; represent the received universal resource locators in a graph; apply analysis algorithms and heuristics to properties of the graph; identify universal resource locator rewriting patterns using the graph to form detected patterns, including if a switch has a complexity value greater than a predetermined value “Q”, grouping identified switches into Left Switches and Right Switches according to a connection set; and generate rewrite rules corresponding to the detected patterns. 8. The apparatus of claim 7 , wherein the processor unit is configured to execute the computer executable program code to receive input further directs the apparatus to: receive a set of universal resource locators, wherein the set comprises a list of universal resource locators generated by a Web crawler examination of Web sites of the application.
| 0.876582 |
9,953,331 | 1 | 6 |
1. A non-transitory computer readable medium having instructions which, when executed by a processor, causes the processor to perform a process for extending attributes for a predictive analysis engine, the process comprising: defining one or more extended attributes of a database entity, the database entity corresponding to a database table, the database table comprising one or more original attribute columns and one or more unused extension columns for the database entity, the one or more unused extension columns providing extensibility of the database entity for the one or more extended attributes not defined in the one or more original attribute columns of the database table of the database entity; receiving from an interface a definition of the one or more extended attributes for the database entity; modifying a metadata schema of the database table using the one or more extended attributes, comprising: modifying a first version of the database entity to a second version of the database entity, the second version of the database entity comprising the one or more extended attributes that do not exist in the first version, by: reviewing the one or more unused extension columns for the first version of the database entity, identifying unused extension columns from among the one or more unused extension columns of the database table for the first version of the database entity, and editing the metadata schema for the database table to map the identified unused extension columns from the database table to the one or more extended attributes to generate the second version of the database entity within the database table; recognizing, by the predictive analysis engine, the one or more extended attributes of the database entity; and executing the predictive analysis engine to generate recommendations based at least in part on the one or more extended attributes by using one or more new rules or one or more new models, the one or more new rules or the one or more new models comprise the one or more extended attributes.
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1. A non-transitory computer readable medium having instructions which, when executed by a processor, causes the processor to perform a process for extending attributes for a predictive analysis engine, the process comprising: defining one or more extended attributes of a database entity, the database entity corresponding to a database table, the database table comprising one or more original attribute columns and one or more unused extension columns for the database entity, the one or more unused extension columns providing extensibility of the database entity for the one or more extended attributes not defined in the one or more original attribute columns of the database table of the database entity; receiving from an interface a definition of the one or more extended attributes for the database entity; modifying a metadata schema of the database table using the one or more extended attributes, comprising: modifying a first version of the database entity to a second version of the database entity, the second version of the database entity comprising the one or more extended attributes that do not exist in the first version, by: reviewing the one or more unused extension columns for the first version of the database entity, identifying unused extension columns from among the one or more unused extension columns of the database table for the first version of the database entity, and editing the metadata schema for the database table to map the identified unused extension columns from the database table to the one or more extended attributes to generate the second version of the database entity within the database table; recognizing, by the predictive analysis engine, the one or more extended attributes of the database entity; and executing the predictive analysis engine to generate recommendations based at least in part on the one or more extended attributes by using one or more new rules or one or more new models, the one or more new rules or the one or more new models comprise the one or more extended attributes. 6. The non-transitory computer readable medium of claim 1 , wherein data for the predictive analysis engine is stored in a transactional system.
| 0.900415 |
8,489,628 | 15 | 17 |
15. A computer-implemented method of: receiving a query from a user; identifying a multiple word phrase in the query; identifying, by at least one processor of a computing system, a phrase extension of the identified phrase, wherein the phrase extension of the identified phrase is a sequence of words that begins with the identified phrase but is longer than the identified phrase, and wherein the identified phrase predicts the phrase extension based on a measure of an actual co-occurrence rate of the phrase extension and the identified phrase exceeding an expected co-occurrence rate of the phrase extension and the identified phrase in the document collection; and selecting, by at least one processor of the computing system, documents from the document collection containing the phrase extension.
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15. A computer-implemented method of: receiving a query from a user; identifying a multiple word phrase in the query; identifying, by at least one processor of a computing system, a phrase extension of the identified phrase, wherein the phrase extension of the identified phrase is a sequence of words that begins with the identified phrase but is longer than the identified phrase, and wherein the identified phrase predicts the phrase extension based on a measure of an actual co-occurrence rate of the phrase extension and the identified phrase exceeding an expected co-occurrence rate of the phrase extension and the identified phrase in the document collection; and selecting, by at least one processor of the computing system, documents from the document collection containing the phrase extension. 17. The method of claim 15 , further comprising suggesting, by at least one processor of the computing system, the phrase extension to the user to use in the query.
| 0.826638 |
9,854,049 | 1 | 2 |
1. A method for providing information to a user comprising: receiving, with user equipment associated with a first user, a communication transmitted by a second user; in response to receiving the communication that was transmitted by the second user, processing, with the user equipment associated with the first user, text of the communication to identify a symbol of the communication that is subject to a plurality of candidate interpretations, the symbol including one or more words in the processed text of the communication; identifying each candidate interpretation of the plurality of candidate interpretations; retrieving a profile of the first user; comparing an attribute of the profile to each candidate interpretation of the plurality of candidate interpretations; in response determining, based on the comparison, that the first user has accessed a first media asset that is associated with a first of the plurality of candidate interpretations more recently than a second media asset that is associated with a second of the plurality of candidate interpretations, selecting as a determined meaning of the symbol the first candidate interpretation; and updating the profile to include information based on the determined meaning.
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1. A method for providing information to a user comprising: receiving, with user equipment associated with a first user, a communication transmitted by a second user; in response to receiving the communication that was transmitted by the second user, processing, with the user equipment associated with the first user, text of the communication to identify a symbol of the communication that is subject to a plurality of candidate interpretations, the symbol including one or more words in the processed text of the communication; identifying each candidate interpretation of the plurality of candidate interpretations; retrieving a profile of the first user; comparing an attribute of the profile to each candidate interpretation of the plurality of candidate interpretations; in response determining, based on the comparison, that the first user has accessed a first media asset that is associated with a first of the plurality of candidate interpretations more recently than a second media asset that is associated with a second of the plurality of candidate interpretations, selecting as a determined meaning of the symbol the first candidate interpretation; and updating the profile to include information based on the determined meaning. 2. The method of claim 1 , further comprising providing a media asset recommendation to the first user based on the determined meaning.
| 0.859959 |
8,725,552 | 11 | 14 |
11. A system comprising: at least one programmable processor; and a non-transitory machine-readable medium storing instructions that, when executed by the at least one programmable processor, perform the method comprising: importing data of a publication; transforming the data into a structured schema including dividing a section of the publication into a plurality of sub-sections; ingesting the structured schema to determine a context of the data and one or more key concepts, wherein ingesting comprises: targeting one or more of the sub-sections using natural language and one or more controlled vocabulary phrases, and drawing associations between the data and a plurality of profiles; and generating a score based on the associations between the raw data and the profiles; wherein the at least one of the above is performed on at least one processor.
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11. A system comprising: at least one programmable processor; and a non-transitory machine-readable medium storing instructions that, when executed by the at least one programmable processor, perform the method comprising: importing data of a publication; transforming the data into a structured schema including dividing a section of the publication into a plurality of sub-sections; ingesting the structured schema to determine a context of the data and one or more key concepts, wherein ingesting comprises: targeting one or more of the sub-sections using natural language and one or more controlled vocabulary phrases, and drawing associations between the data and a plurality of profiles; and generating a score based on the associations between the raw data and the profiles; wherein the at least one of the above is performed on at least one processor. 14. The system according to claim 11 , further comprising assigning a weight to at least one of the profiles.
| 0.652866 |
10,162,853 | 8 | 12 |
8. A method for generating a response to a natural language query, the method comprising: receiving, using a control circuitry of a user equipment device, the natural language query; identifying, using the control circuitry, which query template of a plurality of query templates corresponds to the natural language query, wherein the identified query template comprises: an associated first response template for providing an audio-only response to the natural language query, an associated second response template for providing a visual-only response to the natural language query, and an associated third response template for providing an audio-visual response to the natural language query; retrieving, using the control circuitry, one or more search results corresponding to the natural language query; determining, using the control circuitry, whether the user equipment device is associated with an audio component and a display; in response to determining that the user equipment device is associated with the audio component and the display, updating, using the control circuitry, one or more attributes associated with the user equipment device to indicate that the user equipment device is associated with the audio component and the display; selecting, using the control circuitry, the associated third response template for providing the audio-visual response to the natural language query based on the one or more attributes indicating that the user equipment device is associated with the audio component and the display; and generating the response to the natural language query based on the selected response template and the retrieved one or more search results.
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8. A method for generating a response to a natural language query, the method comprising: receiving, using a control circuitry of a user equipment device, the natural language query; identifying, using the control circuitry, which query template of a plurality of query templates corresponds to the natural language query, wherein the identified query template comprises: an associated first response template for providing an audio-only response to the natural language query, an associated second response template for providing a visual-only response to the natural language query, and an associated third response template for providing an audio-visual response to the natural language query; retrieving, using the control circuitry, one or more search results corresponding to the natural language query; determining, using the control circuitry, whether the user equipment device is associated with an audio component and a display; in response to determining that the user equipment device is associated with the audio component and the display, updating, using the control circuitry, one or more attributes associated with the user equipment device to indicate that the user equipment device is associated with the audio component and the display; selecting, using the control circuitry, the associated third response template for providing the audio-visual response to the natural language query based on the one or more attributes indicating that the user equipment device is associated with the audio component and the display; and generating the response to the natural language query based on the selected response template and the retrieved one or more search results. 12. The method of claim 8 , further comprising: receiving a generic response template associated with the natural language query; determining whether the generic response template may be converted into at least one of an audio response template, a visual response template, and a mixed audio and visual response template; based on determining that the generic response template can be converted into the audio response template, converting the generic response template into the associated first response template; based on determining that the generic response template can be converted into the visual response template, converting the generic response template into the associated second response template; and based on determining that the generic response template can be converted into an audiovisual response template, converting the generic response template into the associated third response template.
| 0.5 |
9,786,267 | 1 | 2 |
1. A method for recording and playing a user voice in a mobile terminal, the method comprising: entering a page by executing an electronic book; identifying, by the mobile terminal, whether a first user voice record file related to the page exists; generating the first user voice record file related to the page by recording a text included in the page to a user voice if the first user voice record file does not exist; playing the user voice by synchronizing the user voice stored in the first user voice record file with the text if the first user voice record file exists; generating a phonemic voice file by classifying the user voice stored in the first user voice record file by phoneme; comparing the phonemic voice file with all the text included in the electronic book; and generating a second user voice record file related to remaining pages without a stored user voice record file if a percentage of the phonemic voice file for all the text is higher than a predetermined level, wherein if a required phoneme is not stored in a Text To Speech (TTS) database, then informing a user by a suggestion to record phoneme.
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1. A method for recording and playing a user voice in a mobile terminal, the method comprising: entering a page by executing an electronic book; identifying, by the mobile terminal, whether a first user voice record file related to the page exists; generating the first user voice record file related to the page by recording a text included in the page to a user voice if the first user voice record file does not exist; playing the user voice by synchronizing the user voice stored in the first user voice record file with the text if the first user voice record file exists; generating a phonemic voice file by classifying the user voice stored in the first user voice record file by phoneme; comparing the phonemic voice file with all the text included in the electronic book; and generating a second user voice record file related to remaining pages without a stored user voice record file if a percentage of the phonemic voice file for all the text is higher than a predetermined level, wherein if a required phoneme is not stored in a Text To Speech (TTS) database, then informing a user by a suggestion to record phoneme. 2. The method of claim 1 , wherein the generating of the first user voice record file comprises recording a text included in the page to a user voice and a synchronization file including text location information corresponding to each time section of the first user voice record file.
| 0.744144 |
8,984,497 | 1 | 3 |
1. A computer implemented method for converting a source code in a first programming language to a code in a second programming language, the method comprising the steps of: preparing the source code in the first programming language; scanning the source code in the first programming language; determining, from the scanning, whether parameters of a target method have type parameters; acquiring a suffix if the target method parameters have the type parameters; generating a syntax class whose name is identical to the acquired syntax; generating a constructor having a dummy parameter of a type of the syntax class; adding the dummy parameter of the type of the synthetic class to a definition of the generated constructor; adding an appropriate value that matches the type of the dummy parameter to an invocation of the generated constructor; and generating a code in the second programming language converted based on a result of adding said dummy parameter and type matching values, wherein the first programming language is a programming language based on reification, and the second programming language is a programming language based on erasure.
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1. A computer implemented method for converting a source code in a first programming language to a code in a second programming language, the method comprising the steps of: preparing the source code in the first programming language; scanning the source code in the first programming language; determining, from the scanning, whether parameters of a target method have type parameters; acquiring a suffix if the target method parameters have the type parameters; generating a syntax class whose name is identical to the acquired syntax; generating a constructor having a dummy parameter of a type of the syntax class; adding the dummy parameter of the type of the synthetic class to a definition of the generated constructor; adding an appropriate value that matches the type of the dummy parameter to an invocation of the generated constructor; and generating a code in the second programming language converted based on a result of adding said dummy parameter and type matching values, wherein the first programming language is a programming language based on reification, and the second programming language is a programming language based on erasure. 3. The method according to claim 1 , wherein the first programming language is X10, the second programming language is Java, and the code in the second programming language is a Java source code.
| 0.5 |
8,200,793 | 11 | 17 |
11. A memory device having instructions stored thereon that, in response to execution by a processing device, cause the processing device to perform operations comprising: embedding a control mark within an electronic document created by a document word processor, wherein the control mark remains embedded in the electronic document after changing a body of the electronic document with the document word processor; wherein the control mark cannot be changed by or removed with the document word processor; and wherein the control mark includes an encrypted check sum configured to self-authenticate or self-validate the electronic document; and detecting transmitted network packets containing the electronic document, based on the control mark; making a determination that the electronic document contained in at least one of the transmitted packets has been changed; and blocking access to the electronic document contained in the at least one of the transmitted packets in response to the determination.
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11. A memory device having instructions stored thereon that, in response to execution by a processing device, cause the processing device to perform operations comprising: embedding a control mark within an electronic document created by a document word processor, wherein the control mark remains embedded in the electronic document after changing a body of the electronic document with the document word processor; wherein the control mark cannot be changed by or removed with the document word processor; and wherein the control mark includes an encrypted check sum configured to self-authenticate or self-validate the electronic document; and detecting transmitted network packets containing the electronic document, based on the control mark; making a determination that the electronic document contained in at least one of the transmitted packets has been changed; and blocking access to the electronic document contained in the at least one of the transmitted packets in response to the determination. 17. The memory device of claim 11 wherein said detecting further includes monitoring network packets transmitted to an internal organization network from an external organization network.
| 0.696429 |
7,827,143 | 15 | 17 |
15. A computer-readable-storage medium comprising instructions thereon that program a computer to perform the following: during a first build of an installation package: receive first seed characters associated with a first file to be included in the first build of the installation package; apply rules to the first seed characters to create a unique, reproducible first file code for the first file, wherein: the rules, when applied to subsequent seed characters identical to the first seed characters, are configured to reproduce a subsequent file code identical to the first file code; the rules are configured to create a different file code for each different set of seed characters; receive second seed characters associated with a first set of files to be included in the first build of the installation package, the first set of files comprising the first file; apply the rules to the second seed characters to create a unique, reproducible first component code for the first set of files; during a second build of the installation package: receive the subsequent seed characters associated with the first file; apply the rules to the subsequent seed characters associated with the first file to create the subsequent file code that is identical to the first file code; wherein: the first component code is related to the first file code; the relationship between the first component code and the first file code enables a product included in the first build of the installation package to be accessible by a product included in the second build of the installation package.
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15. A computer-readable-storage medium comprising instructions thereon that program a computer to perform the following: during a first build of an installation package: receive first seed characters associated with a first file to be included in the first build of the installation package; apply rules to the first seed characters to create a unique, reproducible first file code for the first file, wherein: the rules, when applied to subsequent seed characters identical to the first seed characters, are configured to reproduce a subsequent file code identical to the first file code; the rules are configured to create a different file code for each different set of seed characters; receive second seed characters associated with a first set of files to be included in the first build of the installation package, the first set of files comprising the first file; apply the rules to the second seed characters to create a unique, reproducible first component code for the first set of files; during a second build of the installation package: receive the subsequent seed characters associated with the first file; apply the rules to the subsequent seed characters associated with the first file to create the subsequent file code that is identical to the first file code; wherein: the first component code is related to the first file code; the relationship between the first component code and the first file code enables a product included in the first build of the installation package to be accessible by a product included in the second build of the installation package. 17. The computer-readable-storage medium of claim 15 , further comprising instructions that program the computer to perform the following: during the first build of the installation package: receive third seed characters associated with a second file to be included in the first build of the installation package; apply the rules to the third seed characters to create a unique, reproducible second file code for the second file, wherein: the rules, when applied to subsequent seed characters identical to the third seed characters, are configured to reproduce a subsequent file code identical to the second file code; the second file code is different than the first file code; during the second build of the installation package: receive the subsequent seed characters associated with the second file; apply the rules to the subsequent seed characters associated with the second file to create the subsequent file code that is identical to the second file code.
| 0.5 |
8,266,132 | 7 | 8 |
7. The method of claim 6 , wherein at least a portion of the digital image is displayed concurrently with the reference map.
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7. The method of claim 6 , wherein at least a portion of the digital image is displayed concurrently with the reference map. 8. The method of claim 7 , wherein the at least the portion of the digital image overlays at least a portion of the reference map.
| 0.5 |
8,239,522 | 9 | 16 |
9. A web analytics server system, comprising: a processor; a memory which is interoperable with the processor; reception code configuring the memory and capable of controlling the processor to make the server system receive a web-beacon request and a dynamic variable specification, wherein the dynamic variable specification was built, at least partially, at a web-reading device for inclusion in a transmission of the web-beacon request, and wherein the dynamic variable specification comprises identification of: one or more dynamic data variables; and for each of the one or more dynamic data variables, a data source from which to collect a data value corresponding to the respective dynamic data variable identified; and interpretation code configuring the memory and capable of controlling the processor to cause the server system to interpret the dynamic variable specification, wherein interpreting the dynamic variable specification comprises: collecting, from the data source identified by the dynamic variable specification, the data value corresponding to each of the one or more dynamic data variables identified; and assigning each data value collected to the corresponding dynamic data variable identified.
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9. A web analytics server system, comprising: a processor; a memory which is interoperable with the processor; reception code configuring the memory and capable of controlling the processor to make the server system receive a web-beacon request and a dynamic variable specification, wherein the dynamic variable specification was built, at least partially, at a web-reading device for inclusion in a transmission of the web-beacon request, and wherein the dynamic variable specification comprises identification of: one or more dynamic data variables; and for each of the one or more dynamic data variables, a data source from which to collect a data value corresponding to the respective dynamic data variable identified; and interpretation code configuring the memory and capable of controlling the processor to cause the server system to interpret the dynamic variable specification, wherein interpreting the dynamic variable specification comprises: collecting, from the data source identified by the dynamic variable specification, the data value corresponding to each of the one or more dynamic data variables identified; and assigning each data value collected to the corresponding dynamic data variable identified. 16. The system of claim 9 , wherein the dynamic variable specification conforms with a syntax that contains designations for variable names, operators, and literals.
| 0.682692 |
9,733,821 | 1 | 3 |
1. A method, comprising: at an electronic device comprising a processor and memory storing instructions for execution by the processor: while the device is operating with a first setting in a first state, detecting, at a first time, a change in settings of the device to change the first setting from the first state to a second state that is different from the first state; while the device is operating with the first setting in the second state, receiving, at a second time that is after the first time, a user input that corresponds to a pattern of user behavior, wherein the user input is a user voice input; in response to receiving the user input: comparing the pattern of user behavior to a plurality of predefined conditions that, when met, indicate that the user is having difficulty with operating the device, wherein a predefined condition of the plurality of predefined conditions includes the user voice input containing one or more predetermined words associated with user difficulty; in accordance with a determination, based on the comparison of the pattern of user behavior to the plurality of predefined conditions, that the device changed the first setting from the first state to the second state within a predetermined time period prior to receiving the user input, restoring the first setting to the first state; and in accordance with a determination, based on the comparison of the pattern of user behavior to the plurality of predefined conditions, that the user is not having difficulty with operating the device, maintaining the first setting in the second state.
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1. A method, comprising: at an electronic device comprising a processor and memory storing instructions for execution by the processor: while the device is operating with a first setting in a first state, detecting, at a first time, a change in settings of the device to change the first setting from the first state to a second state that is different from the first state; while the device is operating with the first setting in the second state, receiving, at a second time that is after the first time, a user input that corresponds to a pattern of user behavior, wherein the user input is a user voice input; in response to receiving the user input: comparing the pattern of user behavior to a plurality of predefined conditions that, when met, indicate that the user is having difficulty with operating the device, wherein a predefined condition of the plurality of predefined conditions includes the user voice input containing one or more predetermined words associated with user difficulty; in accordance with a determination, based on the comparison of the pattern of user behavior to the plurality of predefined conditions, that the device changed the first setting from the first state to the second state within a predetermined time period prior to receiving the user input, restoring the first setting to the first state; and in accordance with a determination, based on the comparison of the pattern of user behavior to the plurality of predefined conditions, that the user is not having difficulty with operating the device, maintaining the first setting in the second state. 3. The method of claim 1 , wherein the predetermined time is a predetermined number of minutes.
| 0.900419 |
8,370,131 | 1 | 5 |
1. A method, using a processor, for providing dictionary services to a terminal, the method comprising: displaying a dictionary service window associated with a web browser on a screen of the terminal in response to detection of a click for executing dictionary services; receiving an input query and determining, by the processor, whether the input query exceeds a number of bytes, and if the input query exceeds the number of bytes, the input inquiry is an input query for requesting pronunciation; and selectively providing, by the processor, either a translation data corresponding to an input query for requesting meaning or a pronunciation data corresponding to the input query for requesting pronunciation according to the determination.
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1. A method, using a processor, for providing dictionary services to a terminal, the method comprising: displaying a dictionary service window associated with a web browser on a screen of the terminal in response to detection of a click for executing dictionary services; receiving an input query and determining, by the processor, whether the input query exceeds a number of bytes, and if the input query exceeds the number of bytes, the input inquiry is an input query for requesting pronunciation; and selectively providing, by the processor, either a translation data corresponding to an input query for requesting meaning or a pronunciation data corresponding to the input query for requesting pronunciation according to the determination. 5. The method of claim 1 , further comprising: providing a word or an expression similar to the input query for requesting meaning or pronunciation if the processor fails to retrieve the translation data corresponding to the input query for requesting meaning or pronunciation.
| 0.734165 |
9,754,593 | 12 | 13 |
12. A computer system for identifying at least one speaker from a speech segment obtained by a computer by determining one or more words of the speech segment are determined by the computer by identifying one or more words of the speech segment by identifying one or more portions of a sound wave having a sound wave contour between silences, the computer comprising at least one processor, one or more memories, one or more computer readable storage media having program instructions executable by the computer to perform the program instructions comprising: analyzing, by the computer, the sound wave contour of at least a portion of the sound wave to determine one or more variations within the sound wave contour; assigning, by the computer, one or more features to the one or more variations by selecting, by the computer, a feature from a plurality of features based on slope characteristics of the sound wave contour representing the one or more portions of a sound wave having a sound wave contour between silences; mapping, by the computer, one or more assigned features to one or more sound constructs, wherein the one or more sound constructs are at least part of word; determining, by the computer, parameters of the assigned features and order in which the parameters occur within the sound wave contour to indicate the start of a vowel in the speech segment; grouping, by the computer, the parameters into predefined characteristics; combining, by the computer, the predefined characteristics into a voice characteristic group; and comparing, by the computer, the voice characteristic group to a plurality of existing voice characteristic groups each of the plurality of voice characteristic groups being attributed to one of the plurality of single speakers and, if the predefined characteristics of the voice characteristic group match the predefined characteristics of one of the plurality of existing voice characteristic groups, by the computer, the sound construct to a speaker identified by the existing voice characteristic group matching the voice characteristic group.
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12. A computer system for identifying at least one speaker from a speech segment obtained by a computer by determining one or more words of the speech segment are determined by the computer by identifying one or more words of the speech segment by identifying one or more portions of a sound wave having a sound wave contour between silences, the computer comprising at least one processor, one or more memories, one or more computer readable storage media having program instructions executable by the computer to perform the program instructions comprising: analyzing, by the computer, the sound wave contour of at least a portion of the sound wave to determine one or more variations within the sound wave contour; assigning, by the computer, one or more features to the one or more variations by selecting, by the computer, a feature from a plurality of features based on slope characteristics of the sound wave contour representing the one or more portions of a sound wave having a sound wave contour between silences; mapping, by the computer, one or more assigned features to one or more sound constructs, wherein the one or more sound constructs are at least part of word; determining, by the computer, parameters of the assigned features and order in which the parameters occur within the sound wave contour to indicate the start of a vowel in the speech segment; grouping, by the computer, the parameters into predefined characteristics; combining, by the computer, the predefined characteristics into a voice characteristic group; and comparing, by the computer, the voice characteristic group to a plurality of existing voice characteristic groups each of the plurality of voice characteristic groups being attributed to one of the plurality of single speakers and, if the predefined characteristics of the voice characteristic group match the predefined characteristics of one of the plurality of existing voice characteristic groups, by the computer, the sound construct to a speaker identified by the existing voice characteristic group matching the voice characteristic group. 13. The computer system of claim 12 , wherein if a prior voice characteristic group is not present, forming, by the computer, a new voice characteristic group and storing the new voice characteristic group in a repository.
| 0.909976 |
9,990,442 | 1 | 3 |
1. A computer implemented method for determining search results, comprising the steps of: receiving, by a computer processing device, an at least partial search term input into a search interface; accessing a database to identify and retrieve keywords based on the at least partial search term and at least one keyword attribute associated with each keyword, wherein the at least one keyword attribute is based on the number of times each keyword has been previously searched for within a predetermined time period, and communicating the keywords and at least one keyword attribute to a relevance server comprising a computer processing device; accessing the database to identify and retrieve search results based on each keyword and at least one search attribute associated with each search result and communicating the search results and at least one search attribute to the relevance server; processing, at the relevance server, the keywords and at least one keyword attribute and the search results and at least one search attribute, the processing step comprising: transforming the at least one keyword attribute and the at least one search attribute into a relevance attribute for each search result, comparing the relevance attributes of the search results, then generating an output, by the computer processing device, displaying at least one of the search results based upon the results of the comparison of the relevance attributes of the search results, and at least one of the retrieved keywords for selection by a user in conjunction with the displayed search results, receiving, at the relevance server, notification that one of the displayed keywords has been highlighted by the user, and processing the notification to transform the keyword attribute associated with the highlighted keyword into a higher weighted keyword attribute; receiving, by the computer processing device, entry of one or more additional characters to the at least partial search term to transform the at least partial search term into an updated at least partial search term; accessing the database to identify and retrieve second keywords and at least one second keyword attribute associated with each second keyword, based on the updated at least partial search term; accessing the database to identify and retrieve second search results based on the second keywords retrieved, and at least one second search attribute associated with each second search result; and processing, at the relevance server, the second keywords and at least one second keyword attribute and the second search results and at least one second search attributes, comprising: generating an output, by the computer processing device, updating the search results displayed to reflect any changes following the entry of additional characters to the at least partial search term.
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1. A computer implemented method for determining search results, comprising the steps of: receiving, by a computer processing device, an at least partial search term input into a search interface; accessing a database to identify and retrieve keywords based on the at least partial search term and at least one keyword attribute associated with each keyword, wherein the at least one keyword attribute is based on the number of times each keyword has been previously searched for within a predetermined time period, and communicating the keywords and at least one keyword attribute to a relevance server comprising a computer processing device; accessing the database to identify and retrieve search results based on each keyword and at least one search attribute associated with each search result and communicating the search results and at least one search attribute to the relevance server; processing, at the relevance server, the keywords and at least one keyword attribute and the search results and at least one search attribute, the processing step comprising: transforming the at least one keyword attribute and the at least one search attribute into a relevance attribute for each search result, comparing the relevance attributes of the search results, then generating an output, by the computer processing device, displaying at least one of the search results based upon the results of the comparison of the relevance attributes of the search results, and at least one of the retrieved keywords for selection by a user in conjunction with the displayed search results, receiving, at the relevance server, notification that one of the displayed keywords has been highlighted by the user, and processing the notification to transform the keyword attribute associated with the highlighted keyword into a higher weighted keyword attribute; receiving, by the computer processing device, entry of one or more additional characters to the at least partial search term to transform the at least partial search term into an updated at least partial search term; accessing the database to identify and retrieve second keywords and at least one second keyword attribute associated with each second keyword, based on the updated at least partial search term; accessing the database to identify and retrieve second search results based on the second keywords retrieved, and at least one second search attribute associated with each second search result; and processing, at the relevance server, the second keywords and at least one second keyword attribute and the second search results and at least one second search attributes, comprising: generating an output, by the computer processing device, updating the search results displayed to reflect any changes following the entry of additional characters to the at least partial search term. 3. The method of claim 1 , wherein at least one of the search attribute and the second search attribute is based on the number of times a search result is selected following a keyword search.
| 0.597046 |
8,290,949 | 28 | 29 |
28. The computer-implementable method of claim 24 , further comprising: in response to determining that a duplicate name instance was a superior naming context of another resource stored in a CMDB table, constructing a valid name for said other resource using a newly selected master name.
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28. The computer-implementable method of claim 24 , further comprising: in response to determining that a duplicate name instance was a superior naming context of another resource stored in a CMDB table, constructing a valid name for said other resource using a newly selected master name. 29. The computer-implementable method of claim 28 , further comprising: cleaning up one or more CMDB databases by replacing all references to alias names with new master names.
| 0.5 |
9,223,836 | 6 | 7 |
6. The non-transitory computer-readable medium of claim 5 wherein the at least one negation rule comprises a suffix negation rule comprising that a suffix negation term appear after the key term in the same sentence without the prefix negating term within the selected proximity.
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6. The non-transitory computer-readable medium of claim 5 wherein the at least one negation rule comprises a suffix negation rule comprising that a suffix negation term appear after the key term in the same sentence without the prefix negating term within the selected proximity. 7. The non-transitory computer-readable medium of claim 6 wherein the at least one prefix negation term comprises at least one first member of a first group consisting of no, without, history, resolution, rule out, not see, evaluate, risks, risk, and resolved and the at least one suffix negation term comprises at least one second member of a second group consisting of resolved, not demonstrated, not seen, not evident, not visualized, not confirmed, not noted, not identified, not present, not appreciated, not apparent, and not detected.
| 0.5 |
9,613,024 | 14 | 15 |
14. The system of claim 13 , wherein the first score is produced based on the number of text units that contain the first term or the one or more second terms, or the number of occurrences of the first term or the one or more second terms in the text units.
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14. The system of claim 13 , wherein the first score is produced based on the number of text units that contain the first term or the one or more second terms, or the number of occurrences of the first term or the one or more second terms in the text units. 15. The system of claim 14 , wherein the first score is produced further by dividing the first score by the total number of text units in the first group.
| 0.5 |
9,043,423 | 42 | 50 |
42. A method comprising receiving information from which at least one of the following can be derived: content of a message to be delivered from a first party to a second party about a life event, a manner of delivery of the message, a future time when the message is to be delivered, or the identity of the second party, in which the received information includes information indicative of a relationship between the first party and the second party, in which the content, the future time, or both are not present in the received information, inferring one or more of the content, the manner of delivery, the future time, or the identity of the second party based at least in part on at least some of the received information, including inferring the identity of the second party based on the received information indicative of the relationship between the first party and the second party, automatically on behalf of the first party, forming, based on the received information and one or more of the inferred content or the inferred manner of delivery, an integrated, conversational multimedia message that is to be part of a customized natural language dialog with the second party.
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42. A method comprising receiving information from which at least one of the following can be derived: content of a message to be delivered from a first party to a second party about a life event, a manner of delivery of the message, a future time when the message is to be delivered, or the identity of the second party, in which the received information includes information indicative of a relationship between the first party and the second party, in which the content, the future time, or both are not present in the received information, inferring one or more of the content, the manner of delivery, the future time, or the identity of the second party based at least in part on at least some of the received information, including inferring the identity of the second party based on the received information indicative of the relationship between the first party and the second party, automatically on behalf of the first party, forming, based on the received information and one or more of the inferred content or the inferred manner of delivery, an integrated, conversational multimedia message that is to be part of a customized natural language dialog with the second party. 50. The method of claim 42 , comprising forming the message in response to a conventionally asked question from the second party.
| 0.749027 |
7,693,720 | 1 | 13 |
1. A mobile system responsive to a user generated natural language speech utterance, comprising: a speech unit connected to a computer device on a vehicle, wherein the speech unit receives a natural language speech utterance from a user and converts the received natural language speech utterance into an electronic signal; and a natural language speech processing system connected to the computer device on the vehicle, wherein the natural language speech processing system receives, processes, and responds to the electronic signal using data received from a plurality of domain agents, wherein the natural language speech processing system includes: a speech recognition engine that recognizes at least one of words or phrases from the electronic signal using at least the data received from the plurality of domain agents, wherein the data used by the speech recognition engine includes a plurality of dictionary and phrase entries that are dynamically updated based on at least a history of a current dialog and one or more prior dialogs associated with the user; a parser that interprets the recognized words or phrases, wherein the parser uses at least the data received from the plurality of domain agents to interpret the recognized words or phrases, wherein the parser interprets the recognized words or phrases by: determining a context for the natural language speech utterance; selecting at least one of the plurality of domain agents based on the determined context; and transforming the recognized words or phrases into at least one of a question or a command, wherein the at least one question or command is formulated in a grammar that the selected domain agent uses to process the formulated question or command; and an agent architecture that communicatively couples services of each of an agent manager, a system agent, the plurality of domain agents, and an agent library that includes one or more utilities that can be used by the system agent and the plurality of domain agents, wherein the selected domain agent uses the communicatively coupled services to create a response to the formulated question or command and format the response for presentation to the user.
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1. A mobile system responsive to a user generated natural language speech utterance, comprising: a speech unit connected to a computer device on a vehicle, wherein the speech unit receives a natural language speech utterance from a user and converts the received natural language speech utterance into an electronic signal; and a natural language speech processing system connected to the computer device on the vehicle, wherein the natural language speech processing system receives, processes, and responds to the electronic signal using data received from a plurality of domain agents, wherein the natural language speech processing system includes: a speech recognition engine that recognizes at least one of words or phrases from the electronic signal using at least the data received from the plurality of domain agents, wherein the data used by the speech recognition engine includes a plurality of dictionary and phrase entries that are dynamically updated based on at least a history of a current dialog and one or more prior dialogs associated with the user; a parser that interprets the recognized words or phrases, wherein the parser uses at least the data received from the plurality of domain agents to interpret the recognized words or phrases, wherein the parser interprets the recognized words or phrases by: determining a context for the natural language speech utterance; selecting at least one of the plurality of domain agents based on the determined context; and transforming the recognized words or phrases into at least one of a question or a command, wherein the at least one question or command is formulated in a grammar that the selected domain agent uses to process the formulated question or command; and an agent architecture that communicatively couples services of each of an agent manager, a system agent, the plurality of domain agents, and an agent library that includes one or more utilities that can be used by the system agent and the plurality of domain agents, wherein the selected domain agent uses the communicatively coupled services to create a response to the formulated question or command and format the response for presentation to the user. 13. The mobile system according to claim 1 , wherein the communicatively coupled services include at least one remotely located service and the selected domain agent includes data for controlling or communicating with the remotely located service.
| 0.810583 |
8,529,263 | 1 | 7 |
1. A method of constructing at least a part of a fiber-based garment by a user, comprising: providing a non-transitory computer readable medium having stored thereon computer-executable instructions; providing a display screen device; receiving electronic instructional content from a plurality of instructional manuals, the instructional content comprising a plurality of instructional parts; selecting a plurality of instructional parts to enable construction of at least part of a fiber-based garment; editing one or more of the plurality of instructional parts to create at least one edited instructional part; assembling the at least one edited instructional part with the plurality of instructional parts to create an integrated assembly instruction set; presenting the integrated assembly instruction set to the user by at least one of a user interface, a display screen device, a printed document and electronic voice instructions; tracking the progress of the user with respect to the integrated assembly instruction set; presenting at least one set of companion instructions to the user to execute, the companion instructions presented based upon user progress with respect to at least one of: i) a row of instructions, and ii) the plurality of instruction parts; and constructing at least a part of a fiber-based garment by the user.
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1. A method of constructing at least a part of a fiber-based garment by a user, comprising: providing a non-transitory computer readable medium having stored thereon computer-executable instructions; providing a display screen device; receiving electronic instructional content from a plurality of instructional manuals, the instructional content comprising a plurality of instructional parts; selecting a plurality of instructional parts to enable construction of at least part of a fiber-based garment; editing one or more of the plurality of instructional parts to create at least one edited instructional part; assembling the at least one edited instructional part with the plurality of instructional parts to create an integrated assembly instruction set; presenting the integrated assembly instruction set to the user by at least one of a user interface, a display screen device, a printed document and electronic voice instructions; tracking the progress of the user with respect to the integrated assembly instruction set; presenting at least one set of companion instructions to the user to execute, the companion instructions presented based upon user progress with respect to at least one of: i) a row of instructions, and ii) the plurality of instruction parts; and constructing at least a part of a fiber-based garment by the user. 7. The method of claim 1 , wherein the companion instructions are executed in parallel with the integrated assembly instruction set.
| 0.6 |
7,908,132 | 7 | 9 |
7. A computer-implemented method for providing writing assistance to a user, the method comprising: providing the writing assistance based on an automated statistical comparison, by a computer processor that is a component of the computer, of a well-formed collection of text with a corresponding collection of text that is similar to the well-formed collection of text but includes an intentionally and manually inserted error, wherein the well-formed and corresponding collections of text are in the same language, and wherein the automated statistical comparison includes statistical alignment that factors in syntactical relationships between words in at least one of the well-formed and corresponding collections of text.
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7. A computer-implemented method for providing writing assistance to a user, the method comprising: providing the writing assistance based on an automated statistical comparison, by a computer processor that is a component of the computer, of a well-formed collection of text with a corresponding collection of text that is similar to the well-formed collection of text but includes an intentionally and manually inserted error, wherein the well-formed and corresponding collections of text are in the same language, and wherein the automated statistical comparison includes statistical alignment that factors in syntactical relationships between words in at least one of the well-formed and corresponding collections of text. 9. The method of claim 7 , wherein the writing assistance provided is a list of modifications that will resolve an error contained in an input received from the user, the modifications in the list reflecting a ranking indicative of which of the modifications is most likely to provide an accurate remedy to resolve the error.
| 0.5 |
9,639,524 | 8 | 14 |
8. A system, comprising one or more computer processor circuits that are configured for natural language processing, wherein the one or more computer processor circuits are configured to: receive a text; identify a set of linguistic characteristics contained in the text, wherein linguistic characteristics include grammatical, syntactic, and idiomatic features of the text; determine a plurality of time periods in which the text was potentially written based on the set of linguistic characteristics; retrieve a set of reference documents for each time period in the plurality of time periods, in response to the determining the plurality of time periods in which the text was potentially written; produce a set of proximity scores the text by performing a set of proximity checks using the set of linguistic characteristics, the set of reference documents for each time period, and the text, wherein the proximity checks analyze a usage frequency of the set of linguistic characteristics and a temporal closeness of the plurality of time periods in the set of linguistic characteristics between the text and the set of reference documents for each time period are to one another; rank the plurality of time periods based on the set of proximity scores; and return a set of one or more ranked time periods of the plurality of time periods.
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8. A system, comprising one or more computer processor circuits that are configured for natural language processing, wherein the one or more computer processor circuits are configured to: receive a text; identify a set of linguistic characteristics contained in the text, wherein linguistic characteristics include grammatical, syntactic, and idiomatic features of the text; determine a plurality of time periods in which the text was potentially written based on the set of linguistic characteristics; retrieve a set of reference documents for each time period in the plurality of time periods, in response to the determining the plurality of time periods in which the text was potentially written; produce a set of proximity scores the text by performing a set of proximity checks using the set of linguistic characteristics, the set of reference documents for each time period, and the text, wherein the proximity checks analyze a usage frequency of the set of linguistic characteristics and a temporal closeness of the plurality of time periods in the set of linguistic characteristics between the text and the set of reference documents for each time period are to one another; rank the plurality of time periods based on the set of proximity scores; and return a set of one or more ranked time periods of the plurality of time periods. 14. The system of claim 8 , wherein: the reference documents are selected from the group consisting of social media, literature, government documents, and text books.
| 0.809633 |
9,329,823 | 1 | 2 |
1. A kiosk computing device, communicatively connected to both a scanner and a printing device, wherein the kiosk computing device is configured to: receive scan data from the scanner; wherein the scan data is generated from a scan, by the scanner, of a patient identifier code; wherein the scan data includes a digital representation of a patient identifier that identifies a patient user; the kiosk computing device is further configured to perform, in response to the kiosk computing device receiving the scan data from the scanner: determine, from the scan data, the patient identifier that identifies the patient user; retrieve, via one or more networks and based at least in part on the patient identifier, one or more particular documents from a repository associated with the patient user; wherein the repository is remote from the kiosk computing device, and the kiosk computing device is communicatively connected to the repository via the one or more networks; wherein the one or more particular documents were sent to the repository from a medical service provider that provides medical services to the patient user; wherein the medical service provider is different from the patient user; and cause at least one document of the one or more particular documents to be printed at the printing device; wherein the kiosk computing device is further configured to: log the patient user out; and in response to logging the patient user out, cause said at least one document of the one or more particular documents to be erased from the repository associated with the patient user.
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1. A kiosk computing device, communicatively connected to both a scanner and a printing device, wherein the kiosk computing device is configured to: receive scan data from the scanner; wherein the scan data is generated from a scan, by the scanner, of a patient identifier code; wherein the scan data includes a digital representation of a patient identifier that identifies a patient user; the kiosk computing device is further configured to perform, in response to the kiosk computing device receiving the scan data from the scanner: determine, from the scan data, the patient identifier that identifies the patient user; retrieve, via one or more networks and based at least in part on the patient identifier, one or more particular documents from a repository associated with the patient user; wherein the repository is remote from the kiosk computing device, and the kiosk computing device is communicatively connected to the repository via the one or more networks; wherein the one or more particular documents were sent to the repository from a medical service provider that provides medical services to the patient user; wherein the medical service provider is different from the patient user; and cause at least one document of the one or more particular documents to be printed at the printing device; wherein the kiosk computing device is further configured to: log the patient user out; and in response to logging the patient user out, cause said at least one document of the one or more particular documents to be erased from the repository associated with the patient user. 2. The kiosk computing device of claim 1 wherein: the scan data is received from the patient user; the kiosk computing device is located near an exit of a building of the medical service provider; and said receiving the scan data from the patient user is performed before said patient user exits the building.
| 0.749595 |
8,554,601 | 42 | 45 |
42. A computing device for selecting information to provide to users based on reputations of evaluators of the information, comprising: one or more processors; a content rater component configured to, when executed by at least one of the one or more processors: receive from a reviewer user a review related to an item available from a Web merchant; receive evaluations of the review from each of multiple evaluator users, each received evaluation including a quantitative assessment of contents of the review for each of one or more of multiple content rating dimensions available for use in assessing the review, each of the evaluator users having a single existing reputation weight for the Web merchant based at least in part on previous evaluations supplied by that evaluator user for multiple other reviews for items available from the Web merchant; and automatically generate at least one aggregate assessment of the content of the review based at least in part on combining quantitative assessments from the received evaluations for the review, one or more of the generated aggregate assessments being further based on the single existing reputation weights of the evaluator users in such a manner that a first quantitative assessment from a first evaluator user with a first reputation weight has a different impact on that generated aggregate assessment than that first quantitative assessment from a distinct second evaluator user with a distinct second reputation weight; an evaluator reputation assessor component configured to automatically update the single existing reputation weights for each of one or more of the evaluator users for the Web merchant based on a relationship of the quantitative assessments from the evaluation of that evaluator user to the quantitative assessments from the evaluations of other of the evaluator users; and a content manager system configured to, when executed by at least one of the one or more processors, determine whether to provide the review to another user based at least in part on one or more of the automatically generated aggregate assessments for the content of the review.
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42. A computing device for selecting information to provide to users based on reputations of evaluators of the information, comprising: one or more processors; a content rater component configured to, when executed by at least one of the one or more processors: receive from a reviewer user a review related to an item available from a Web merchant; receive evaluations of the review from each of multiple evaluator users, each received evaluation including a quantitative assessment of contents of the review for each of one or more of multiple content rating dimensions available for use in assessing the review, each of the evaluator users having a single existing reputation weight for the Web merchant based at least in part on previous evaluations supplied by that evaluator user for multiple other reviews for items available from the Web merchant; and automatically generate at least one aggregate assessment of the content of the review based at least in part on combining quantitative assessments from the received evaluations for the review, one or more of the generated aggregate assessments being further based on the single existing reputation weights of the evaluator users in such a manner that a first quantitative assessment from a first evaluator user with a first reputation weight has a different impact on that generated aggregate assessment than that first quantitative assessment from a distinct second evaluator user with a distinct second reputation weight; an evaluator reputation assessor component configured to automatically update the single existing reputation weights for each of one or more of the evaluator users for the Web merchant based on a relationship of the quantitative assessments from the evaluation of that evaluator user to the quantitative assessments from the evaluations of other of the evaluator users; and a content manager system configured to, when executed by at least one of the one or more processors, determine whether to provide the review to another user based at least in part on one or more of the automatically generated aggregate assessments for the content of the review. 45. The computing device of claim 42 wherein the automatic generating of the at least one aggregate assessments of the content of the review is further based in part on an existing reputation weight of the reviewer user from which the review was received.
| 0.927557 |
8,522,135 | 1 | 7 |
1. A method for generating a transformation specification document describing transformations for transforming a received message to enable communication between first and second agents, wherein the first agent utilizes a first interface definition describing a first application programming interface and the second agent utilizes a second interface definition describing a second different application programming interface, the method comprising: comparing elements of the first and second interface definitions to determine additional elements of the second interface definition absent from the first interface definition, wherein the second interface definition is constrained by one or more rules describing permissible differences relative to the first interface definition and the comparing elements identifies violations of the rules; generating processing logic for transforming a received message from the second agent conforming to the second interface definition to a message for the first agent conforming to the first interface definition by removing all of the additional elements from the received message not contained in the first interface definition to enable processing of the received message by the first agent and communication between the first and second agents; and generating the transformation specification document using the generated processing logic.
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1. A method for generating a transformation specification document describing transformations for transforming a received message to enable communication between first and second agents, wherein the first agent utilizes a first interface definition describing a first application programming interface and the second agent utilizes a second interface definition describing a second different application programming interface, the method comprising: comparing elements of the first and second interface definitions to determine additional elements of the second interface definition absent from the first interface definition, wherein the second interface definition is constrained by one or more rules describing permissible differences relative to the first interface definition and the comparing elements identifies violations of the rules; generating processing logic for transforming a received message from the second agent conforming to the second interface definition to a message for the first agent conforming to the first interface definition by removing all of the additional elements from the received message not contained in the first interface definition to enable processing of the received message by the first agent and communication between the first and second agents; and generating the transformation specification document using the generated processing logic. 7. The method as claimed in claim 1 , wherein the first and second interface definitions are specified in XML.
| 0.77459 |
9,075,760 | 21 | 23 |
21. A system for sharing audiobook customizations, the system comprising: an electronic data store configured to store one or more audiobook narration settings files; and a server computing device in communication with the electronic data store, the server computing device configured to: receive, from a first user computing device, a request for an audiobook narration settings file; in response to the request, access a first social graph, the first social graph being affiliated with a user of the first user computing device and comprising a plurality of individuals related to the user of the first user computing device; identify, from the first social graph, a first individual of the plurality of individuals related to the user of the first user computing device, wherein the first individual has generated at least one audiobook narration settings file, the at least one audiobook narration settings file including audiobook narration settings specified by the first individual; identify the at least one audiobook narration settings file generated by the first individual identified in the first social graph; retrieve, from the electronic data store, the at least one audiobook narration settings file; and transmit the at least one audiobook narration settings file to the first user computing device.
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21. A system for sharing audiobook customizations, the system comprising: an electronic data store configured to store one or more audiobook narration settings files; and a server computing device in communication with the electronic data store, the server computing device configured to: receive, from a first user computing device, a request for an audiobook narration settings file; in response to the request, access a first social graph, the first social graph being affiliated with a user of the first user computing device and comprising a plurality of individuals related to the user of the first user computing device; identify, from the first social graph, a first individual of the plurality of individuals related to the user of the first user computing device, wherein the first individual has generated at least one audiobook narration settings file, the at least one audiobook narration settings file including audiobook narration settings specified by the first individual; identify the at least one audiobook narration settings file generated by the first individual identified in the first social graph; retrieve, from the electronic data store, the at least one audiobook narration settings file; and transmit the at least one audiobook narration settings file to the first user computing device. 23. The system of claim 21 , wherein the server computing device is further configured to: access a second social graph, the second social graph being affiliated with a user of a second computing device and comprising a plurality of individuals related to the user of the second computing device; determine that the first individual identified from the first social graph is also in the second social graph, transmit, to the second computing device, a recommendation to request the at least one audiobook narration settings file, the at least one audiobook narration settings file including the audiobook narration settings specified by the first individual; receive, from the second user computing device, a request for the at least one audiobook narration settings file; in response to the request, retrieve, from the electronic data store, the at least one audiobook narration settings file; and transmit the at least one audiobook narration settings file to the second user computing device.
| 0.502997 |
8,115,658 | 16 | 17 |
16. A handheld electronic device comprising: a processor apparatus comprising a processor and a memory in electronic communication with one another, the memory having stored therein a plurality of objects comprising a plurality of language objects and a plurality of linguistic elements, at least some of the language objects each comprising a number of the linguistic elements; and an interface apparatus having an input portion comprising a plurality of input members, at least some of the input members each having a number of the linguistic elements assigned thereto; the memory further having stored therein a number of routines which, when executed on the processor, cause the handheld electronic device to perform operations comprising: detecting an input comprising a number of input member actuations including a current input member actuation; identifying linguistic elements corresponding to the input member actuations; identifying a language object having at least an initial portion that corresponds with the linguistic elements of the input; identifying in the language object at least one of: a current linguistic element that is consistent with a linguistic element assigned to the input member of the current input member actuation and that is positioned in the language object at a location that corresponds with the current input member actuation, and a predictive linguistic element that is positioned in the language object at a location adjacent and subsequent to the current linguistic element; and highlighting, on the at least some input members, the current linguistic element and the predictive linguistic element.
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16. A handheld electronic device comprising: a processor apparatus comprising a processor and a memory in electronic communication with one another, the memory having stored therein a plurality of objects comprising a plurality of language objects and a plurality of linguistic elements, at least some of the language objects each comprising a number of the linguistic elements; and an interface apparatus having an input portion comprising a plurality of input members, at least some of the input members each having a number of the linguistic elements assigned thereto; the memory further having stored therein a number of routines which, when executed on the processor, cause the handheld electronic device to perform operations comprising: detecting an input comprising a number of input member actuations including a current input member actuation; identifying linguistic elements corresponding to the input member actuations; identifying a language object having at least an initial portion that corresponds with the linguistic elements of the input; identifying in the language object at least one of: a current linguistic element that is consistent with a linguistic element assigned to the input member of the current input member actuation and that is positioned in the language object at a location that corresponds with the current input member actuation, and a predictive linguistic element that is positioned in the language object at a location adjacent and subsequent to the current linguistic element; and highlighting, on the at least some input members, the current linguistic element and the predictive linguistic element. 17. The handheld electronic device of claim 16 wherein a portion of the input members each have as the number of linguistic elements assigned thereto a plurality of linguistic elements assigned thereto, wherein the objects further comprise a disambiguation routine executable on the processor, and wherein the operations further comprise: employing the disambiguation routine to identify as a default language object a language object having at least an initial portion that corresponds with the linguistic elements of input; and responsive to each input member actuation of the input, highlighting, on the at least some input members, a linguistic element assigned to the actuated input member that is consistent with a correspondingly positioned linguistic element in the default language object.
| 0.5 |
8,408,913 | 1 | 10 |
1. A system for facilitating language learning wherein said system is used upon samples of a target language, wherein each of said samples is called in this invention ORIGINAL EXTRACT, said target language is a foreign language or is the native language of the learner, wherein said system comprises: a) a display apparatus, b) a memory containing information related to said original extracts, c) control logic means to show one or more BLIND EXTRACTS for at least one of said original extracts, wherein a blind extract is a graphical entity whose fragments have certain correspondence with fragments of an original extract, said original extract being associated to said blind extract, a blind extract is made up of one or more fragments, the fragments of a blind extract are created by replacing the sounds of said fragments of said original extract by graphical objects that are different from the letters associated to said sounds in said target language, d) means to prevent the user from watching text that represents said language sample while the user is watching said blind extract, e) control logic means to choose at least a fragment of a blind extract wherein said fragment is associated to a fragment of an original extract, f) means to generate information about said fragment of an original extract which is associated to said fragment of a blind extract, and wherein at least two of the linguistic entities which are included in said sample of target language and which have different pronunciation from each other are represented by graphical objects which display the same information, wherein a linguistic entity is an entity of any of the following plurality of types: sentences, phrases, words, syllables, or phonemes, and wherein said system is used in isolation or as a complement to other language orientated system, for facilitating foreign language learning or for correcting a problem in the utilization of the native language.
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1. A system for facilitating language learning wherein said system is used upon samples of a target language, wherein each of said samples is called in this invention ORIGINAL EXTRACT, said target language is a foreign language or is the native language of the learner, wherein said system comprises: a) a display apparatus, b) a memory containing information related to said original extracts, c) control logic means to show one or more BLIND EXTRACTS for at least one of said original extracts, wherein a blind extract is a graphical entity whose fragments have certain correspondence with fragments of an original extract, said original extract being associated to said blind extract, a blind extract is made up of one or more fragments, the fragments of a blind extract are created by replacing the sounds of said fragments of said original extract by graphical objects that are different from the letters associated to said sounds in said target language, d) means to prevent the user from watching text that represents said language sample while the user is watching said blind extract, e) control logic means to choose at least a fragment of a blind extract wherein said fragment is associated to a fragment of an original extract, f) means to generate information about said fragment of an original extract which is associated to said fragment of a blind extract, and wherein at least two of the linguistic entities which are included in said sample of target language and which have different pronunciation from each other are represented by graphical objects which display the same information, wherein a linguistic entity is an entity of any of the following plurality of types: sentences, phrases, words, syllables, or phonemes, and wherein said system is used in isolation or as a complement to other language orientated system, for facilitating foreign language learning or for correcting a problem in the utilization of the native language. 10. A system as claimed in claim 1 wherein said means to prevent the user from watching said text is means to prevent said text from appearing on said display.
| 0.891245 |
8,332,745 | 1 | 4 |
1. An electronic filing system for registering a document, comprising: at least one processor coupled via a bus to a memory, the processor being programmed to control one or more of: a style-sheet setting unit configured to set any one of a plurality of style sheet data to any one of a plurality of folders, wherein a portion of a document is emphasized by converting the document using the set style sheet data, the portion of the document to be emphasized being different depending on each style sheet data; an input unit configured to input a document to be registered into one of the plurality of folders, the one of the plurality of folders being specified by a user; a style-sheet acquisition unit configured to acquire the style sheet data set to the specified folder into which the document is input by the input unit; a conversion unit configured to convert the input document using the style sheet data acquired by the style-sheet acquisition unit to obtain the input document of which a portion corresponding to the acquired style sheet data has been emphasized; a reduced-image generation unit configured to generate a reduced image from the obtained document of which the portion corresponding to the acquired style sheet data has been emphasized, wherein the reduced image itself provides a preview of a portion of the document; and a registration unit configured to link the reduced image generated by the reduced-image generation unit to the input document being stored into the specified folder.
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1. An electronic filing system for registering a document, comprising: at least one processor coupled via a bus to a memory, the processor being programmed to control one or more of: a style-sheet setting unit configured to set any one of a plurality of style sheet data to any one of a plurality of folders, wherein a portion of a document is emphasized by converting the document using the set style sheet data, the portion of the document to be emphasized being different depending on each style sheet data; an input unit configured to input a document to be registered into one of the plurality of folders, the one of the plurality of folders being specified by a user; a style-sheet acquisition unit configured to acquire the style sheet data set to the specified folder into which the document is input by the input unit; a conversion unit configured to convert the input document using the style sheet data acquired by the style-sheet acquisition unit to obtain the input document of which a portion corresponding to the acquired style sheet data has been emphasized; a reduced-image generation unit configured to generate a reduced image from the obtained document of which the portion corresponding to the acquired style sheet data has been emphasized, wherein the reduced image itself provides a preview of a portion of the document; and a registration unit configured to link the reduced image generated by the reduced-image generation unit to the input document being stored into the specified folder. 4. The electronic filing system according to claim 1 , wherein the processor is programmed to control one or more of: a determining unit configured to determine whether the document input by the input unit is a structured document; and a structurizing unit configured to structurize the input document into a structured document if the determining unit determines that the input document is not a structured document, wherein the conversion unit converts the structured document structurized by the structurizing unit using the style sheet data acquired by the style-sheet acquisition unit if the determining unit determines that the input document is not a structured document, and converts the input document using the style sheet data acquired by the style-sheet acquisition unit if the determining unit determines that the input document is a structured document.
| 0.5 |
7,970,824 | 1 | 4 |
1. A Capacity Planning Tool comprising: having a system run on a computing device in its memory for synchronizing and scheduling a multimedia document using a client/server model where said system is incorporated with an Internet browser tool having said system formalizes the representation of a multimedia document into hierarchy structure where said hierarchy structure being comprised of a four level hierarchy comprising of object, operation, time and precedence, where each successive level offers a fine-grain representation, where the system looks up the current status workloads on the servers and networks, where the system uses coded software to automatically perform translations between the levels representation, where the system uses coded software the will automatically perform all translations between the four levels representation, synchronizes the rendering of all objects and provides a schedule for fetching all objects from the server, transmitting all object from the server to the client through the network, and processing and rendering all objects at the client's computer, wherein the system performs the following tasks, models the extracted objects into an object flow graph (OFG), transforms the OFG into an operation flow graph (OPFG), transforms the OFG into a precedence flow graph (TFG), transforms the TFG into a precedence flow graph (PFG).
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1. A Capacity Planning Tool comprising: having a system run on a computing device in its memory for synchronizing and scheduling a multimedia document using a client/server model where said system is incorporated with an Internet browser tool having said system formalizes the representation of a multimedia document into hierarchy structure where said hierarchy structure being comprised of a four level hierarchy comprising of object, operation, time and precedence, where each successive level offers a fine-grain representation, where the system looks up the current status workloads on the servers and networks, where the system uses coded software to automatically perform translations between the levels representation, where the system uses coded software the will automatically perform all translations between the four levels representation, synchronizes the rendering of all objects and provides a schedule for fetching all objects from the server, transmitting all object from the server to the client through the network, and processing and rendering all objects at the client's computer, wherein the system performs the following tasks, models the extracted objects into an object flow graph (OFG), transforms the OFG into an operation flow graph (OPFG), transforms the OFG into a precedence flow graph (TFG), transforms the TFG into a precedence flow graph (PFG). 4. The Capacity Planning Tool as described in claim 1 , where the system looks up the current status workloads on the servers and networks.
| 0.600575 |
7,979,794 | 5 | 7 |
5. A computer program product recorded on computer readable medium for determining a target language for automatic programmatic translation of text in a first language, comprising: creating text in the first language, the text being in a single discrete document; using an HTML ‘lang’ attribute to set at least one target language for a portion of the text which is different from the first language; and automatically programmatically translating the portion having the first language into said at least one target language with said ‘lang’ attribute as a key for machine translation in order to produce a mixed translation of the text.
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5. A computer program product recorded on computer readable medium for determining a target language for automatic programmatic translation of text in a first language, comprising: creating text in the first language, the text being in a single discrete document; using an HTML ‘lang’ attribute to set at least one target language for a portion of the text which is different from the first language; and automatically programmatically translating the portion having the first language into said at least one target language with said ‘lang’ attribute as a key for machine translation in order to produce a mixed translation of the text. 7. The program product of claim 5 , wherein said at least one target language comprises a plurality of languages resulting in translation into a mixed language content.
| 0.815789 |
9,646,164 | 2 | 3 |
2. The method of claim 1 , wherein step ii includes examining the subset (R) of access requests in order to determine: a first set (D) of attributes that are associated with exactly the same set of values in all requests of said subset (R); a second set (A) of attributes that are absent in all requests of said subset (R); and a third set (U) of all other attributes not included in any of the sets (D or A) of attributes.
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2. The method of claim 1 , wherein step ii includes examining the subset (R) of access requests in order to determine: a first set (D) of attributes that are associated with exactly the same set of values in all requests of said subset (R); a second set (A) of attributes that are absent in all requests of said subset (R); and a third set (U) of all other attributes not included in any of the sets (D or A) of attributes. 3. The method of claim 2 , wherein step iii includes using said sets (D, A, U) of attributes to generate a partial access request, which: assigns, to each attribute in said first set (D) of attributes, the exact set of values associated to it by any request in said subset (R); and leaves all attributes in said set (U) undefined.
| 0.5 |
9,161,007 | 1 | 6 |
1. A method performed on at least one computing device that includes at least one processor and memory, the method comprising: receiving, by the at least one computing device, a selection of a theme script; and generating, by the at least one computing device a story, where the generated story comprises at least a portion of user assets organized according to the theme script, and where the generating comprises: applying a plurality of rules from the theme script to the user assets, selecting at least the portion of the user assets according to the theme script and meta data of the user assets, automatically generating an introduction section according to the theme script at a beginning of the generated story, where the introduction section comprises a title generated according to the meta data of the user assets in response to the meta data being sufficient for generating the title, and where the introduction section comprises a generic title in response to the meta data being insufficient for generating the title, and automatically generating a conclusion section according to the theme script at an end of the generated story.
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1. A method performed on at least one computing device that includes at least one processor and memory, the method comprising: receiving, by the at least one computing device, a selection of a theme script; and generating, by the at least one computing device a story, where the generated story comprises at least a portion of user assets organized according to the theme script, and where the generating comprises: applying a plurality of rules from the theme script to the user assets, selecting at least the portion of the user assets according to the theme script and meta data of the user assets, automatically generating an introduction section according to the theme script at a beginning of the generated story, where the introduction section comprises a title generated according to the meta data of the user assets in response to the meta data being sufficient for generating the title, and where the introduction section comprises a generic title in response to the meta data being insufficient for generating the title, and automatically generating a conclusion section according to the theme script at an end of the generated story. 6. The method of claim 1 where the theme script is configured for comprising an effects rule as part of the plurality of rules, the transition rule configured for defining visual effects and sound effects to be imposed on the portion of the user assets.
| 0.5 |
7,966,187 | 32 | 36 |
32. A method of evaluating compliance of at least one agent with at least one script that governs, at least in part, at least one interaction processed by at least one agent, the method comprising at least the following: creating at least one voice record of at least one interaction processed by the at least one agent at an agent workstation; defining at least first data relating to evaluating compliance of the at least one agent with the at least one script; and processing the at least one voice record against the at least first data, wherein the voice record is divided into viewable panel-level segments, wherein a panel-level time displacement stamp is assigned to each panel of the panel-level segments, wherein each panel-level segment is compared with a corresponding portion of the first data, wherein a confidence level threshold of the automatic speech recognition component is used to evaluate the accuracy of each panel-level segment based on an output of a comparison between each panel-level segment and its corresponding portion of the first data, wherein a score is assigned to each panel-level segment, each score indicating a match accuracy between the panel-level segment to which it is assigned and its assigned panel-level segment's corresponding portion of the first data, wherein the scores are evaluated against a standard, the standard defining a required score for each of the panel-level segments to be declared as a match to their corresponding portions of the first data, a set of action rules being applied to the output of the processing to direct a quality assurance action to be taken.
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32. A method of evaluating compliance of at least one agent with at least one script that governs, at least in part, at least one interaction processed by at least one agent, the method comprising at least the following: creating at least one voice record of at least one interaction processed by the at least one agent at an agent workstation; defining at least first data relating to evaluating compliance of the at least one agent with the at least one script; and processing the at least one voice record against the at least first data, wherein the voice record is divided into viewable panel-level segments, wherein a panel-level time displacement stamp is assigned to each panel of the panel-level segments, wherein each panel-level segment is compared with a corresponding portion of the first data, wherein a confidence level threshold of the automatic speech recognition component is used to evaluate the accuracy of each panel-level segment based on an output of a comparison between each panel-level segment and its corresponding portion of the first data, wherein a score is assigned to each panel-level segment, each score indicating a match accuracy between the panel-level segment to which it is assigned and its assigned panel-level segment's corresponding portion of the first data, wherein the scores are evaluated against a standard, the standard defining a required score for each of the panel-level segments to be declared as a match to their corresponding portions of the first data, a set of action rules being applied to the output of the processing to direct a quality assurance action to be taken. 36. The method of claim 32 , wherein creating at least one voice record includes creating at least one voice record of at least one interaction handled by at least one agent physically located in at least one location remote from at least one call center.
| 0.569257 |
10,007,895 | 1 | 2 |
1. A computer-implemented method for implementing an identity resolution service, comprising: receiving a plurality of identities on disparate online services comprising websites and service providers, wherein the identities are without having known correspondence to an entity registered on the identity resolution service when the identities are received; discovering which individual ones of the identities when compared to the plurality of the identities are likely to be for any same underlying entities, and in response to identifying two identities are likely for the same underlying entity, storing information that represents a discovered identity relationship, wherein the discovering and storing comprises: retrieving identity information for a first identity in a first internet service from the plurality of identities; retrieving identity information for a second identity in a second internet service from the plurality of identities; generating a first contextualized identity for the first identity using the retrieved identity information for the first identity, the first contextualized identity including standardized profile information of a first entity in the first internet service, and the profile information including relationship information of the first entity that associates the first identity with other identities as being inter-related or intra-related, wherein inter-related is defined by a relation to another entity and intra-related is defined by a relation to other identities representing the same entity; generating a second contextualized identity for the second identity using the retrieved identity information for the second identity, the second contextualized identity including standardized profile information of a second entity in the second internet service, and the profile information including relationship information of the second entity that associates the second identity with other identities as being inter-related or intra-related, wherein inter-related is defined by a relation to another entity and intra-related is defined by a relation to other identities representing the same entity; managing generated contextualized identities in a social graph; identifying the first contextualized identity as intra-related to the second contextualized identity through identity resolution on the social graph, the steps including: analyzing, by a computer processor, the contextualized identities and their profile information; processing the profile information of the first contextualized identity and the second contextualized identity to determine commonalties between the identities, the commonalties including: a similarity of the contextualized identity and profile information, a similarity of inter-related and intra-related identities, a directionality and character of associations between intra-related and inter-related identities; generating a likelihood value that the first contextualized identity represents the same underlying entity as the second contextualized identity based on the identified relations and determined commonalties; upon determining that the likelihood value is greater than a threshold value which indicates the two contextualized identities to be intra-related, aggregating the first contextualized identity and the second contextualized identity into a node representing an aggregated meta-identity, each aggregated meta-identity comprising a collection of intra-related contextualized identities that have been determined to represent the same underlying entity at a selected likelihood value or greater, wherein the aggregated meta-identity's node combines information and relationships from the plurality of contextualized identities to generate a unified profile; and responding to requests for graph operations for identity information by utilizing the aggregated meta-identity or unified profile associated with one or more intra-related contextualized identities in place of the one or more intra-related identities; wherein the identity resolution services is implemented using one or more computer memories.
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1. A computer-implemented method for implementing an identity resolution service, comprising: receiving a plurality of identities on disparate online services comprising websites and service providers, wherein the identities are without having known correspondence to an entity registered on the identity resolution service when the identities are received; discovering which individual ones of the identities when compared to the plurality of the identities are likely to be for any same underlying entities, and in response to identifying two identities are likely for the same underlying entity, storing information that represents a discovered identity relationship, wherein the discovering and storing comprises: retrieving identity information for a first identity in a first internet service from the plurality of identities; retrieving identity information for a second identity in a second internet service from the plurality of identities; generating a first contextualized identity for the first identity using the retrieved identity information for the first identity, the first contextualized identity including standardized profile information of a first entity in the first internet service, and the profile information including relationship information of the first entity that associates the first identity with other identities as being inter-related or intra-related, wherein inter-related is defined by a relation to another entity and intra-related is defined by a relation to other identities representing the same entity; generating a second contextualized identity for the second identity using the retrieved identity information for the second identity, the second contextualized identity including standardized profile information of a second entity in the second internet service, and the profile information including relationship information of the second entity that associates the second identity with other identities as being inter-related or intra-related, wherein inter-related is defined by a relation to another entity and intra-related is defined by a relation to other identities representing the same entity; managing generated contextualized identities in a social graph; identifying the first contextualized identity as intra-related to the second contextualized identity through identity resolution on the social graph, the steps including: analyzing, by a computer processor, the contextualized identities and their profile information; processing the profile information of the first contextualized identity and the second contextualized identity to determine commonalties between the identities, the commonalties including: a similarity of the contextualized identity and profile information, a similarity of inter-related and intra-related identities, a directionality and character of associations between intra-related and inter-related identities; generating a likelihood value that the first contextualized identity represents the same underlying entity as the second contextualized identity based on the identified relations and determined commonalties; upon determining that the likelihood value is greater than a threshold value which indicates the two contextualized identities to be intra-related, aggregating the first contextualized identity and the second contextualized identity into a node representing an aggregated meta-identity, each aggregated meta-identity comprising a collection of intra-related contextualized identities that have been determined to represent the same underlying entity at a selected likelihood value or greater, wherein the aggregated meta-identity's node combines information and relationships from the plurality of contextualized identities to generate a unified profile; and responding to requests for graph operations for identity information by utilizing the aggregated meta-identity or unified profile associated with one or more intra-related contextualized identities in place of the one or more intra-related identities; wherein the identity resolution services is implemented using one or more computer memories. 2. The method of claim 1 wherein the aggregated meta-identities are represented in a graph in the computer memories as nodes, said nodes being connected to a plurality of intra-related contextualized identities via edges describing their relation.
| 0.869174 |
9,241,101 | 1 | 12 |
1. A portable electronic device comprising: a display; user controls configured to enable a user to select between at least an up input, a down input, a left input, a right input, and a confirmation input; a storage memory; a data processing system; and a program memory communicatively connected to the data processing system and configured to store instructions configured to cause the data processing system to provide a user-specified input string, wherein the display is configured to display a string input interface wherein the string input interface includes: a string entry section for displaying the user-specified input string; and at least two independently scrollable character selection sections, the at least two independently scrollable character selection sections separate from the string entry section, wherein each independently scrollable character selection section enables a user to select from a corresponding predefined set of characters, wherein only a subset of the corresponding predefined set of characters are displayed in each of the at least two independently scrollable character selection sections at a particular time, wherein each of the at least two independently scrollable character selection sections enables scrolling between a plurality of characters within a respective independently scrollable character selection section; wherein the program memory includes instructions to accept user input provided using the user controls to sequentially select characters to specify the user-specified input string, wherein the up input and the down input are used to select one of the at least two independently scrollable character selection sections, the left input and the right input are used to scroll through the predefined set of characters in the selected independently scrollable character selection section to select a particular character, and the confirmation input is used to add the selected particular character to the input string displayed in the string entry section; and wherein the storage memory is configured to store the input string.
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1. A portable electronic device comprising: a display; user controls configured to enable a user to select between at least an up input, a down input, a left input, a right input, and a confirmation input; a storage memory; a data processing system; and a program memory communicatively connected to the data processing system and configured to store instructions configured to cause the data processing system to provide a user-specified input string, wherein the display is configured to display a string input interface wherein the string input interface includes: a string entry section for displaying the user-specified input string; and at least two independently scrollable character selection sections, the at least two independently scrollable character selection sections separate from the string entry section, wherein each independently scrollable character selection section enables a user to select from a corresponding predefined set of characters, wherein only a subset of the corresponding predefined set of characters are displayed in each of the at least two independently scrollable character selection sections at a particular time, wherein each of the at least two independently scrollable character selection sections enables scrolling between a plurality of characters within a respective independently scrollable character selection section; wherein the program memory includes instructions to accept user input provided using the user controls to sequentially select characters to specify the user-specified input string, wherein the up input and the down input are used to select one of the at least two independently scrollable character selection sections, the left input and the right input are used to scroll through the predefined set of characters in the selected independently scrollable character selection section to select a particular character, and the confirmation input is used to add the selected particular character to the input string displayed in the string entry section; and wherein the storage memory is configured to store the input string. 12. The portable electronic device of claim 1 wherein at least some of the user controls are provided using a joystick, wherein the joystick is moved in an up direction to provide the up input, the joystick is moved in a down direction to provide the down input, the joystick is moved in a left direction to provide the left input, and the joystick is moved in a right direction to provide the right input.
| 0.537585 |
9,729,381 | 1 | 17 |
1. A method comprising: receiving geographical location information for an entity; receiving a proprietary name for the entity; and geocoding the geographical location information into a hierarchical address by first transforming the geographical location information into latitude/longitude coordinates, next transforming the latitude/longitude coordinates to reference grid coordinates, wherein a reference grid for the geographical location is selected, at least in part, according to the geographical location's proximity to a regional centroid of a candidate reference grid or a governmental jurisdiction associated with the geographical location, and determining the hierarchical address based on the location of the latitude/longitude coordinates of the geographical location of the entity within the reference grid.
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1. A method comprising: receiving geographical location information for an entity; receiving a proprietary name for the entity; and geocoding the geographical location information into a hierarchical address by first transforming the geographical location information into latitude/longitude coordinates, next transforming the latitude/longitude coordinates to reference grid coordinates, wherein a reference grid for the geographical location is selected, at least in part, according to the geographical location's proximity to a regional centroid of a candidate reference grid or a governmental jurisdiction associated with the geographical location, and determining the hierarchical address based on the location of the latitude/longitude coordinates of the geographical location of the entity within the reference grid. 17. The method of claim 1 , wherein the geographical location information includes a street address, and the hierarchical address is a World Geographic Referencing System (WGRS) universal locational address.
| 0.702586 |
8,260,049 | 1 | 4 |
1. A method for determining a logical structure of a document, the method comprising: acquiring an image of the document; identifying one or more blocks in the image of the document; generating a hypothesis for at least one of the identified blocks in the image of the document (a “block hypothesis”); generating at least one document hypothesis for the image of the document, wherein said generating included referencing a plurality of document models, wherein each document model describes one or more possible logical structures, and wherein such logical structures are based on the presence of one or more blocks; selecting a document hypothesis based on its degree of correspondence with at least one block hypothesis; and forming a representation of the document based on the selected document hypothesis.
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1. A method for determining a logical structure of a document, the method comprising: acquiring an image of the document; identifying one or more blocks in the image of the document; generating a hypothesis for at least one of the identified blocks in the image of the document (a “block hypothesis”); generating at least one document hypothesis for the image of the document, wherein said generating included referencing a plurality of document models, wherein each document model describes one or more possible logical structures, and wherein such logical structures are based on the presence of one or more blocks; selecting a document hypothesis based on its degree of correspondence with at least one block hypothesis; and forming a representation of the document based on the selected document hypothesis. 4. The method of claim 1 , the method further comprising: saving the representation of the document in an extended format in a memory.
| 0.789969 |
7,885,904 | 1 | 5 |
1. A user-interface method of selecting and presenting a subset of content items of a first dataspace in which at least one content item of the subset is selected at least in part based on content preferences of the user learned from the user selecting content of a second dataspace, the method comprising: providing access to a first collection of content items of a first dataspace, each content item of the first collection having at least one associated descriptive term to describe the content item; providing access to a second collection of content items of a second dataspace, each content item of the second collection having at least one associated descriptive term to describe the content item; receiving selection actions of content items of the second collection from the user; a computer system determining a user preference signature by analyzing the descriptive terms of the selected content items of the second collection to learn the content preferences of the user for the content of the second dataspace; determining a relationship between the content items of the first dataspace and the content items of the second dataspace, the relationship defining which learned user content preferences of the user preference signature are relevant to the content items of the first dataspace; and subsequent to learning the content preferences of the user, selecting and presenting to the user at least one content item of the first dataspace based on the learned content preferences of the user determined to be relevant to the content items of the first dataspace.
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1. A user-interface method of selecting and presenting a subset of content items of a first dataspace in which at least one content item of the subset is selected at least in part based on content preferences of the user learned from the user selecting content of a second dataspace, the method comprising: providing access to a first collection of content items of a first dataspace, each content item of the first collection having at least one associated descriptive term to describe the content item; providing access to a second collection of content items of a second dataspace, each content item of the second collection having at least one associated descriptive term to describe the content item; receiving selection actions of content items of the second collection from the user; a computer system determining a user preference signature by analyzing the descriptive terms of the selected content items of the second collection to learn the content preferences of the user for the content of the second dataspace; determining a relationship between the content items of the first dataspace and the content items of the second dataspace, the relationship defining which learned user content preferences of the user preference signature are relevant to the content items of the first dataspace; and subsequent to learning the content preferences of the user, selecting and presenting to the user at least one content item of the first dataspace based on the learned content preferences of the user determined to be relevant to the content items of the first dataspace. 5. The method of claim 1 , wherein the first dataspace and second dataspace are different dataspaces.
| 0.951813 |
7,991,609 | 3 | 4 |
3. The method of claim 2 , wherein one of the evaluation modules extracts lexical features from the strings of text and evaluates the lexical features with a classifier.
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3. The method of claim 2 , wherein one of the evaluation modules extracts lexical features from the strings of text and evaluates the lexical features with a classifier. 4. The method of claim 3 , wherein the classifier further provides at least one of the suggested alternative strings of text, based on at least one lexical feature found to be a relatively close match for at least one string of text with non-standard usage.
| 0.5 |
9,704,480 | 1 | 8 |
1. An information processing apparatus, comprising: a circuitry configured to: receive: voice data of a user, wherein the voice data is related to an item; and a rating for the item based on an input other than the voice data, wherein the rating corresponds to a first numerical value selected from a first range of numerical values; convert the voice data into language text data; analyze the language text data to determine a second numerical value selected from a second range of numerical values; assign a weight to one among the rating or the analyzed language text data based on the other of the rating or the analyzed language text data; extract at least one recommendation item based on the assigned weight, the analyzed language text data and the rating; and change the first numerical value to make the first numerical value closer to a middle numerical value of the first range of numerical values, based on one of the first numerical value is less than a first threshold and the second numerical value is greater than a second threshold, or the first numerical value is greater than the first threshold and the second numerical value is less than the second threshold.
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1. An information processing apparatus, comprising: a circuitry configured to: receive: voice data of a user, wherein the voice data is related to an item; and a rating for the item based on an input other than the voice data, wherein the rating corresponds to a first numerical value selected from a first range of numerical values; convert the voice data into language text data; analyze the language text data to determine a second numerical value selected from a second range of numerical values; assign a weight to one among the rating or the analyzed language text data based on the other of the rating or the analyzed language text data; extract at least one recommendation item based on the assigned weight, the analyzed language text data and the rating; and change the first numerical value to make the first numerical value closer to a middle numerical value of the first range of numerical values, based on one of the first numerical value is less than a first threshold and the second numerical value is greater than a second threshold, or the first numerical value is greater than the first threshold and the second numerical value is less than the second threshold. 8. The information processing apparatus according to claim 1 , wherein the circuitry is further configured to determine the analyzed language text data as a main preference of the user, based on whether a first error between the analyzed language text data and a first predicted value of the analyzed language text data for a plurality of recommendation-candidate items from which the at least one recommendation item is extracted is less than a second error between the rating and a second predicted value of the rating for the plurality of recommendation-candidate items.
| 0.540865 |
9,727,606 | 1 | 2 |
1. A method comprising: based on a predicate that specifies criteria for filtering results of a query that targets a table, programming reconfigurable hardware of a filtering unit with the predicate; wherein the predicate specifies a condition for a particular column of the table; wherein programming the reconfigurable hardware with the predicate creates a filter unit hardware circuit that is configured to apply the predicate; causing the filter unit hardware circuit to generate a first predicate result by loading values, from the particular column, into the filter unit hardware circuit; wherein hardware configuration of the filter unit hardware circuit causes the predicate to be applied to the values; wherein the first predicate result identifies rows of the table that have values, within the particular column, that satisfy the condition specified by the predicate; selecting rows to return, as results of the query, based at least in part on the first predicate result; returning the selected rows as results to the query; based on a second predicate that specifies criteria for filtering results that targets the table, programming the reconfigurable hardware of the filtering unit with the second predicate; wherein the second predicate specifies a condition for a second column of the table; wherein programming the reconfigurable hardware with the predicate creates a second filter unit hardware circuit that is configured to apply the second predicate; causing the second filter unit hardware circuit to generate a second predicate result by loading values, from the second column, into the second filter unit hardware circuit; wherein hardware configuration of the second filter unit hardware circuit causes the second predicate to be applied to the values; wherein the second predicate result identifies rows of the table that have values, within the second column, that satisfy the condition specified by the second predicate; wherein the method is performed by one or more computing devices.
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1. A method comprising: based on a predicate that specifies criteria for filtering results of a query that targets a table, programming reconfigurable hardware of a filtering unit with the predicate; wherein the predicate specifies a condition for a particular column of the table; wherein programming the reconfigurable hardware with the predicate creates a filter unit hardware circuit that is configured to apply the predicate; causing the filter unit hardware circuit to generate a first predicate result by loading values, from the particular column, into the filter unit hardware circuit; wherein hardware configuration of the filter unit hardware circuit causes the predicate to be applied to the values; wherein the first predicate result identifies rows of the table that have values, within the particular column, that satisfy the condition specified by the predicate; selecting rows to return, as results of the query, based at least in part on the first predicate result; returning the selected rows as results to the query; based on a second predicate that specifies criteria for filtering results that targets the table, programming the reconfigurable hardware of the filtering unit with the second predicate; wherein the second predicate specifies a condition for a second column of the table; wherein programming the reconfigurable hardware with the predicate creates a second filter unit hardware circuit that is configured to apply the second predicate; causing the second filter unit hardware circuit to generate a second predicate result by loading values, from the second column, into the second filter unit hardware circuit; wherein hardware configuration of the second filter unit hardware circuit causes the second predicate to be applied to the values; wherein the second predicate result identifies rows of the table that have values, within the second column, that satisfy the condition specified by the second predicate; wherein the method is performed by one or more computing devices. 2. The method of claim 1 wherein the first predicate result is a bitvector and each bit of the bitvector corresponds to a particular row and identifies whether the particular row satisfies the condition specified by the predicate.
| 0.873904 |
7,752,031 | 25 | 26 |
25. The storage memory as set forth in claim 21 wherein said software transforms said pause relationship model to produce beginnings of translated snippets offset by a calculated delay from a beginning of a snippet which corresponds to a pause marker at a end of a mutual silence.
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25. The storage memory as set forth in claim 21 wherein said software transforms said pause relationship model to produce beginnings of translated snippets offset by a calculated delay from a beginning of a snippet which corresponds to a pause marker at a end of a mutual silence. 26. The storage memory as set forth in claim 25 wherein said delay is determined according to a proportional relationship mode of pause management.
| 0.5 |
9,971,841 | 7 | 12 |
7. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: develop source content using a source content taxonomy, using a content authoring service, and using a content architecture standard; store the source content in source content storage; assign one or more unique identifiers to the source content based on the source content taxonomy; generate Web content, wherein the Web content contains tags having references to the source content; insert the one or more unique identifiers into corresponding tags in the Web content; store the Web content in Web content storage; responsive to a user viewing from a Web server a page of Web content containing a given tag having a given unique identifier within the one or more unique identifiers, generate Web usage data recording the viewing of the page of Web content, wherein the given tag contains a reference to given item of content in the source content, wherein the reference to the given item of content comprises a uniform resource locator, and wherein inserting the one or more unique identifiers comprises inserting the given unique identifier into the uniform resource locator referencing the given item of content; and generate a Web metrics report based on the Web usage data, wherein the Web metrics report maps the viewing of the page of Web content to the source content taxonomy based on the given unique identifier.
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7. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: develop source content using a source content taxonomy, using a content authoring service, and using a content architecture standard; store the source content in source content storage; assign one or more unique identifiers to the source content based on the source content taxonomy; generate Web content, wherein the Web content contains tags having references to the source content; insert the one or more unique identifiers into corresponding tags in the Web content; store the Web content in Web content storage; responsive to a user viewing from a Web server a page of Web content containing a given tag having a given unique identifier within the one or more unique identifiers, generate Web usage data recording the viewing of the page of Web content, wherein the given tag contains a reference to given item of content in the source content, wherein the reference to the given item of content comprises a uniform resource locator, and wherein inserting the one or more unique identifiers comprises inserting the given unique identifier into the uniform resource locator referencing the given item of content; and generate a Web metrics report based on the Web usage data, wherein the Web metrics report maps the viewing of the page of Web content to the source content taxonomy based on the given unique identifier. 12. The computer program product of claim 7 , wherein assigning one or more unique identifiers to the source content based on the source content taxonomy comprises: generating a prototype usage metrics report; presenting the prototype usage metrics report to an author; and receiving modification of the one or more identifiers from the author.
| 0.5 |
9,990,923 | 1 | 2 |
1. A method for automated execution of computer software using intelligent speech recognition techniques, the method comprising: capturing, by a server computing device, a bitstream containing a digitized voice segment from a remote device as a speech file, the first digitized voice segment corresponding to speech submitted by a user of the remote device during a voice call; parsing, by the server computing device, the bitstream to locate the digitized voice segment; adjusting, by the server computing device, compression of the bitstream containing the digitized voice segment to enhance audio quality of the bitstream; analyzing, by the server computing device, the speech file to convert the speech file into text and extract a set of keywords from the converted text; displaying, by a client computing device coupled to the server computing device, the extracted keywords in a user interface of a display device; determining, by the server computing device, one or more computer software applications accessible to the client computing device; selecting, by the server computing device, at least one of the computer software applications that include functionality responsive to the keywords, comprising: generating an input vector comprising a sequence of numeric values, each value associated with a keyword and weighted according to a relative position of the keyword in the set of keywords, matching the input vector against a predefined set of vectors to determine one or more vectors that are similar to the input vector, identifying a label corresponding to each matched vector, wherein the label is associated with computer software functionality, and selecting one or more computer software applications that are associated with a most common label of the identified labels; and executing, by the client computing device, the functionality of the selected computer software applications that are responsive to the keywords.
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1. A method for automated execution of computer software using intelligent speech recognition techniques, the method comprising: capturing, by a server computing device, a bitstream containing a digitized voice segment from a remote device as a speech file, the first digitized voice segment corresponding to speech submitted by a user of the remote device during a voice call; parsing, by the server computing device, the bitstream to locate the digitized voice segment; adjusting, by the server computing device, compression of the bitstream containing the digitized voice segment to enhance audio quality of the bitstream; analyzing, by the server computing device, the speech file to convert the speech file into text and extract a set of keywords from the converted text; displaying, by a client computing device coupled to the server computing device, the extracted keywords in a user interface of a display device; determining, by the server computing device, one or more computer software applications accessible to the client computing device; selecting, by the server computing device, at least one of the computer software applications that include functionality responsive to the keywords, comprising: generating an input vector comprising a sequence of numeric values, each value associated with a keyword and weighted according to a relative position of the keyword in the set of keywords, matching the input vector against a predefined set of vectors to determine one or more vectors that are similar to the input vector, identifying a label corresponding to each matched vector, wherein the label is associated with computer software functionality, and selecting one or more computer software applications that are associated with a most common label of the identified labels; and executing, by the client computing device, the functionality of the selected computer software applications that are responsive to the keywords. 2. The method of claim 1 , wherein matching the input vector comprises determining, by the server computing device, a distance between the input vector and each vector in the predefined set of vectors; and choosing, by the server computing device, one or more of vectors in the predefined set of vectors where the distance is within a predetermined threshold.
| 0.711415 |
9,208,213 | 1 | 8 |
1. A system for presenting reports processed by an on-line analytical processing (OLAP) system over a network, the system comprising: at least one physical processing device that executes one or more computer program modules that: receive, from a user system through a web browser, a request for a workbook comprising a plurality of reports and a selection of one or more specified templates or filter combinations to format one or more of the plurality of reports; return control of the web browser to enable a user to use the web browser to perform one or more other tasks while the workbook request is being processed, wherein the one or more other tasks includes requesting an additional workbook; receive the workbook comprising the plurality of reports processed by the OLAP system in response to the workbook request; format one or more of the plurality of reports in the workbook in accordance with the selected one or more specified template or filter combinations received from the user system through the web browser in communication with the OLAP system over the network; build an interactive spreadsheet application for presenting the workbook at the web browser of the user system, wherein the interactive spreadsheet application configures an arrangement of the plurality of formatted reports in the workbook; and transmit the workbook including the plurality of formatted reports within a page over the network to the web browser of the user system through which the request was received, wherein the transmitted workbook is presented at the user system using the interactive spreadsheet application displayed within the web browser.
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1. A system for presenting reports processed by an on-line analytical processing (OLAP) system over a network, the system comprising: at least one physical processing device that executes one or more computer program modules that: receive, from a user system through a web browser, a request for a workbook comprising a plurality of reports and a selection of one or more specified templates or filter combinations to format one or more of the plurality of reports; return control of the web browser to enable a user to use the web browser to perform one or more other tasks while the workbook request is being processed, wherein the one or more other tasks includes requesting an additional workbook; receive the workbook comprising the plurality of reports processed by the OLAP system in response to the workbook request; format one or more of the plurality of reports in the workbook in accordance with the selected one or more specified template or filter combinations received from the user system through the web browser in communication with the OLAP system over the network; build an interactive spreadsheet application for presenting the workbook at the web browser of the user system, wherein the interactive spreadsheet application configures an arrangement of the plurality of formatted reports in the workbook; and transmit the workbook including the plurality of formatted reports within a page over the network to the web browser of the user system through which the request was received, wherein the transmitted workbook is presented at the user system using the interactive spreadsheet application displayed within the web browser. 8. The system of claim 1 , wherein the one or more template or filter combinations specify one or more predefined formats used to format the plurality of reports in the workbook.
| 0.716561 |
9,529,784 | 18 | 20 |
18. The computer-implemented method of claim 16 , further comprising causing display of an object graphically representing a geographic relationship between the client computing devices associated with the common characteristic.
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18. The computer-implemented method of claim 16 , further comprising causing display of an object graphically representing a geographic relationship between the client computing devices associated with the common characteristic. 20. The computer-implemented method of claim 18 , wherein the common characteristic comprises the requested network resource.
| 0.803459 |
8,630,972 | 13 | 17 |
13. A computer readable storage device comprising computer executable instructions that when executed perform a method for assessing an emotional sentiment related to a topic, comprising: identifying first social media content comprising a first link to a first article associated with the topic; assessing an emotional sentiment related to the first article as a function of one or more terms in the first social media content; identifying second social media content comprising a second link to a second article associated with the topic and comprising content similar to the first article, the second article comprising content similar to the first article when S(a i ,a j )/size(a i ) exceeds a predetermined threshold, where S(a i ,a j ) is a number of terms of a largest set of infrequent terms between the first article (a i ) and the second article (a j ) and size (a i ) is the number of terms in the larger of articles a i and a j ; assessing an emotional sentiment related to the second article as a function of one or more terms in the second social media content; and aggregating the emotional sentiment related to the first article with the emotional sentiment related to the second article to assess the emotional sentiment related to the topic.
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13. A computer readable storage device comprising computer executable instructions that when executed perform a method for assessing an emotional sentiment related to a topic, comprising: identifying first social media content comprising a first link to a first article associated with the topic; assessing an emotional sentiment related to the first article as a function of one or more terms in the first social media content; identifying second social media content comprising a second link to a second article associated with the topic and comprising content similar to the first article, the second article comprising content similar to the first article when S(a i ,a j )/size(a i ) exceeds a predetermined threshold, where S(a i ,a j ) is a number of terms of a largest set of infrequent terms between the first article (a i ) and the second article (a j ) and size (a i ) is the number of terms in the larger of articles a i and a j ; assessing an emotional sentiment related to the second article as a function of one or more terms in the second social media content; and aggregating the emotional sentiment related to the first article with the emotional sentiment related to the second article to assess the emotional sentiment related to the topic. 17. The computer readable storage device of claim 13 , the second article comprising content similar to the first article when a fraction of words in W(a i ) that are covered by at least one set of term sequences that occur in both the first article a i and the second article a j exceeds a predetermined threshold, where W(a i ) is a substring of all terms in the first article a i not covered by frequent terms.
| 0.51182 |
7,593,927 | 6 | 9 |
6. The data mining tool of claim 1 , further comprising an interface component that communicates the formatted portion of unstructured data to the data mining algorithm.
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6. The data mining tool of claim 1 , further comprising an interface component that communicates the formatted portion of unstructured data to the data mining algorithm. 9. The data mining tool of claim 6 , the received command is generated by a user.
| 0.900978 |
8,488,774 | 29 | 34 |
29. A system comprising: a real-time decision engine to receive information about a caller and identify a skill that is useful for providing service to the caller, the caller being associated with a plurality of parameters, the decision engine identifying the skill by predicting an action prior to caller input about the action, including generating scores for a plurality of statistical models, each statistical model representing a correlation between a subset of the plurality of parameters and an action that may be performed or requested to be performed by the caller, the score for each statistical model being generated using the statistical model and the subset of the plurality of parameters associated with the statistical model, the score for each statistical model providing information about a probability that the caller will perform an action associated with the statistical model or request the action to be performed, and identifying a skill based on the scores; a storage to store the statistical models; and a call router to route a call from the customer to a representative who has the skill.
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29. A system comprising: a real-time decision engine to receive information about a caller and identify a skill that is useful for providing service to the caller, the caller being associated with a plurality of parameters, the decision engine identifying the skill by predicting an action prior to caller input about the action, including generating scores for a plurality of statistical models, each statistical model representing a correlation between a subset of the plurality of parameters and an action that may be performed or requested to be performed by the caller, the score for each statistical model being generated using the statistical model and the subset of the plurality of parameters associated with the statistical model, the score for each statistical model providing information about a probability that the caller will perform an action associated with the statistical model or request the action to be performed, and identifying a skill based on the scores; a storage to store the statistical models; and a call router to route a call from the customer to a representative who has the skill. 34. The system of claim 29 wherein identifying the skill based on the scores comprises using a second layer of statistical modeling to determine the skill based on the scores.
| 0.727414 |
9,659,578 | 19 | 20 |
19. A computer implemented method for identifying significant speech frames within speech signals for facilitating speech recognition, said method comprising: storing instructions and data in a memory; receiving, using a processor, said instructions and data from said memory; storing, a set of computing instructions related to spectral analysis into a first repository, a set of computing instructions related to feature vector extractions into a second repository, a set of computing instructions related to frame weighting and a set of computing instructions related to suitability measure; receiving, by an input module, at least an input speech signal, wherein the speech signal is represented by a plurality of feature vectors; dividing, using a divider of a spectrum analyzer, the input speech signal into a plurality of speech frames and computing at least a spectral magnitude of each of the speech frames; extracting, using an extractor, at least a feature vector from each of the speech frames; receiving at a suitability engine of said computer, the speech frames and the corresponding spectral magnitude of each of speech frames for the purpose of computing a suitability measure for each of the speech frames: computing, by a spectral flatness module of said suitability engine, a spectral flatness measure for each of the speech frames and determining, by said spectral flatness module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the spectral flatness measure computed; computing, by an energy normalized variance module of said suitability engine, an energy normalized variance for each of the speech frame and determining, by said energy normalized variance module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the energy normalized variance computed; computing, by an entropy module of said suitability engine, an entropy for each of the speech frame and determining, by said entropy module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the entropy computed; computing, by a signal-to-noise ratio module of said suitability engine, a signal-to-noise ratio for each of the speech frame and determining, by said signal-to-noise ratio module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the signal-to-noise ratio computed; computing, by a similarity module of said suitability engine, a similarity measure for each of the speech frame and determining, by said similarity module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to similarity measure computed; calculating, by a final suitability measure module of said suitability engine, a final suitability measure by considering the spectral flatness measure, the energy normalized variance, the entropy, the signal-to-noise ratio and the similarity measure along with the corresponding suitability measures computed for each of said speech frames; and computing and assigning, by a frame weight assigner of said computer, at least a weight for each of the speech frames to identify significant speech frames based on the spectral magnitude and the final suitability measure of respective speech frame.
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19. A computer implemented method for identifying significant speech frames within speech signals for facilitating speech recognition, said method comprising: storing instructions and data in a memory; receiving, using a processor, said instructions and data from said memory; storing, a set of computing instructions related to spectral analysis into a first repository, a set of computing instructions related to feature vector extractions into a second repository, a set of computing instructions related to frame weighting and a set of computing instructions related to suitability measure; receiving, by an input module, at least an input speech signal, wherein the speech signal is represented by a plurality of feature vectors; dividing, using a divider of a spectrum analyzer, the input speech signal into a plurality of speech frames and computing at least a spectral magnitude of each of the speech frames; extracting, using an extractor, at least a feature vector from each of the speech frames; receiving at a suitability engine of said computer, the speech frames and the corresponding spectral magnitude of each of speech frames for the purpose of computing a suitability measure for each of the speech frames: computing, by a spectral flatness module of said suitability engine, a spectral flatness measure for each of the speech frames and determining, by said spectral flatness module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the spectral flatness measure computed; computing, by an energy normalized variance module of said suitability engine, an energy normalized variance for each of the speech frame and determining, by said energy normalized variance module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the energy normalized variance computed; computing, by an entropy module of said suitability engine, an entropy for each of the speech frame and determining, by said entropy module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the entropy computed; computing, by a signal-to-noise ratio module of said suitability engine, a signal-to-noise ratio for each of the speech frame and determining, by said signal-to-noise ratio module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the signal-to-noise ratio computed; computing, by a similarity module of said suitability engine, a similarity measure for each of the speech frame and determining, by said similarity module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to similarity measure computed; calculating, by a final suitability measure module of said suitability engine, a final suitability measure by considering the spectral flatness measure, the energy normalized variance, the entropy, the signal-to-noise ratio and the similarity measure along with the corresponding suitability measures computed for each of said speech frames; and computing and assigning, by a frame weight assigner of said computer, at least a weight for each of the speech frames to identify significant speech frames based on the spectral magnitude and the final suitability measure of respective speech frame. 20. The method as claimed in claim 19 , wherein said method further comprising: generating and transmitting, at a mel-filter-bank analyzer, at least a mel frequency cepstral coefficient (MFCC) for each of the speech frames for a time instance (t); receiving and generating, at a training module, at least a training model based on the computed MFCC and the weight assigned to each of the speech frames; receiving the training model, at a scoring module, and generate an output for a speech recognition decision module for identifying the potential speech frame.
| 0.5 |
7,689,927 | 25 | 27 |
25. A display system for managing a view-size of an electronic document, comprising: a display device; and a processor for: (a) rendering a user interface window; (b) rendering at least a portion of the electronic document in the user interface window; (c) storing a viewable document section corresponding to the view-size of the electronic document, wherein the viewable document section includes boundary information cumulative of only portions of the electronic document that have previously been displayed in the user interface window; (d) providing a first system that enables a user to change a displayed portion of the electronic document in the user interface window when at least a portion of information indicated by the stored boundary information in the viewable document section does not appear in the user interface window and the viewable document section also changes to include information indicative of a registering activity of any digitizing user-input at an outer portion of the user interface window, wherein the first system is not provided when all information indicated by the stored boundary information in the viewable document section appears in the user interface window and changes to the viewable document section with an additional input to include information indicative of a registering activity of any digitizing user-input at an outer portion of the user interface window that associates a user-input extending beyond the outer portion of the user interface window, while suppressing any scrolling view handle display or similar scroll bar display; and (e) providing a second system that enables a user to change a size of the user interface window, and responsive to the user interface window being enlarged, the stored boundary information in the viewable document section is adjusted based on any portion of the electronic document displayed for a first time within the user interface window.
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25. A display system for managing a view-size of an electronic document, comprising: a display device; and a processor for: (a) rendering a user interface window; (b) rendering at least a portion of the electronic document in the user interface window; (c) storing a viewable document section corresponding to the view-size of the electronic document, wherein the viewable document section includes boundary information cumulative of only portions of the electronic document that have previously been displayed in the user interface window; (d) providing a first system that enables a user to change a displayed portion of the electronic document in the user interface window when at least a portion of information indicated by the stored boundary information in the viewable document section does not appear in the user interface window and the viewable document section also changes to include information indicative of a registering activity of any digitizing user-input at an outer portion of the user interface window, wherein the first system is not provided when all information indicated by the stored boundary information in the viewable document section appears in the user interface window and changes to the viewable document section with an additional input to include information indicative of a registering activity of any digitizing user-input at an outer portion of the user interface window that associates a user-input extending beyond the outer portion of the user interface window, while suppressing any scrolling view handle display or similar scroll bar display; and (e) providing a second system that enables a user to change a size of the user interface window, and responsive to the user interface window being enlarged, the stored boundary information in the viewable document section is adjusted based on any portion of the electronic document displayed for a first time within the user interface window. 27. A display system according to claim 25 , wherein the second system enables the size of the user interface window to be changed through a user input device drag operation.
| 0.819876 |
9,997,069 | 3 | 6 |
3. The method of claim 1 , wherein the turn for navigation is a right turn, wherein playing the non-verbal prompt comprises: playing a first set of non-verbal tones on a set of left speakers in the plurality of stereo speakers; and after playing the first set of tones, playing a second set of non-verbal tones on a set of right speakers in the plurality of stereo speakers.
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3. The method of claim 1 , wherein the turn for navigation is a right turn, wherein playing the non-verbal prompt comprises: playing a first set of non-verbal tones on a set of left speakers in the plurality of stereo speakers; and after playing the first set of tones, playing a second set of non-verbal tones on a set of right speakers in the plurality of stereo speakers. 6. The method of claim 3 , wherein each of the first and second sets of tones comprises only one tone.
| 0.5 |
7,716,161 | 16 | 21 |
16. The computer implemented method of claim 12 , wherein analyzing the content further comprises: determining at least one similar web page to the target web page; revising the content of the target web page by supplementing it with the content of the similar web page; and analyzing the revised content of the target web page to identify a set of one or more topics.
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16. The computer implemented method of claim 12 , wherein analyzing the content further comprises: determining at least one similar web page to the target web page; revising the content of the target web page by supplementing it with the content of the similar web page; and analyzing the revised content of the target web page to identify a set of one or more topics. 21. The computer implemented method of claim 16 , wherein the web page is contained in a host, and wherein determining at least one similar web page comprises determining that a web page is similar if it is stored within a subdirectory of related pages on the same host as the target web page.
| 0.5 |
8,880,495 | 1 | 12 |
1. A method for constructing an expanded search query at a computing device, the method comprising: receiving audio information via a microphone of the computing device; recording the audio information in an overwriteable circular buffer of the computing device, including recording at least some of the audio information during a period when the computing device is powered-on, but is in an inactive state or a sleep state in which a graphical display of the computing device is off or substantially dimmed, said recording initiated responsive to a triggering condition including detection of a sound level via the microphone that exceeds a sound level threshold, the overwriteable circular buffer having a limited data storage capacity in which older audio information is overwritten with newer audio information upon reaching the limited data storage capacity; initiating construction of a search query by receiving a user input via a text-based user interface of the computing device, the user input including one or more keywords forming a user-defined portion of the search query; processing at least a portion of the audio information recorded in the overwriteable circular buffer to obtain one or more additional keywords forming an expanded portion of the search query, the portion of the audio information containing the one or more additional keywords received and recorded in the overwriteable circular buffer prior to receiving the user input including the one or more keywords; supplying the search query including the user-defined portion and the expanded portion to a search engine; and receiving a response to the search query from the search engine, the response generated by the search engine based, at least in part, on the one or more keywords of the user-defined portion and the one or more additional keywords of the expanded portion of the search query.
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1. A method for constructing an expanded search query at a computing device, the method comprising: receiving audio information via a microphone of the computing device; recording the audio information in an overwriteable circular buffer of the computing device, including recording at least some of the audio information during a period when the computing device is powered-on, but is in an inactive state or a sleep state in which a graphical display of the computing device is off or substantially dimmed, said recording initiated responsive to a triggering condition including detection of a sound level via the microphone that exceeds a sound level threshold, the overwriteable circular buffer having a limited data storage capacity in which older audio information is overwritten with newer audio information upon reaching the limited data storage capacity; initiating construction of a search query by receiving a user input via a text-based user interface of the computing device, the user input including one or more keywords forming a user-defined portion of the search query; processing at least a portion of the audio information recorded in the overwriteable circular buffer to obtain one or more additional keywords forming an expanded portion of the search query, the portion of the audio information containing the one or more additional keywords received and recorded in the overwriteable circular buffer prior to receiving the user input including the one or more keywords; supplying the search query including the user-defined portion and the expanded portion to a search engine; and receiving a response to the search query from the search engine, the response generated by the search engine based, at least in part, on the one or more keywords of the user-defined portion and the one or more additional keywords of the expanded portion of the search query. 12. The method of claim 1 , wherein recording the audio information in the overwriteable circular buffer includes continuously recording the audio information in the overwriteable circular buffer by overwriting the oldest audio information with newest audio information upon reaching the limited data storage capacity.
| 0.751174 |
7,784,045 | 19 | 22 |
19. A computer-implemented method for delivering, by a computer, at least one computer based test comprising: validating data for at least one computer based test with a plugin; amalgamating the data for at least one computer based test such that the data associated with the at least one computer based test exists virtually as one virtual storage location even though the data resides at different memory locations, wherein common data for at least one computer based test appears once even if used more than one time in delivering the at least one computer based test; instantiating the plugin utilized by a test driver executed by the computer that delivers the at least one computer based test, wherein amalgamated data provides information to the plugin to provide executed by the test driver to deliver the at least one computer based test, and wherein the amalgamating further comprises amalgamating the data content to exist virtually by at least one of embedding the data content as an object and linking the data content with a pointer.
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19. A computer-implemented method for delivering, by a computer, at least one computer based test comprising: validating data for at least one computer based test with a plugin; amalgamating the data for at least one computer based test such that the data associated with the at least one computer based test exists virtually as one virtual storage location even though the data resides at different memory locations, wherein common data for at least one computer based test appears once even if used more than one time in delivering the at least one computer based test; instantiating the plugin utilized by a test driver executed by the computer that delivers the at least one computer based test, wherein amalgamated data provides information to the plugin to provide executed by the test driver to deliver the at least one computer based test, and wherein the amalgamating further comprises amalgamating the data content to exist virtually by at least one of embedding the data content as an object and linking the data content with a pointer. 22. The method of claim 19 , wherein amalgamating stores the data in an object-linking and embedding (OLE) structured storage format.
| 0.779801 |
8,521,587 | 2 | 5 |
2. A method for placing advertisements on a user interface comprising the steps of: providing a user interface having a plurality of user interface screens, at least some of said plurality of user interface screens containing user-selectable objects; and determining, by using a processor, which of a plurality of advertisements to display on a user interface screen based on at least one of the following criteria: topical relevance, contextual relevance, path relevance and cognitive prominence, wherein said at least one criteria includes contextual relevance and said contextual relevance is a measure of a relationship between a theme of the respective user interface screen and a theme associated with each advertisement, and further wherein said contextual relevance is calculated as: HD ( q , c ) = ∑ x ∈ { P q - P c } α r x + ∑ y ∈ { P c - P q } β r y + ∑ z ∈ { q , c } γ r z where: α, β, and γ are weighting factors, r n is a hierarchical level of a given topic, and P n is a set of parent topics of an item.
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2. A method for placing advertisements on a user interface comprising the steps of: providing a user interface having a plurality of user interface screens, at least some of said plurality of user interface screens containing user-selectable objects; and determining, by using a processor, which of a plurality of advertisements to display on a user interface screen based on at least one of the following criteria: topical relevance, contextual relevance, path relevance and cognitive prominence, wherein said at least one criteria includes contextual relevance and said contextual relevance is a measure of a relationship between a theme of the respective user interface screen and a theme associated with each advertisement, and further wherein said contextual relevance is calculated as: HD ( q , c ) = ∑ x ∈ { P q - P c } α r x + ∑ y ∈ { P c - P q } β r y + ∑ z ∈ { q , c } γ r z where: α, β, and γ are weighting factors, r n is a hierarchical level of a given topic, and P n is a set of parent topics of an item. 5. The method of claim 2 , wherein said at least one criteria includes path relevance and wherein said path relevance uses information associated with a user's navigation path through the user interface to determine relevant ones of said plurality of advertisements.
| 0.818306 |
10,148,961 | 13 | 24 |
13. An apparatus for entropy coding of video data, the apparatus comprising: a memory configured to store a plurality of contexts used in a context-adaptive entropy binary arithmetic (CABAC) process; and one or more processors configured to: determine a window size of a plurality of window sizes for a first context of the plurality of contexts; CABAC code, based on a probability state of the first context, a bin of a value for a first syntax element of the video data; update the probability state of the first context based on the window size for the first context the coded bin of the value for the first syntax element; determine a window size of the plurality of window sizes for a second context of the plurality of contexts, wherein the window size for the second context is different than the window size for the first context, and wherein the window size for the second context is not used to update the probability state of the first context; CABAC code, based on a probability state of the second context, a bin of a value for a second syntax element of the video data; and update the probability state of the second context based on the window size for the second context and the coded bin for the second syntax element.
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13. An apparatus for entropy coding of video data, the apparatus comprising: a memory configured to store a plurality of contexts used in a context-adaptive entropy binary arithmetic (CABAC) process; and one or more processors configured to: determine a window size of a plurality of window sizes for a first context of the plurality of contexts; CABAC code, based on a probability state of the first context, a bin of a value for a first syntax element of the video data; update the probability state of the first context based on the window size for the first context the coded bin of the value for the first syntax element; determine a window size of the plurality of window sizes for a second context of the plurality of contexts, wherein the window size for the second context is different than the window size for the first context, and wherein the window size for the second context is not used to update the probability state of the first context; CABAC code, based on a probability state of the second context, a bin of a value for a second syntax element of the video data; and update the probability state of the second context based on the window size for the second context and the coded bin for the second syntax element. 24. The apparatus of claim 13 , wherein the apparatus comprises at least one of: an integrated circuit; a microprocessor; or a wireless communication device.
| 0.703774 |
7,587,318 | 32 | 35 |
32. The system of claim 28 , wherein the system for speech recognition is part of a mobile phone.
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32. The system of claim 28 , wherein the system for speech recognition is part of a mobile phone. 35. The system of claim 32 , wherein the recognizable information comprises one or more numeric characters.
| 0.597744 |
9,271,329 | 51 | 55 |
51. A wireless station, comprising: a wireless interface to at least one wireless access point in wireless range of the wireless station; and a processor, communicating with the at least one access point via the wireless interface, the processor being configured to— locate character set information identifying a non-Unicode character set for the access point in a wireless beacon broadcast by the access point, the wireless beacon comprising a service set identification information element comprising a service set identification for the access point encoded in the character set, decode the service set identification information element packed in the wireless beacon in accordance with the non-Unicode character set and broadcast by the access point using the non-Unicode character set, and present the service set identification in Unicode format to a user of the wireless station to select a network connection.
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51. A wireless station, comprising: a wireless interface to at least one wireless access point in wireless range of the wireless station; and a processor, communicating with the at least one access point via the wireless interface, the processor being configured to— locate character set information identifying a non-Unicode character set for the access point in a wireless beacon broadcast by the access point, the wireless beacon comprising a service set identification information element comprising a service set identification for the access point encoded in the character set, decode the service set identification information element packed in the wireless beacon in accordance with the non-Unicode character set and broadcast by the access point using the non-Unicode character set, and present the service set identification in Unicode format to a user of the wireless station to select a network connection. 55. The wireless station of claim 51 , wherein locating the character set information comprises extracting the character set information from a vendor-specific information element.
| 0.579439 |
8,694,888 | 4 | 7 |
4. A non-transitory computer readable medium storing a computer program for presenting computer-generated characters, the computer program executable by at least one processor, the computer program comprising sets of instructions for: receiving a plurality of frames as input; assigning the plurality of frames to represent a character in a font, wherein each frame depicts a particular representation of said character; defining the font by storing the plurality of frames in at least one file associated with said font; and associating the character with a keystroke on a keyboard, so that when the font is selected and the keystroke is received, the plurality of frames is sequentially displayed on a display screen to provide an animated presentation of the character.
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4. A non-transitory computer readable medium storing a computer program for presenting computer-generated characters, the computer program executable by at least one processor, the computer program comprising sets of instructions for: receiving a plurality of frames as input; assigning the plurality of frames to represent a character in a font, wherein each frame depicts a particular representation of said character; defining the font by storing the plurality of frames in at least one file associated with said font; and associating the character with a keystroke on a keyboard, so that when the font is selected and the keystroke is received, the plurality of frames is sequentially displayed on a display screen to provide an animated presentation of the character. 7. The non-transitory computer readable medium of claim 4 , wherein storing the plurality of frames comprises storing the plurality of frames in a plurality of files, wherein at least one file comprises image data for one frame of the character and all parameter data that specifically define the character, wherein at least one file comprises image data for the remaining frames of the character.
| 0.751253 |
7,499,024 | 16 | 17 |
16. The apparatus of claim 13 , further comprising means for visually snapping the text object to the visible symbol when the visible symbol is positioned near the selected text of the source location and when the button of the control device is in the second position.
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16. The apparatus of claim 13 , further comprising means for visually snapping the text object to the visible symbol when the visible symbol is positioned near the selected text of the source location and when the button of the control device is in the second position. 17. The apparatus of claim 16 , wherein the visible symbol is displayed in a first shape when the visible symbol is positioned within a proximity of the selected text of the source location, indicating that the text object can be created and snapped to the visible symbol.
| 0.5 |
8,321,202 | 1 | 6 |
1. A method, comprising: receiving, by a computing device, a set of information descriptive of a user; receiving, by the computing device, narrative information associated with the user; and validating, by the computing device, at least one item in the set of information based on an analysis of the narrative information.
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1. A method, comprising: receiving, by a computing device, a set of information descriptive of a user; receiving, by the computing device, narrative information associated with the user; and validating, by the computing device, at least one item in the set of information based on an analysis of the narrative information. 6. The method of claim 1 , wherein the set of information includes an indicated education level of the user, and wherein the validating includes analyzing the narrative information to determine whether the indicated education level of the user is accurate.
| 0.5 |
7,739,115 | 1 | 23 |
1. A method for evaluating compliance of at least one agent reading at least one script to at least one client, the method comprising at least the following: conducting at least one voice interaction between the at least one agent and the at least one client, wherein the at least one agent follows the at least one script via at least one of a plurality of panels; entering information by the at least one agent according to responses obtained from the at least one client during the voice interaction; assigning a time displacement timestamp to each of the plurality of panels as they are presented and viewed by the at least one agent during the voice interaction; logging a time displacement, based on the time displacement timestamp, per panel as a portion of a log record; logging the voice interaction as a portion of the log record; based on the logging, evaluating the at least one voice interaction via the at least one of the plurality of panels employing panel-by-panel playback with the assigned time displacement timestamp with at least one automatic speech recognition component adapted to analyze the at least one voice interaction; and determining, via generating a score using confidence level thresholds of the least one automatic speech recognition component such that the confidence level thresholds are assigned to each of the plurality of panels and evaluating the score against a static or a varying standard, whether the at least one agent has adequately followed the at least one script by using the evaluated at least one voice interaction.
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1. A method for evaluating compliance of at least one agent reading at least one script to at least one client, the method comprising at least the following: conducting at least one voice interaction between the at least one agent and the at least one client, wherein the at least one agent follows the at least one script via at least one of a plurality of panels; entering information by the at least one agent according to responses obtained from the at least one client during the voice interaction; assigning a time displacement timestamp to each of the plurality of panels as they are presented and viewed by the at least one agent during the voice interaction; logging a time displacement, based on the time displacement timestamp, per panel as a portion of a log record; logging the voice interaction as a portion of the log record; based on the logging, evaluating the at least one voice interaction via the at least one of the plurality of panels employing panel-by-panel playback with the assigned time displacement timestamp with at least one automatic speech recognition component adapted to analyze the at least one voice interaction; and determining, via generating a score using confidence level thresholds of the least one automatic speech recognition component such that the confidence level thresholds are assigned to each of the plurality of panels and evaluating the score against a static or a varying standard, whether the at least one agent has adequately followed the at least one script by using the evaluated at least one voice interaction. 23. The method of claim 1 , further comprising identifying at least one instance of non-compliance with the script, wherein the agent did not adequately follow the script during at least one given interaction.
| 0.877778 |
9,342,496 | 1 | 11 |
1. A method for automatically completing a remainder portion of a name as it is being entered, comprising: receiving, at processing circuitry configured to execute instructions stored on a memory, at least a prescribed number of starting characters of a name being entered into a first cell, wherein: the first cell is disposed in a document; the document includes a first table having a first table name and a second table having a second table name; the first table includes a first row or column having a first row or column name and the second table includes a second row or column having a second row or column name; the first row or column name and the second row or column name are the same; and the starting characters of the name being entered into the first cell include a string of characters found in the first row or column name and the second row or column name; using the processing circuitry to determine a set of valid reference names that include the starting characters of the name being entered into the first cell, wherein: a first valid reference name of the set of valid reference names comprises the first row or column name; a second valid reference name of the set of valid reference names comprises the second row or column name; and the first valid reference name comprises the first table name or the second valid reference name comprises the second table name; and providing with the processing circuitry the set of valid reference names as selectable auto-completion options to enable selection between the first valid reference name and the second valid reference name.
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1. A method for automatically completing a remainder portion of a name as it is being entered, comprising: receiving, at processing circuitry configured to execute instructions stored on a memory, at least a prescribed number of starting characters of a name being entered into a first cell, wherein: the first cell is disposed in a document; the document includes a first table having a first table name and a second table having a second table name; the first table includes a first row or column having a first row or column name and the second table includes a second row or column having a second row or column name; the first row or column name and the second row or column name are the same; and the starting characters of the name being entered into the first cell include a string of characters found in the first row or column name and the second row or column name; using the processing circuitry to determine a set of valid reference names that include the starting characters of the name being entered into the first cell, wherein: a first valid reference name of the set of valid reference names comprises the first row or column name; a second valid reference name of the set of valid reference names comprises the second row or column name; and the first valid reference name comprises the first table name or the second valid reference name comprises the second table name; and providing with the processing circuitry the set of valid reference names as selectable auto-completion options to enable selection between the first valid reference name and the second valid reference name. 11. A method as recited in claim 1 , wherein the first valid reference name comprises the first table name prepended to the first row or column name; or wherein the second valid reference name comprises the second table name prepended to the second row or column name.
| 0.5 |
8,447,760 | 27 | 28 |
27. A non-transitory computer storage medium having instructions stored thereon that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: determining a respective strength of relationship score between each candidate document in a group of candidate documents and each of the first documents by aggregating user selection data for multiple users, the first documents and the candidate documents being in a corpus of web documents, the user selection data indicating, for each of the multiple users, whether the user viewed the candidate document during a window of time after the first document is presented to the user on a search results web page in response to a query, wherein the strength of relationship score is a probability that the candidate document will be viewed given that the first document has been presented to a user on a search results web page in response to a query; calculating an aggregate strength of relationship score for each candidate document from the respective strength of relationship scores for the candidate document; and selecting the one or more second documents from the candidate documents according to the aggregate strength of relationship scores for the candidate documents.
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27. A non-transitory computer storage medium having instructions stored thereon that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: determining a respective strength of relationship score between each candidate document in a group of candidate documents and each of the first documents by aggregating user selection data for multiple users, the first documents and the candidate documents being in a corpus of web documents, the user selection data indicating, for each of the multiple users, whether the user viewed the candidate document during a window of time after the first document is presented to the user on a search results web page in response to a query, wherein the strength of relationship score is a probability that the candidate document will be viewed given that the first document has been presented to a user on a search results web page in response to a query; calculating an aggregate strength of relationship score for each candidate document from the respective strength of relationship scores for the candidate document; and selecting the one or more second documents from the candidate documents according to the aggregate strength of relationship scores for the candidate documents. 28. The non-transitory computer storage medium of claim 27 , wherein the user selection data further indicates whether each of the multiple users viewed the candidate document for a threshold period of time.
| 0.817138 |
8,983,955 | 1 | 30 |
1. A computer readable medium for managing electronic information, comprising: a plurality of predefined portions of text-based data with at least one of said plurality of predefined portions of text-based data being stored; at least one modified predefined portion of text-based data, said at least one modified predefined portion of text-based data being created based at least in part on modifications to at least one of said plurality of predefined portions of text-based data; and said at least one modified predefined portion of text-based data being stored; a plurality of links comprising at least one of code or a markup language, at least one of said plurality of predefined portions of said text-based data and said at least one modified predefined portion of text-based data being associated with at least one of said plurality of links; and a plurality of attributes for organizing at least one of said plurality of predefined portions of text-based data and said at least one modified predefined portion of text-based data, at least one of said plurality of attributes defining a point in a multidimensional space.
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1. A computer readable medium for managing electronic information, comprising: a plurality of predefined portions of text-based data with at least one of said plurality of predefined portions of text-based data being stored; at least one modified predefined portion of text-based data, said at least one modified predefined portion of text-based data being created based at least in part on modifications to at least one of said plurality of predefined portions of text-based data; and said at least one modified predefined portion of text-based data being stored; a plurality of links comprising at least one of code or a markup language, at least one of said plurality of predefined portions of said text-based data and said at least one modified predefined portion of text-based data being associated with at least one of said plurality of links; and a plurality of attributes for organizing at least one of said plurality of predefined portions of text-based data and said at least one modified predefined portion of text-based data, at least one of said plurality of attributes defining a point in a multidimensional space. 30. The recording medium according to claim 1 , wherein the multidimensional space comprises non-terminal nodes in a hierarchy and wherein said non-terminal nodes do not possess content.
| 0.835398 |
8,943,063 | 10 | 12 |
10. An apparatus comprising: a) at least one processor; and b) at least one storage device storing processor executable instructions which, when executed by the at least one processor, cause the at least one processor to perform a method for generating a tunable finite automaton (“TFA”) from a nondeterministic finite automaton (“NFA”) having a finite set of states, a finite set of input symbols and a transition function covering each state and input symbol, the TFA having, at most, a number b of concurrent active states, the computer-implemented method including 1) receiving a deterministic finite automaton (“DFA”) representation of the NFA, 2) regrouping the NFA active state combination associated with each state of the DFA into up to b subsets, with the objective of minimizing the number of total distinct subsets, 3) generating one TFA state for each of the distinct subsets, 4) for each of the DFA states, storing pointers to the up to b TFA states in a table entry associated with the NFA active state combination of the DFA state, 5) associating each of the TFA states with appropriate transition representations using the transition functions of the NFA states corresponding to the TFA state, 6) storing each of the TFA states, and 7) storing for each of the TFA states, each of the appropriate transition representations in association with the TFA state and a corresponding input symbol, wherein the number b is a specified parameter and is at least 2.
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10. An apparatus comprising: a) at least one processor; and b) at least one storage device storing processor executable instructions which, when executed by the at least one processor, cause the at least one processor to perform a method for generating a tunable finite automaton (“TFA”) from a nondeterministic finite automaton (“NFA”) having a finite set of states, a finite set of input symbols and a transition function covering each state and input symbol, the TFA having, at most, a number b of concurrent active states, the computer-implemented method including 1) receiving a deterministic finite automaton (“DFA”) representation of the NFA, 2) regrouping the NFA active state combination associated with each state of the DFA into up to b subsets, with the objective of minimizing the number of total distinct subsets, 3) generating one TFA state for each of the distinct subsets, 4) for each of the DFA states, storing pointers to the up to b TFA states in a table entry associated with the NFA active state combination of the DFA state, 5) associating each of the TFA states with appropriate transition representations using the transition functions of the NFA states corresponding to the TFA state, 6) storing each of the TFA states, and 7) storing for each of the TFA states, each of the appropriate transition representations in association with the TFA state and a corresponding input symbol, wherein the number b is a specified parameter and is at least 2. 12. The apparatus of claim 10 wherein the method further includes receiving, as input, with the computer system, a set of regular expressions, generating, with the computer system, an NFA from the received set of regular expressions, and generating, with the computer system, the received DFA representation of the NFA using a subset construction scheme, such that states of the generated DFA provide all valid active state combinations of the NFA.
| 0.907705 |
9,100,722 | 1 | 10 |
1. A method of selecting content items for presentation to a user, comprising: obtaining a list of candidate content items; obtaining metadata tags associated with the candidate content items; selecting at least one of the candidate content items for presentation to a user, based on previously stored user exposure scores for one or more metadata tags associated with the candidate content item, wherein the metadata tags refer to non-skipped portions of content items associated with the metadata tags and not to a skipped portion of the content items, the user exposure scores based on a number of occurrences of viewings of the non-skipped portions of the content items associated with the metadata tags, wherein the non-skipped portions of the content items are defined by demarcation points with respect to one or more skipped portions of the content items, each demarcation point being designated automatically in response to skipping within the content items based on user input during presentation of the content items, the designated demarcation points between the skipped portions and the non-skipped portions specifying a start point and an end point for the skipped portion.
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1. A method of selecting content items for presentation to a user, comprising: obtaining a list of candidate content items; obtaining metadata tags associated with the candidate content items; selecting at least one of the candidate content items for presentation to a user, based on previously stored user exposure scores for one or more metadata tags associated with the candidate content item, wherein the metadata tags refer to non-skipped portions of content items associated with the metadata tags and not to a skipped portion of the content items, the user exposure scores based on a number of occurrences of viewings of the non-skipped portions of the content items associated with the metadata tags, wherein the non-skipped portions of the content items are defined by demarcation points with respect to one or more skipped portions of the content items, each demarcation point being designated automatically in response to skipping within the content items based on user input during presentation of the content items, the designated demarcation points between the skipped portions and the non-skipped portions specifying a start point and an end point for the skipped portion. 10. The method of claim 1 wherein the list of candidate content items and metadata tags associated with the candidate content items are stored at a remote source and wherein the selecting is performed remotely from a client device which presents the selected at least one candidate content items.
| 0.59116 |
8,073,694 | 1 | 4 |
1. A method for preparing a text-to-speech (TTS) voice via a computing device, the method comprising: synthesizing words utilizing a preprocessed TTS voice; presenting to a person a subset of word variants that contains at least N instances of a group of units in the TTS voice; receiving information from the person associated with a correction needed to the TTS voice; and making the correction with the computing device to the TTS voice according to the received information, wherein each phonetic unit in the TTS voice is exercised.
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1. A method for preparing a text-to-speech (TTS) voice via a computing device, the method comprising: synthesizing words utilizing a preprocessed TTS voice; presenting to a person a subset of word variants that contains at least N instances of a group of units in the TTS voice; receiving information from the person associated with a correction needed to the TTS voice; and making the correction with the computing device to the TTS voice according to the received information, wherein each phonetic unit in the TTS voice is exercised. 4. The method of claim 1 , wherein N equals more than 1.
| 0.787879 |
7,487,095 | 75 | 76 |
75. The method of claim 74 in which a first mode of expression of the communications from the user is different from a second mode of expression of the responses to the user.
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75. The method of claim 74 in which a first mode of expression of the communications from the user is different from a second mode of expression of the responses to the user. 76. The method of claim 75 in which the first mode and second mode of expression comprise at least one of text or speech.
| 0.5 |
8,086,548 | 4 | 5 |
4. The method of claim 3 , further comprising generating fingerprints for the second set of passages, wherein the fingerprints for the second set of passages correspond to an observation sequence of the HMM.
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4. The method of claim 3 , further comprising generating fingerprints for the second set of passages, wherein the fingerprints for the second set of passages correspond to an observation sequence of the HMM. 5. The method of claim 4 , further comprising calculating passage similarities by comparing the fingerprints of the second set of passages with the fingerprints of the first set of passages.
| 0.5 |
8,219,817 | 19 | 23 |
19. A system for verifying matching content between a plurality of text documents, comprising: a storage device for storing in electronic form an authentication signature generated from electronic text characters from an electronic form of a first text document; a processor communicatively coupled to the storage device and being operative to access the authentication signature generated from the electronic text characters from the electronic form of the first text document and being further operative to: electronically obtain an image document; store the image document in the storage device; transform the image document to a second electronic text document; generate an authentication signature from the second electronic text document; and compare authentication signatures respectively generated from the first and second electronic text documents for a match.
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19. A system for verifying matching content between a plurality of text documents, comprising: a storage device for storing in electronic form an authentication signature generated from electronic text characters from an electronic form of a first text document; a processor communicatively coupled to the storage device and being operative to access the authentication signature generated from the electronic text characters from the electronic form of the first text document and being further operative to: electronically obtain an image document; store the image document in the storage device; transform the image document to a second electronic text document; generate an authentication signature from the second electronic text document; and compare authentication signatures respectively generated from the first and second electronic text documents for a match. 23. The system according to claim 19 , further comprising a storage device for storing one or more of the authentication signatures.
| 0.682692 |
9,043,296 | 12 | 13 |
12. A method of operating a mobile computing device to provide a suggestion to a user, the method comprising: sensing context data related to a user environment using at least one sensor; from an implicit user query, generating a hypothesis of information of interest to the user based on at least one list of information and the context data, the context data indicating activity that the user may perform in the future; based on the generated hypothesis, identifying at least one item consistent with the hypothesis; presenting a suggestion, on a display of a user interface of the mobile computing device, of the at least one identified item consistent with the hypothesis; and receiving a user input that results in a modification of the presented suggestion, on the display of the user interface of the mobile computing device, of the at least one identified item, wherein the generating a hypothesis includes generating at least one vector based on the at least one list of information and at least one vector based on the context data and assessing a degree in which the at least one vector based on the at least one list of information matches with the at least one vector based on the context data.
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12. A method of operating a mobile computing device to provide a suggestion to a user, the method comprising: sensing context data related to a user environment using at least one sensor; from an implicit user query, generating a hypothesis of information of interest to the user based on at least one list of information and the context data, the context data indicating activity that the user may perform in the future; based on the generated hypothesis, identifying at least one item consistent with the hypothesis; presenting a suggestion, on a display of a user interface of the mobile computing device, of the at least one identified item consistent with the hypothesis; and receiving a user input that results in a modification of the presented suggestion, on the display of the user interface of the mobile computing device, of the at least one identified item, wherein the generating a hypothesis includes generating at least one vector based on the at least one list of information and at least one vector based on the context data and assessing a degree in which the at least one vector based on the at least one list of information matches with the at least one vector based on the context data. 13. The mobile computing device of claim 12 , wherein generating a hypothesis of information of interest to the user comprises generating a social graph of one or more users and preferences of the one or more users.
| 0.5 |
8,732,096 | 10 | 11 |
10. A computer system for making optimal medical decisions, comprising: (a) a data input means for collecting, storing, and outputting medical evidence, (b) first computing processor means for operating a model of evidence configured to receive said medical evidence from said data input means, to retrieve the model of evidence from the data storage, to infer probable current medical states given said medical evidence, and to store and forward the output, (c) second computing processor means for operating a model of the progression of the disease configured to retrieve said model of the progression of the disease from the data storage, to infer, given possible medical decisions, probable future medical states from the probable current medical states, and to store and forward the output, (d) third computing processor means for operating a plurality of models of costs and benefits configured to retrieve said models of costs and benefits from the data storage, to infer, given possible medical decision, probable costs and benefits for each of said probable future medical states, and to store and forward the output, (e) fourth computing processor means for operating personal preference functions configured to accept a formula and a set of parameters from approximately reflecting the circumstances and preferences of the user of the system, to calculate an approximate value for the user of each combination of costs and benefits, and to store and forward the output, (f) fifth computer processor means for evaluation and optimization of costs and benefits of said medical decisions configured to compute preference values of said personal preference functions for the probable costs and benefits, to rank said preference values, to display the medical decision corresponding to the highest preference value as said optimal medical decision, to process the optimal decision, and to store and forward the optimal decision.
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10. A computer system for making optimal medical decisions, comprising: (a) a data input means for collecting, storing, and outputting medical evidence, (b) first computing processor means for operating a model of evidence configured to receive said medical evidence from said data input means, to retrieve the model of evidence from the data storage, to infer probable current medical states given said medical evidence, and to store and forward the output, (c) second computing processor means for operating a model of the progression of the disease configured to retrieve said model of the progression of the disease from the data storage, to infer, given possible medical decisions, probable future medical states from the probable current medical states, and to store and forward the output, (d) third computing processor means for operating a plurality of models of costs and benefits configured to retrieve said models of costs and benefits from the data storage, to infer, given possible medical decision, probable costs and benefits for each of said probable future medical states, and to store and forward the output, (e) fourth computing processor means for operating personal preference functions configured to accept a formula and a set of parameters from approximately reflecting the circumstances and preferences of the user of the system, to calculate an approximate value for the user of each combination of costs and benefits, and to store and forward the output, (f) fifth computer processor means for evaluation and optimization of costs and benefits of said medical decisions configured to compute preference values of said personal preference functions for the probable costs and benefits, to rank said preference values, to display the medical decision corresponding to the highest preference value as said optimal medical decision, to process the optimal decision, and to store and forward the optimal decision. 11. The computer system for making optimal medical decisions of claim 10 , wherein said data input means for collecting, storing, and outputting a medical evidence comprises automated data collection means for supplying the medical evidence in realtime.
| 0.5 |
9,535,963 | 11 | 18 |
11. An apparatus, comprising: one or more processors; memory; and a program module, wherein the program module is stored in the memory and, during operation of the apparatus, is executed by the one or more processors to request desired information from a graph database storing a graph, the program module including: instructions for receiving an initial query that is compatible with a first type of database that is different from the graph database; instructions for converting the initial query into a query using primitives, wherein the primitives comprise: a rule, based on edges in the graph, that expresses a relational schema in the first type of database, and information associated with a compound key that specifies a relationship between nodes, edges and predicates in the graph corresponding to a table in the first type of database; instructions for executing the query against the graph database, wherein: the graph comprises nodes, edges between the nodes, and predicates to represent and store data with index-free adjacency; and the query identifies a first edge associated with a predicate that specifies one or more of the nodes in the graph; and instructions for receiving a result in response to the query, wherein the result includes a subset of the graph.
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11. An apparatus, comprising: one or more processors; memory; and a program module, wherein the program module is stored in the memory and, during operation of the apparatus, is executed by the one or more processors to request desired information from a graph database storing a graph, the program module including: instructions for receiving an initial query that is compatible with a first type of database that is different from the graph database; instructions for converting the initial query into a query using primitives, wherein the primitives comprise: a rule, based on edges in the graph, that expresses a relational schema in the first type of database, and information associated with a compound key that specifies a relationship between nodes, edges and predicates in the graph corresponding to a table in the first type of database; instructions for executing the query against the graph database, wherein: the graph comprises nodes, edges between the nodes, and predicates to represent and store data with index-free adjacency; and the query identifies a first edge associated with a predicate that specifies one or more of the nodes in the graph; and instructions for receiving a result in response to the query, wherein the result includes a subset of the graph. 18. The apparatus of claim 11 , wherein the query includes a variable.
| 0.868914 |
4,145,742 | 6 | 12 |
6. An electronic calculator comprising: keyboard input means having a plurality of alphabetic and numeric keys for entering alphameric information, including functions, into the calculator; memory means, coupled to said keyboard input means, for storing alphameric information entered into the calculator; processing means, coupled to said keyboard input means and memory means, for processing alphameric information entered into the calculator to perform selected functions; and output means, coupled to said processing means, for providing a visual indication of the results of selected functions performed by said processing means; said keyboard input means including an execute control key, a store control key, a definable key, and means, including a parameter key, for defining a function to be associated with said definable key and for designating one or more parameters to be specified for the defined function, said store control key being operative for initiating storage of the defined function, with the designated parameters to be specified, in said memory means; said processing means being responsive to actuaton of said execute control key, following actuation of said definable key and one or more other keys specifying the designated parameters, for executing the defined function with those specified parameters, said processing means being further responsive to actuation of said store control key, following actuation of said definable key and one or more other keys specifying the designated parameters, for storing the defined function with those specified parameters in said memory means.
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6. An electronic calculator comprising: keyboard input means having a plurality of alphabetic and numeric keys for entering alphameric information, including functions, into the calculator; memory means, coupled to said keyboard input means, for storing alphameric information entered into the calculator; processing means, coupled to said keyboard input means and memory means, for processing alphameric information entered into the calculator to perform selected functions; and output means, coupled to said processing means, for providing a visual indication of the results of selected functions performed by said processing means; said keyboard input means including an execute control key, a store control key, a definable key, and means, including a parameter key, for defining a function to be associated with said definable key and for designating one or more parameters to be specified for the defined function, said store control key being operative for initiating storage of the defined function, with the designated parameters to be specified, in said memory means; said processing means being responsive to actuaton of said execute control key, following actuation of said definable key and one or more other keys specifying the designated parameters, for executing the defined function with those specified parameters, said processing means being further responsive to actuation of said store control key, following actuation of said definable key and one or more other keys specifying the designated parameters, for storing the defined function with those specified parameters in said memory means. 12. An electronic calculator as in claim 6 wherein each specified parameter comprises a variable.
| 0.775463 |
9,043,209 | 1 | 2 |
1. A language model creation device comprising: a language model creating unit configured to execute a language model creation process of: acquiring a first content-specific language model which represents an appearance probability that a specific word appears in a first content, the first content comprising a first word sequence, a second content-specific language model which represents an appearance probability that the specific word appears in a second content, the second content comprising a second word sequence, a first probability parameter representing a probability that a content represented by a target word sequence is the first content, and a second probability parameter representing a probability that the content represented by the target word sequence is the second content, the target word sequence being at least a part of a speech recognition hypothesis generated in a speech recognition process; and creating a language model based on the first probability parameter, the second probability parameter, the first content-specific language model and the second content-specific language model, the created language model representing a combined appearance probability which is a probability that the specific word appears within at least a portion of the target word sequence.
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1. A language model creation device comprising: a language model creating unit configured to execute a language model creation process of: acquiring a first content-specific language model which represents an appearance probability that a specific word appears in a first content, the first content comprising a first word sequence, a second content-specific language model which represents an appearance probability that the specific word appears in a second content, the second content comprising a second word sequence, a first probability parameter representing a probability that a content represented by a target word sequence is the first content, and a second probability parameter representing a probability that the content represented by the target word sequence is the second content, the target word sequence being at least a part of a speech recognition hypothesis generated in a speech recognition process; and creating a language model based on the first probability parameter, the second probability parameter, the first content-specific language model and the second content-specific language model, the created language model representing a combined appearance probability which is a probability that the specific word appears within at least a portion of the target word sequence. 2. The language model creation device according to claim 1 , wherein: the language model creating unit is configured to create the language model such that the combined appearance probability increases as a sum of (i) a product of a first coefficient and the probability represented by the first content-specific language model, and (ii) a product of a second coefficient and the probability represented by the second content-specific language model, becomes larger, wherein the first coefficient increases in value as the first probability parameter becomes larger, and the second coefficient increases in value as the second probability parameter becomes larger.
| 0.511046 |
8,209,320 | 21 | 25 |
21. A system comprising: a processor; a memory coupled to the processor to store information related to keywords; and a keyword extraction component to place an object in a web page, the web page displayed to a user on a client device with a processor having access to a network, the web page is an affiliate web page, the object is an executable code component configured to execute a network communication when the web page is accessed, to invoke a keyword extraction service at a host site via a network access in response to activation of the object in the web page when the web page is accessed by the user, to obtain information related to user activity on the client device, the information obtained in response to activation of the object in the web page when the web page is accessed by the user, the information related to user activity on the client device including impressions viewed by the user and user click-throughs received, wherein the information related to user activity on the client device is based on information selected from the group: user behavior on a web site, frequency of user queries, listings availability, post-search user activity, and catalog data, to use the keyword extraction service to extract relevant keywords from content of the web page, the information related to user activity on the client device used to determine relevancy of the extracted keywords, the keyword extraction component to identify items relevant to the extracted keywords, the relevancy of the extracted keywords to the items is based on information from the group consisting of: measures of item popularity, measures of web site popularity, aggregate user behavior on the web site; user feedback, listings availability, and catalog data, and to rank the relevant items.
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21. A system comprising: a processor; a memory coupled to the processor to store information related to keywords; and a keyword extraction component to place an object in a web page, the web page displayed to a user on a client device with a processor having access to a network, the web page is an affiliate web page, the object is an executable code component configured to execute a network communication when the web page is accessed, to invoke a keyword extraction service at a host site via a network access in response to activation of the object in the web page when the web page is accessed by the user, to obtain information related to user activity on the client device, the information obtained in response to activation of the object in the web page when the web page is accessed by the user, the information related to user activity on the client device including impressions viewed by the user and user click-throughs received, wherein the information related to user activity on the client device is based on information selected from the group: user behavior on a web site, frequency of user queries, listings availability, post-search user activity, and catalog data, to use the keyword extraction service to extract relevant keywords from content of the web page, the information related to user activity on the client device used to determine relevancy of the extracted keywords, the keyword extraction component to identify items relevant to the extracted keywords, the relevancy of the extracted keywords to the items is based on information from the group consisting of: measures of item popularity, measures of web site popularity, aggregate user behavior on the web site; user feedback, listings availability, and catalog data, and to rank the relevant items. 25. The system as claimed in claim 21 to perform a search using the extracted keywords.
| 0.733129 |
9,940,931 | 1 | 3 |
1. A computer-implemented method comprising: under control of a computing device configured with specific computer-executable instructions, generating audio data comprising speech; transmitting the audio data to a remote computing system including a speech recognition engine; receiving, from the remote computing system, a plurality of transcription results for a portion of a transcription of the speech, wherein the transcription has been generated from the audio data by the speech recognition engine; receiving, from the remote computing system, a confidence level for each transcription result of the plurality of transcription results, wherein the confidence level for each transcription result has been generated by the speech recognition engine, and wherein the confidence level for each transcription result of the plurality of transcription results represents a confidence in an accuracy of the transcription result; determining a ranked order for the plurality of transcription results from the confidence levels of the plurality of transcription results; presenting the plurality of transcription results for the portion of the transcription in the ranked order, with each transcription result of the plurality of transcription results presented with the confidence level for the transcription result; and receiving a selection, from the plurality of transcription results, of a first transcription result for the portion of the transcription.
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1. A computer-implemented method comprising: under control of a computing device configured with specific computer-executable instructions, generating audio data comprising speech; transmitting the audio data to a remote computing system including a speech recognition engine; receiving, from the remote computing system, a plurality of transcription results for a portion of a transcription of the speech, wherein the transcription has been generated from the audio data by the speech recognition engine; receiving, from the remote computing system, a confidence level for each transcription result of the plurality of transcription results, wherein the confidence level for each transcription result has been generated by the speech recognition engine, and wherein the confidence level for each transcription result of the plurality of transcription results represents a confidence in an accuracy of the transcription result; determining a ranked order for the plurality of transcription results from the confidence levels of the plurality of transcription results; presenting the plurality of transcription results for the portion of the transcription in the ranked order, with each transcription result of the plurality of transcription results presented with the confidence level for the transcription result; and receiving a selection, from the plurality of transcription results, of a first transcription result for the portion of the transcription. 3. The computer-implemented method of claim 1 , wherein at least two transcription results of the plurality of transcription results satisfy a threshold confidence level, and further comprising: determining which transcription results of the plurality of transcription results for the portion have a confidence level satisfying a threshold confidence level, and wherein presenting the plurality of transcription results for the portion of the transcription comprises presenting the at least two transcription results, in the ranked order, that have a confidence level satisfying the threshold confidence level, with each transcription result of the at least two transcription results presented with the confidence level for the transcription result.
| 0.5 |
4,412,305 | 1 | 10 |
1. An electronic language translator for use in translating any of a certain plurality of groups of words from a first language into a second language, the translator comprising: an input means for entering and storing a selected word from a chosen group of words corresponding to one of the certain plurality of groups of words in the first language; a first memory means for storing data representing each of the plurality of groups of words in the first language; an address means responsive to the input means for addressing the first memory means to cause sequential retrieval of each of the plurality of groups of words stored in the first memory means; a detection means connected to the first memory means and responsive to the addressing of the first memory means by the address means for detecting equivalency between the selected word stored in the input means and any word of any one of the plurality of groups of words retrieved from the first memory means; a second memory means for storing data representing a second and like plurality of groups of words in the second language, each of the second groups of words being the translation of one of the groups in the first language and being correspondingly addressed within the second memory means as is its counterpart in the first memory means, the second memory means being simultaneously addressed along with the first memory means by the address means such that upon a detection of equivalency by the detection means, the corresponding, translated group of words in the second language is retrieved; and a display means responsive to the detection means for displaying the corresponding, translated group of words in the second language that has been retrieved from the second memory means whereby translation of a group of words from the first language to the second language can be accomplished by inputting only a single word selected from the group of words in the first language.
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1. An electronic language translator for use in translating any of a certain plurality of groups of words from a first language into a second language, the translator comprising: an input means for entering and storing a selected word from a chosen group of words corresponding to one of the certain plurality of groups of words in the first language; a first memory means for storing data representing each of the plurality of groups of words in the first language; an address means responsive to the input means for addressing the first memory means to cause sequential retrieval of each of the plurality of groups of words stored in the first memory means; a detection means connected to the first memory means and responsive to the addressing of the first memory means by the address means for detecting equivalency between the selected word stored in the input means and any word of any one of the plurality of groups of words retrieved from the first memory means; a second memory means for storing data representing a second and like plurality of groups of words in the second language, each of the second groups of words being the translation of one of the groups in the first language and being correspondingly addressed within the second memory means as is its counterpart in the first memory means, the second memory means being simultaneously addressed along with the first memory means by the address means such that upon a detection of equivalency by the detection means, the corresponding, translated group of words in the second language is retrieved; and a display means responsive to the detection means for displaying the corresponding, translated group of words in the second language that has been retrieved from the second memory means whereby translation of a group of words from the first language to the second language can be accomplished by inputting only a single word selected from the group of words in the first language. 10. An electronic language translator according to claim 1, wherein the address means includes an address counter the output of which is connected to both the first and the second memory means.
| 0.724286 |
9,552,399 | 38 | 39 |
38. A configured system comprising: one or more hardware processors of one or more computing systems; and one or more modules that are configured to, when executed by at least one of the one or more hardware processors, initiate display of summarized information about a distributed group discussion having a plurality of content items submitted by a plurality of users, by: obtaining information about one or more predictions regarding future content items that will be submitted for the distributed group discussion; determining multiple visual aspects to use to display information to one or more users about multiple topics indicated in the plurality of content items; generating information for display to the one or more users that is based at least in part on the one or more predictions, the generated information including, for each of the multiple topics, at least one summarization that is based on content items of the distributed group discussion corresponding to the topic and that is represented using at least one of the multiple visual aspects; and providing the generated information for display to the one or more users.
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38. A configured system comprising: one or more hardware processors of one or more computing systems; and one or more modules that are configured to, when executed by at least one of the one or more hardware processors, initiate display of summarized information about a distributed group discussion having a plurality of content items submitted by a plurality of users, by: obtaining information about one or more predictions regarding future content items that will be submitted for the distributed group discussion; determining multiple visual aspects to use to display information to one or more users about multiple topics indicated in the plurality of content items; generating information for display to the one or more users that is based at least in part on the one or more predictions, the generated information including, for each of the multiple topics, at least one summarization that is based on content items of the distributed group discussion corresponding to the topic and that is represented using at least one of the multiple visual aspects; and providing the generated information for display to the one or more users. 39. The system of claim 38 wherein the multiple topics are part of multiple comment groups within an information category, and wherein the generated information illustrates comparative information for the multiple comment groups within the information category.
| 0.789855 |
8,620,836 | 1 | 4 |
1. A method comprising: receiving, by a device, a document; determining, by the device, a plurality of topics associated with the document; each of the plurality of topics being associated with text, determining, by the device, one or more desired topics of the plurality of topics; filtering, by the device, a first portion of text from the document without filtering a second portion of text from the document, the second portion of text being associated with the one or more desired topics, the first portion of text not being associated with the one or more desired topics, the first portion of text being removed from the document, and the second portion of text being different than the first portion of text; splitting, by the device, the second portion of text into a plurality of segments; clustering, by the device, each of the plurality of segments into one or more clusters of a plurality of clusters, each cluster, of the plurality of clusters, including at least one of the plurality of segments, and each cluster, of the plurality of clusters, being associated with the one or more desired topics; identifying, by the device, at least one segment, of the plurality of segments, having low relevance to a cluster, of the plurality of clusters, that includes the at least one segment; and removing, by the device, the at least one segment from the cluster.
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1. A method comprising: receiving, by a device, a document; determining, by the device, a plurality of topics associated with the document; each of the plurality of topics being associated with text, determining, by the device, one or more desired topics of the plurality of topics; filtering, by the device, a first portion of text from the document without filtering a second portion of text from the document, the second portion of text being associated with the one or more desired topics, the first portion of text not being associated with the one or more desired topics, the first portion of text being removed from the document, and the second portion of text being different than the first portion of text; splitting, by the device, the second portion of text into a plurality of segments; clustering, by the device, each of the plurality of segments into one or more clusters of a plurality of clusters, each cluster, of the plurality of clusters, including at least one of the plurality of segments, and each cluster, of the plurality of clusters, being associated with the one or more desired topics; identifying, by the device, at least one segment, of the plurality of segments, having low relevance to a cluster, of the plurality of clusters, that includes the at least one segment; and removing, by the device, the at least one segment from the cluster. 4. The method of claim 1 , where, when splitting the second portion of text into the plurality of segments, the method includes: applying sentence identification criteria to the text to identify sentences in the text; and associating each identified sentence with a segment of the plurality of segments.
| 0.5 |
7,627,582 | 5 | 6 |
5. The system of claim 1 , wherein the pictorial graphical image is a video.
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5. The system of claim 1 , wherein the pictorial graphical image is a video. 6. The system of claim 5 , wherein the video is played upon a user selecting a thumbnail of the video.
| 0.527778 |
8,756,207 | 17 | 19 |
17. A computer-implemented system comprising: a processor configured to perform operations including: accessing records, wherein: the records include first records and second records; each of the records includes a respective essential field and a respective nonessential field, and wherein: in each of the first records and in each of the second records, the respective essential field includes an essential substring; in each of the first records, the respective nonessential field includes a nonessential substring; and in each of the second records, the respective nonessential field is empty; for each of the records, deriving: a first matchcode that includes a first fuzzy representation of the respective essential substring; and a second matchcode that includes a second fuzzy representation of the respective essential substring, wherein the second representation is different than the first representation, and wherein: each of the second matchcodes derived for a first record field matchcode segment that represents the respective nonessential substring; and each of the second matchcodes derived for a second record includes a wildcard character segment that is deemed to be equivalent to each of the nonessential field matchcode segments; forming first matchcode equivalence clusters by selectively grouping the records such that first matchcodes for records grouped together are equivalent, wherein forming the first matchcode equivalence clusters is done independently of record type; within at least one of the first matchcode equivalence clusters, further grouping at least one of the records with at least one of the other records, wherein grouping within each of the at least one first matchcode equivalence clusters: is done such that second matchcodes for records grouped together are equivalent; and is done independently of similarities between records in different first matchcode equivalence clusters; and identifying matches amongst the records based on the grouping within the at least one first matchcode equivalence cluster.
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17. A computer-implemented system comprising: a processor configured to perform operations including: accessing records, wherein: the records include first records and second records; each of the records includes a respective essential field and a respective nonessential field, and wherein: in each of the first records and in each of the second records, the respective essential field includes an essential substring; in each of the first records, the respective nonessential field includes a nonessential substring; and in each of the second records, the respective nonessential field is empty; for each of the records, deriving: a first matchcode that includes a first fuzzy representation of the respective essential substring; and a second matchcode that includes a second fuzzy representation of the respective essential substring, wherein the second representation is different than the first representation, and wherein: each of the second matchcodes derived for a first record field matchcode segment that represents the respective nonessential substring; and each of the second matchcodes derived for a second record includes a wildcard character segment that is deemed to be equivalent to each of the nonessential field matchcode segments; forming first matchcode equivalence clusters by selectively grouping the records such that first matchcodes for records grouped together are equivalent, wherein forming the first matchcode equivalence clusters is done independently of record type; within at least one of the first matchcode equivalence clusters, further grouping at least one of the records with at least one of the other records, wherein grouping within each of the at least one first matchcode equivalence clusters: is done such that second matchcodes for records grouped together are equivalent; and is done independently of similarities between records in different first matchcode equivalence clusters; and identifying matches amongst the records based on the grouping within the at least one first matchcode equivalence cluster. 19. The system of claim 17 , wherein each of the first matchcodes and each of the second matchcodes is generated based on matchcode generation rules.
| 0.909035 |
8,996,582 | 9 | 11 |
9. A non-transitory computer readable storage medium configured to store instructions that when executed cause a processor to perform creating an attribute category tree data structure having more than one level of tree data, the processor being further configured to perform: receiving a plurality of objects having a plurality of corresponding predefined attribute values; assigning the plurality of predefined attribute values to at least one category value; constructing a first category of the attribute category tree data structure based on a of data associated with the at least one category value; assigning the first category to a first level of tree data, wherein the first category is an image category corresponding to a particular product, and wherein the first category is represented by at least one assigned image file; assigning at least one predefined attribute value of the plurality of attribute values to a second level of tree data, wherein the at least on attribute value comprises a plurality of numerical values corresponding to a plurality of different numerical sizes of the particular product which are available for purchase; assigning, via the processor, at least one additional predefined attribute value of the plurality of attribute values to a third level of tree data that is separate from the first level of tree data and the second level of tree data, and wherein the third level of tree data is linked to the first level of tree data and to the second level of tree data; displaying a plurality of image options available for selection each comprising the at least one predefined attribute value; receiving a selection of at least one of the image options associated with the at least one predefined attribute value; and selecting a branch of the tree under the selected at least one image option and expanding the tree to display available options for the at least one additional predefined attribute value that is available based on the selected predefined attribute value, wherein the available options comprise the plurality of different numerical sizes of the particular product which are available for purchase.
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9. A non-transitory computer readable storage medium configured to store instructions that when executed cause a processor to perform creating an attribute category tree data structure having more than one level of tree data, the processor being further configured to perform: receiving a plurality of objects having a plurality of corresponding predefined attribute values; assigning the plurality of predefined attribute values to at least one category value; constructing a first category of the attribute category tree data structure based on a of data associated with the at least one category value; assigning the first category to a first level of tree data, wherein the first category is an image category corresponding to a particular product, and wherein the first category is represented by at least one assigned image file; assigning at least one predefined attribute value of the plurality of attribute values to a second level of tree data, wherein the at least on attribute value comprises a plurality of numerical values corresponding to a plurality of different numerical sizes of the particular product which are available for purchase; assigning, via the processor, at least one additional predefined attribute value of the plurality of attribute values to a third level of tree data that is separate from the first level of tree data and the second level of tree data, and wherein the third level of tree data is linked to the first level of tree data and to the second level of tree data; displaying a plurality of image options available for selection each comprising the at least one predefined attribute value; receiving a selection of at least one of the image options associated with the at least one predefined attribute value; and selecting a branch of the tree under the selected at least one image option and expanding the tree to display available options for the at least one additional predefined attribute value that is available based on the selected predefined attribute value, wherein the available options comprise the plurality of different numerical sizes of the particular product which are available for purchase. 11. The non-transitory computer readable storage medium of claim 9 , wherein the first tree level of tree data is reserved for non-numerical category image data, and the lower tree levels are reserved for category numerical data and category textual data.
| 0.5 |
9,922,647 | 1 | 4 |
1. A method for reducing response time in a speech interface comprising: constructing a partially completed word sequence from a partially received utterance from a speaker received by an audio sensor; modeling a remainder portion for the partially received utterance using a processor based on a rich predictive model to predict the remainder portion; and responding to the partially completed word sequence and the predicted remainder portion for the partially received utterance using a natural language vocalization generator with a vocalization, wherein the vocalization is prepared before a complete utterance is received from the speaker and conveyed to the speaker by an audio transducer.
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1. A method for reducing response time in a speech interface comprising: constructing a partially completed word sequence from a partially received utterance from a speaker received by an audio sensor; modeling a remainder portion for the partially received utterance using a processor based on a rich predictive model to predict the remainder portion; and responding to the partially completed word sequence and the predicted remainder portion for the partially received utterance using a natural language vocalization generator with a vocalization, wherein the vocalization is prepared before a complete utterance is received from the speaker and conveyed to the speaker by an audio transducer. 4. The method according to claim 1 , wherein the rich predictive model is an n-gram model, a recurrent neural network model, a long short term memory, feed forward neural network, or a combination thereof.
| 0.556277 |
9,684,741 | 2 | 4 |
2. The method of claim 1 : the device comprising at least one input component associated with an input domain, and the instructions configured to receive the query through at least one input component.
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2. The method of claim 1 : the device comprising at least one input component associated with an input domain, and the instructions configured to receive the query through at least one input component. 4. The method of claim 2 , the instructions configured to, after receiving the query and before executing the query on the at least one search engine, normalize the query.
| 0.82622 |
8,843,949 | 4 | 6 |
4. The information processing apparatus according to claim 1 , wherein the processor is configured to determine, as the recommendation content, a piece of content having a high experience importance degree among the pieces of content sorted.
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4. The information processing apparatus according to claim 1 , wherein the processor is configured to determine, as the recommendation content, a piece of content having a high experience importance degree among the pieces of content sorted. 6. The information processing apparatus according to claim 4 , wherein the processor is further configured to: sort the pieces of content in the descending order of the corresponding experience importance degrees; and determine, as the recommendation content, pieces of content corresponding to highest n experience importance degrees among the pieces of content sorted.
| 0.559524 |
8,533,274 | 8 | 9 |
8. The method of claim 7 , wherein the criteria include an event triggering condition upon which the user-selected conversation is brought back to the first list of conversations.
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8. The method of claim 7 , wherein the criteria include an event triggering condition upon which the user-selected conversation is brought back to the first list of conversations. 9. The method of claim 8 , wherein the event triggering condition is satisfied when a number of unchecked messages in the conversation has reached a predetermined limit.
| 0.804398 |
7,773,806 | 10 | 14 |
10. A system for segmenting an object in a set of image data using one or more prior instances of the object, comprising: a processor; computer software operable on the processor, the computer software being capable of: determining a nonparametric estimate of a statistical shape distribution from the one or more prior instances of the object in a subspace spanned by the one or more prior instances of the object by a kernel density estimator; determining a nonparametric estimate of a statistical intensity distribution from the one or more prior instances of the object by a kernel density estimator; combining the kernel density estimator of the statistical shape distribution with the kernel density estimator of the statistical intensity distribution in a Bayesian expression conditioned on the set of image data, wherein the expression is provided in accordance with: E ( α , h , θ ) = - ∫ Ω ( H ϕ log p in ( I ) + ( 1 - H ϕ ) log p out ( I ) ) ⅆ x - log ( 1 N σ ∑ i = 1 N K ( α - α i σ ) ) ; and selecting a segmentation of the object in the set of image data by executing a level set method which optimizes the Bayesian expression.
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10. A system for segmenting an object in a set of image data using one or more prior instances of the object, comprising: a processor; computer software operable on the processor, the computer software being capable of: determining a nonparametric estimate of a statistical shape distribution from the one or more prior instances of the object in a subspace spanned by the one or more prior instances of the object by a kernel density estimator; determining a nonparametric estimate of a statistical intensity distribution from the one or more prior instances of the object by a kernel density estimator; combining the kernel density estimator of the statistical shape distribution with the kernel density estimator of the statistical intensity distribution in a Bayesian expression conditioned on the set of image data, wherein the expression is provided in accordance with: E ( α , h , θ ) = - ∫ Ω ( H ϕ log p in ( I ) + ( 1 - H ϕ ) log p out ( I ) ) ⅆ x - log ( 1 N σ ∑ i = 1 N K ( α - α i σ ) ) ; and selecting a segmentation of the object in the set of image data by executing a level set method which optimizes the Bayesian expression. 14. The system of claim 10 , wherein the statistical shape distribution is translation and rotation invariant.
| 0.747706 |
8,209,664 | 14 | 16 |
14. One or more processor readable storage devices having processor readable code stored thereon, the processor readable code programs one or more processors to perform a method comprising: receiving one or more expressions from an application executing at a first machine, the one or more expressions include an aggregate function that invokes a user-defined function referencing a first dataset; automatically generating an execution plan for executing the one or more expressions in parallel at nodes of a compute cluster, the automatically generating including: determining whether the one or more expressions include an extension specifying a particular data partitioning for the first dataset, if the one or more expressions include the extension specifying a particular data partitioning, generating a first execution graph with the first dataset partitioned according to the particular data partitioning, if the one or more expressions do not include the extension specifying a particular data partitioning, generating a second execution graph with the first dataset partitioned according to a different data partitioning, determining whether the user-defined function includes an annotation specifying the user-defined function as associative, if the user-defined function includes the annotation, generating code to apply the aggregate function on the individual partitions of the first dataset and code to combine the results of applying the aggregate function on the individual partitions, and if the user-defined function does not include the annotation, generating code to stream the individual partitions of the first dataset to a single node for application of the aggregate function; and providing the execution plan to an execution engine that controls parallel execution of the one or more expressions in the compute cluster.
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14. One or more processor readable storage devices having processor readable code stored thereon, the processor readable code programs one or more processors to perform a method comprising: receiving one or more expressions from an application executing at a first machine, the one or more expressions include an aggregate function that invokes a user-defined function referencing a first dataset; automatically generating an execution plan for executing the one or more expressions in parallel at nodes of a compute cluster, the automatically generating including: determining whether the one or more expressions include an extension specifying a particular data partitioning for the first dataset, if the one or more expressions include the extension specifying a particular data partitioning, generating a first execution graph with the first dataset partitioned according to the particular data partitioning, if the one or more expressions do not include the extension specifying a particular data partitioning, generating a second execution graph with the first dataset partitioned according to a different data partitioning, determining whether the user-defined function includes an annotation specifying the user-defined function as associative, if the user-defined function includes the annotation, generating code to apply the aggregate function on the individual partitions of the first dataset and code to combine the results of applying the aggregate function on the individual partitions, and if the user-defined function does not include the annotation, generating code to stream the individual partitions of the first dataset to a single node for application of the aggregate function; and providing the execution plan to an execution engine that controls parallel execution of the one or more expressions in the compute cluster. 16. One or more processor readable storage devices according to claim 14 , wherein the method further comprises: dividing the first dataset into a plurality of partitions according to the particular data partitioning or the different data partitioning; providing each partition of the plurality to one node in the compute cluster; and executing the one or more expressions in parallel at the nodes of the compute cluster.
| 0.549251 |
8,842,660 | 1 | 7 |
1. A method for communicating contextual information relating to a conversation between a caller and a callee on a voice communication channel, comprising: obtaining caller contextual information from the caller that is exchanged using the voice communication channel; wherein the voice communication channel is used to transmit contextual data packets and conversational data packets during the conversation; wherein the caller contextual information is based on a caller rule used in determining the caller contextual information to be transmitted between the caller and the callee; obtaining callee contextual information based on a callee rule used in determining callee contextual information to be transmitted between the callee and the caller; determining a first scope of the callee contextual information; determining a second scope of the caller contextual information; determining whether to change the first scope of the callee contextual information based on the second scope of the caller contextual information; updating the callee contextual information based on the determined the second scope of the caller contextual information; and transmitting the callee contextual information.
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1. A method for communicating contextual information relating to a conversation between a caller and a callee on a voice communication channel, comprising: obtaining caller contextual information from the caller that is exchanged using the voice communication channel; wherein the voice communication channel is used to transmit contextual data packets and conversational data packets during the conversation; wherein the caller contextual information is based on a caller rule used in determining the caller contextual information to be transmitted between the caller and the callee; obtaining callee contextual information based on a callee rule used in determining callee contextual information to be transmitted between the callee and the caller; determining a first scope of the callee contextual information; determining a second scope of the caller contextual information; determining whether to change the first scope of the callee contextual information based on the second scope of the caller contextual information; updating the callee contextual information based on the determined the second scope of the caller contextual information; and transmitting the callee contextual information. 7. The method of claim 1 , wherein the callee contextual information is transmitted over a Voice over Internet Protocol communication channel.
| 0.756014 |
7,797,724 | 22 | 24 |
22. A system for securely providing access to a content file, the system comprising: a server for processing a request for access to a content file; a client device that receives, from the server, the requested content file, the client device containing a volatile memory element; a file transport mechanism on the client device; a storage buffer, created by the transport mechanism in the volatile memory element, the storage buffer storing the received content file; a document container, created by the transport mechanism on the client device, that provides a context for invoking an application program associated with the content file, the application program providing a set of menu commands for interacting with the application program, the document container further providing a replacement set of menu commands comprising a subset of the set of menu commands provided by the application program.
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22. A system for securely providing access to a content file, the system comprising: a server for processing a request for access to a content file; a client device that receives, from the server, the requested content file, the client device containing a volatile memory element; a file transport mechanism on the client device; a storage buffer, created by the transport mechanism in the volatile memory element, the storage buffer storing the received content file; a document container, created by the transport mechanism on the client device, that provides a context for invoking an application program associated with the content file, the application program providing a set of menu commands for interacting with the application program, the document container further providing a replacement set of menu commands comprising a subset of the set of menu commands provided by the application program. 24. The system of claim 22 wherein the client device saves the content file, and transmits the content file to the server.
| 0.706731 |
9,984,054 | 1 | 9 |
1. A method for controlling collaborative review of a document between a plurality of document reviewers, the method comprising: receiving a request to review a document from each of a plurality of document reviewers; responsive to the request, retrieving the document, the document having a read-only access file permission; converting the document to read-write access file permission such that source content of the document is modifiable; providing the source content to the plurality of document reviewers, each of the document reviewers using a document editor that executes within a browser of each of the reviewer computing systems, the source content being converted for display within the document editor; receiving, from the plurality of document reviewers, tentative modifications of the source content of the document; applying, by the document editor, an XML schema definition (XSD) to the source content; comparing the tentative modifications to the XSD for consistency and formatting, rejecting the tentative modifications if non-conforming with the XSD; displaying a warning message if the tentative modifications are non-conforming; displaying the tentative modifications of the source content within the document; transmitting the tentative modifications to a plurality of client nodes; receiving crowdsourced feedback to the tentative modifications from the plurality of client nodes; and creating a modified document based on the tentative modifications and the crowdsourced feedback, the modified document being displayed via a web-based interface.
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1. A method for controlling collaborative review of a document between a plurality of document reviewers, the method comprising: receiving a request to review a document from each of a plurality of document reviewers; responsive to the request, retrieving the document, the document having a read-only access file permission; converting the document to read-write access file permission such that source content of the document is modifiable; providing the source content to the plurality of document reviewers, each of the document reviewers using a document editor that executes within a browser of each of the reviewer computing systems, the source content being converted for display within the document editor; receiving, from the plurality of document reviewers, tentative modifications of the source content of the document; applying, by the document editor, an XML schema definition (XSD) to the source content; comparing the tentative modifications to the XSD for consistency and formatting, rejecting the tentative modifications if non-conforming with the XSD; displaying a warning message if the tentative modifications are non-conforming; displaying the tentative modifications of the source content within the document; transmitting the tentative modifications to a plurality of client nodes; receiving crowdsourced feedback to the tentative modifications from the plurality of client nodes; and creating a modified document based on the tentative modifications and the crowdsourced feedback, the modified document being displayed via a web-based interface. 9. The method according to claim 1 , further comprising converting the modified document back to read-only access file permission and storing the modified document in a storage media.
| 0.751359 |
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