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8,632,344 | 15 | 17 |
15. The system of claim 13 , wherein assigning relative weights uses human rated benchmark essay responses.
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15. The system of claim 13 , wherein assigning relative weights uses human rated benchmark essay responses. 17. The system of claim 15 , wherein assigning relative weights comprises using n number of human scored benchmark essays scored by each of k human raters, wherein n and k are selected to satisfy the inequality: 0.08 ≥ 1.2 1 - [ 0.8 k 1 + ( k - 1 ) 0.8 ] 2 n .
| 0.5 |
8,156,135 | 12 | 13 |
12. The non-transitory computer-readable storage media of claim 11 , wherein the first search context comprises a first user context comprising: user behavior; user preferences; user environment.
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12. The non-transitory computer-readable storage media of claim 11 , wherein the first search context comprises a first user context comprising: user behavior; user preferences; user environment. 13. The non-transitory computer-readable storage media of claim 12 , wherein the presenting the first search result page further comprises: presenting a first set of advertisements in response to the first search query and the first user context.
| 0.5 |
9,799,333 | 1 | 6 |
1. An electronic system configured to perform speech processing comprising: a memory having stored therein a database of keyword models, wherein the database of keyword models includes an ensemble of filters describing an evolution of phonetic events associated with each keyword in the database; a processor configured to: i) receive a signal including speech; ii) decompose the signal including speech into a sparse set of phonetic impulses; iii) access the database of keyword models; iv) identify keywords within the signal including speech using the sparse set of phonetic impulses and the database of keywords; and v) generate an output indicating the keywords identified in iv).
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1. An electronic system configured to perform speech processing comprising: a memory having stored therein a database of keyword models, wherein the database of keyword models includes an ensemble of filters describing an evolution of phonetic events associated with each keyword in the database; a processor configured to: i) receive a signal including speech; ii) decompose the signal including speech into a sparse set of phonetic impulses; iii) access the database of keyword models; iv) identify keywords within the signal including speech using the sparse set of phonetic impulses and the database of keywords; and v) generate an output indicating the keywords identified in iv). 6. The system of claim 1 wherein the database of keyword models includes an ensemble of filters associated with each keyword in the database and the processor is configured to convolve the sparse set of phonetic impulses with the ensemble of filters and calculate a score vector based on the convolving of the sparse set of phonetic impulses with ensemble of filters.
| 0.5 |
7,805,446 | 6 | 7 |
6. The method of claim 1 , 2 , 3 , 4 , or 5 , further comprising searching for stored documents according to a search query having at least one term and identifying the documents found in the search; and displaying the documents so as to indicate similarity of the documents to each other.
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6. The method of claim 1 , 2 , 3 , 4 , or 5 , further comprising searching for stored documents according to a search query having at least one term and identifying the documents found in the search; and displaying the documents so as to indicate similarity of the documents to each other. 7. The method of claim 6 , wherein the documents are displayed as nodes of a tree structure having links and nodes in which similarity of documents is indicated by proximity of nodes to each other and by a length of links connecting the nodes to a common vertex.
| 0.5 |
8,918,344 | 1 | 4 |
1. A method for generating a habituation-compensated library, comprising: receiving samples comprising temporal windows of token instances to which a user was exposed, wherein the temporal windows of token instances comprise a window comprising instantiations of first and second tokens that have overlapping instantiation periods; receiving data on previous instantiations of the first and second tokens, to which the user was exposed; receiving target values corresponding to the temporal windows of token instances; the target values represent affective responses of the user to the token instances from the temporal windows of token instances; wherein the affective responses are values comprising representations of emotional responses; training a machine learning-based user response model using data comprising: the samples, the data on previous instantiations of the first and second tokens, and the corresponding target values; and generating, based on the machine learning-based user response model, the habituation-compensated library that comprises for each token of the first and second tokens: a first expected affective response of the user to an instance of the token after a first number of previous exposures to instantiations of the token, and a second expected affective response of the user to an instance of the token after a second number, that is greater than the first number, of previous exposures to instantiations of the token; wherein for the first token, the first expected affective response is stronger than the second expected affective response, while for the second token, the first expected affective response is weaker than the second expected affective response.
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1. A method for generating a habituation-compensated library, comprising: receiving samples comprising temporal windows of token instances to which a user was exposed, wherein the temporal windows of token instances comprise a window comprising instantiations of first and second tokens that have overlapping instantiation periods; receiving data on previous instantiations of the first and second tokens, to which the user was exposed; receiving target values corresponding to the temporal windows of token instances; the target values represent affective responses of the user to the token instances from the temporal windows of token instances; wherein the affective responses are values comprising representations of emotional responses; training a machine learning-based user response model using data comprising: the samples, the data on previous instantiations of the first and second tokens, and the corresponding target values; and generating, based on the machine learning-based user response model, the habituation-compensated library that comprises for each token of the first and second tokens: a first expected affective response of the user to an instance of the token after a first number of previous exposures to instantiations of the token, and a second expected affective response of the user to an instance of the token after a second number, that is greater than the first number, of previous exposures to instantiations of the token; wherein for the first token, the first expected affective response is stronger than the second expected affective response, while for the second token, the first expected affective response is weaker than the second expected affective response. 4. The method of claim 1 , wherein the habituation-compensated library is generated by analyzing at least two different machine learning-based user response models that were trained on data collected over periods during which the user was in different situations; and the habituation-compensated library comprises expected affective responses of the user to same tokens in different situations.
| 0.5 |
9,355,178 | 24 | 39 |
24. A system comprising: a) a Web server computer configured to present web page search results related to terms of a search query initiated by a user, wherein the web page search results include a results list comprising a list of web pages related to the terms of the search query, the order in which the web pages are presented in response to the search query being influenced by relevance feedback provided by multiple users prior to the search query, and wherein the relevance feedback is different from selection of a link to a web page in the results list; b) a search engine for querying a database and providing the web page search results in response to user queries; and c) a content manager for managing the supplemental information in response to user input, wherein the user input comprises the relevance feedback.
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24. A system comprising: a) a Web server computer configured to present web page search results related to terms of a search query initiated by a user, wherein the web page search results include a results list comprising a list of web pages related to the terms of the search query, the order in which the web pages are presented in response to the search query being influenced by relevance feedback provided by multiple users prior to the search query, and wherein the relevance feedback is different from selection of a link to a web page in the results list; b) a search engine for querying a database and providing the web page search results in response to user queries; and c) a content manager for managing the supplemental information in response to user input, wherein the user input comprises the relevance feedback. 39. The system of claim 24 , wherein the relevance feedback comprises information related to relevancies of elements in the results list or an indication of the user's assessment of the quality or interest of the web page corresponding to an entry in the results list.
| 0.588957 |
9,889,858 | 4 | 5 |
4. The method according to claim 1 , wherein the confidence estimate is assigned a numerical value representing a confidence of the associated environment representation.
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4. The method according to claim 1 , wherein the confidence estimate is assigned a numerical value representing a confidence of the associated environment representation. 5. The method according to claim 4 , wherein the confidence is expressed as a probability value.
| 0.5 |
7,613,688 | 1 | 3 |
1. A computer-implemented method comprising: initiating a plurality of business warehouse system queries; associating each type of query with a category; during runtime of each query, identifying one or more row types for each query, and defining a template for each row type within a query from the identified row types, the template defining a format and a pattern for the row type; applying the template to query data for each query according to the row type to generate a sub-report; combining at least two sub-reports to generate an aggregated report, the sub-reports being positioned relative to each other within the aggregated report based on the associated category; and displaying the aggregated report.
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1. A computer-implemented method comprising: initiating a plurality of business warehouse system queries; associating each type of query with a category; during runtime of each query, identifying one or more row types for each query, and defining a template for each row type within a query from the identified row types, the template defining a format and a pattern for the row type; applying the template to query data for each query according to the row type to generate a sub-report; combining at least two sub-reports to generate an aggregated report, the sub-reports being positioned relative to each other within the aggregated report based on the associated category; and displaying the aggregated report. 3. A method as in claim 1 , further comprising: generating a plurality of business warehouse system queries from a plurality of heterogeneous data providers.
| 0.866269 |
9,148,500 | 15 | 19 |
15. A memory storing instructions that when executed cause a processor to perform operations, the operations comprising: receiving an audio signal generated by a microphone from speech spoken by a user to control a feature in a vehicle; recognizing a command prefix in the audio signal, the command prefix representing a spoken word in the spoken speech that is recognized as preceding any voice command; identifying a next spoken word after the command prefix as the voice command; storing associations between different next spoken words and different vehicular commands; retrieving a vehicular command of the different vehicular commands that is associated with the next spoken word; and executing the vehicular command in response to the next spoken word after the command prefix.
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15. A memory storing instructions that when executed cause a processor to perform operations, the operations comprising: receiving an audio signal generated by a microphone from speech spoken by a user to control a feature in a vehicle; recognizing a command prefix in the audio signal, the command prefix representing a spoken word in the spoken speech that is recognized as preceding any voice command; identifying a next spoken word after the command prefix as the voice command; storing associations between different next spoken words and different vehicular commands; retrieving a vehicular command of the different vehicular commands that is associated with the next spoken word; and executing the vehicular command in response to the next spoken word after the command prefix. 19. The memory of claim 15 , wherein the operations further comprise retrieving a stored voice greeting associated with the next spoken word.
| 0.520408 |
9,218,392 | 1 | 3 |
1. A method for providing search results based on search queries, the method comprising: under the control of one or more computer systems configured with executable instructions: receiving a search query for a product or service; identifying a user interest based on the search query; comparing the user interest with currently trending interests; identifying interest items based on the currently trending interests that relate to the user interest; identifying the currently trending interests based on a plurality of executed search queries received within a predefined time period prior to the search query being received; identifying key words associated with the plurality of executed search queries; and categorizing the executed search queries that contain the key words as the search query into expert groupings, wherein each expert grouping has a different characteristic from each of the other expert groupings.
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1. A method for providing search results based on search queries, the method comprising: under the control of one or more computer systems configured with executable instructions: receiving a search query for a product or service; identifying a user interest based on the search query; comparing the user interest with currently trending interests; identifying interest items based on the currently trending interests that relate to the user interest; identifying the currently trending interests based on a plurality of executed search queries received within a predefined time period prior to the search query being received; identifying key words associated with the plurality of executed search queries; and categorizing the executed search queries that contain the key words as the search query into expert groupings, wherein each expert grouping has a different characteristic from each of the other expert groupings. 3. The method of claim 1 , wherein the interest items include interest categories, wherein the interest categories are based on the currently trending interests that relate to the user interest.
| 0.795359 |
8,200,745 | 35 | 38 |
35. A framework system for a handheld client device comprising: a client-side framework; a server/proxy client for controlling and modifying behavior of said client without having to update client code and for unifying communication with said client to a single protocol; and a programming language for creating a device-specific application by adapting abstract representations of presentation and system objects within said framework to interface with a native operating system of said handheld client device; wherein said server/proxy client, upon receipt of a request for specific up to date presentation components from a client system, checks if the client system's original presentation components and/or executable bytecodes have expired; wherein said server proxy client updates said client system with raw data, presentation, and logic components, the raw data component comprising data retrieved from a server by said server proxy client in response to a client request, using a universal data format; wherein said server proxy client separates raw data and presentation components of said response and places said raw data component into said universal data format, wherein said raw data and said presentation components are sent independently by said server proxy client to said client system; wherein said server proxy client receives presentation and logic component updates for said client system; and wherein said presentation component updates are for a specific client device type; wherein said logic component updates comprise updates to a common code base that is shared between different client device types and which enables said server proxy client to control a feature set of said client system independently of an implementation supplied by native client code and without modifying said native client code; and wherein said client system reuses at least a portion of said raw data for other display purposes.
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35. A framework system for a handheld client device comprising: a client-side framework; a server/proxy client for controlling and modifying behavior of said client without having to update client code and for unifying communication with said client to a single protocol; and a programming language for creating a device-specific application by adapting abstract representations of presentation and system objects within said framework to interface with a native operating system of said handheld client device; wherein said server/proxy client, upon receipt of a request for specific up to date presentation components from a client system, checks if the client system's original presentation components and/or executable bytecodes have expired; wherein said server proxy client updates said client system with raw data, presentation, and logic components, the raw data component comprising data retrieved from a server by said server proxy client in response to a client request, using a universal data format; wherein said server proxy client separates raw data and presentation components of said response and places said raw data component into said universal data format, wherein said raw data and said presentation components are sent independently by said server proxy client to said client system; wherein said server proxy client receives presentation and logic component updates for said client system; and wherein said presentation component updates are for a specific client device type; wherein said logic component updates comprise updates to a common code base that is shared between different client device types and which enables said server proxy client to control a feature set of said client system independently of an implementation supplied by native client code and without modifying said native client code; and wherein said client system reuses at least a portion of said raw data for other display purposes. 38. The system of claim 35 , wherein said client-side framework comprises: a presentation object layer; an object layer; an object runtime layer; an abstraction layer; and a bootstrap application layer.
| 0.625926 |
9,870,539 | 25 | 28 |
25. The kiosk system according to claim 22 , wherein the computer is further configured to: display on the display device a map comprising a plurality of markers, each marker indicating a location of one or more predetermined geographic communities including the target geographic community.
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25. The kiosk system according to claim 22 , wherein the computer is further configured to: display on the display device a map comprising a plurality of markers, each marker indicating a location of one or more predetermined geographic communities including the target geographic community. 28. The kiosk system according to claim 25 , wherein each of the predetermined geographic communities corresponds to a village or an urban neighborhood.
| 0.654545 |
8,489,388 | 21 | 24 |
21. A data processing system, the system comprising: an input for receiving text, the input coupled to a processor through a bus; a pattern engine executing on the processor; a statistical engine executing on the processor, wherein the pattern engine and the statistical engine together detect data of a plurality of predetermined types in the text, the statistical engine converting the text into a first sequence of tokens, each token comprising a lexeme and a token type relating to the function of the lexeme within the text and having a predetermined probability that the corresponding data is of at least one of the predetermined types, the pattern engine converting the text into a second sequence of tokens, each token corresponding to data that matchers a predetermined pattern indicative of the at least one of the predetermined types, the pattern engine further parsing a combination of the first and second sequence of tokens; and a comparison engine executing on the processor to compare the first and second sequence of tokens, wherein when corresponding tokens from the first and second sequence of tokens for a portion of the text are the same, parsing only one of the corresponding tokens, when the token are not name tokens and the corresponding tokens are different, parsing both corresponding tokens, and when the tokens are name tokens and the corresponding tokens are different, parsing the corresponding token only from the statistical engine; and an output for outputting the data corresponding to the combination of tokens as the data that matches the predetermined pattern, the output coupled to a processor through the bus.
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21. A data processing system, the system comprising: an input for receiving text, the input coupled to a processor through a bus; a pattern engine executing on the processor; a statistical engine executing on the processor, wherein the pattern engine and the statistical engine together detect data of a plurality of predetermined types in the text, the statistical engine converting the text into a first sequence of tokens, each token comprising a lexeme and a token type relating to the function of the lexeme within the text and having a predetermined probability that the corresponding data is of at least one of the predetermined types, the pattern engine converting the text into a second sequence of tokens, each token corresponding to data that matchers a predetermined pattern indicative of the at least one of the predetermined types, the pattern engine further parsing a combination of the first and second sequence of tokens; and a comparison engine executing on the processor to compare the first and second sequence of tokens, wherein when corresponding tokens from the first and second sequence of tokens for a portion of the text are the same, parsing only one of the corresponding tokens, when the token are not name tokens and the corresponding tokens are different, parsing both corresponding tokens, and when the tokens are name tokens and the corresponding tokens are different, parsing the corresponding token only from the statistical engine; and an output for outputting the data corresponding to the combination of tokens as the data that matches the predetermined pattern, the output coupled to a processor through the bus. 24. The system according to claim 21 , wherein: the statistical engine outputs tokens of a first token type and the pattern engine comprises a lexer, which outputs tokens of a second token type; wherein at least one of said predetermined types of data comprises at least a token of the first token type and a token of the second token type.
| 0.510086 |
9,785,953 | 12 | 21 |
12. A system for generation of demand groups comprising: one or more network nodes including scanners to generate point of sales data; at least one processor coupled to the one or more network nodes over a network and including: an econometric coefficient analyzer configured to receive a product listing, demand coefficients, and point of sales data, wherein the product listing includes products comprising existing products of a product line and at least one new product with insufficient information for demand modeling that is being considered for inclusion in the product line, wherein the point of sales data and demand coefficients are received for the existing products and the point of sales data is received over a network from the one or more network nodes, and to analyze the point of sales data and generate a transition matrix including one or more pairs of existing products and, for each pair of products, a sum of a quantity of occurrences of transitions within a series of purchases to identify substitutable products, wherein a transition is represented by a switch from a first product of that pair in a first purchase to a second product of that pair in a second immediately succeeding purchase; an attribute engine configured to receive product data for each of the products in the product listing, and further configured to assign attributes to each of the products of the product listing based upon the product data, wherein the product data includes product descriptors, and assigning the attributes to the products includes natural language processing of the product descriptors via the at least one processor, wherein the product descriptors are provided in a natural language and the natural language processing enables the at least one processor to generate machine readable attribute data and indicate meanings by annotating terms of the product descriptors with information indicating corresponding characteristics to assign the attributes; a clustering engine configured to cluster data of the existing products and the at least one new product of the product listing by: clustering data of the existing products based on the received point of sales data and demand coefficients, the transition matrix, and the assigned attributes including the machine readable attribute data and meanings; and clustering data of the at least one new product by: determining a distance between the clustered data of the existing products and the assigned attributes of the at least one new product including the machine readable attribute data and meanings from the natural language processing of the product descriptors; and clustering the data of the at least one new product with the clustered data of the existing products based on the determined distance; a decision tree generator configured to generate a decision tree modeling consumer decisions for the existing products utilizing the point of sales data; a rule interface configured to receive at least one demand rule specifying one or more criteria for the demand groups; a rule based engine configured to generate demand groups of the substitutable products by applying the received at least one demand rule to at least one of the decision tree and the clusters of data of the products of the product listing; and a price optimization system for product price setting that utilizes the generated demand groups.
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12. A system for generation of demand groups comprising: one or more network nodes including scanners to generate point of sales data; at least one processor coupled to the one or more network nodes over a network and including: an econometric coefficient analyzer configured to receive a product listing, demand coefficients, and point of sales data, wherein the product listing includes products comprising existing products of a product line and at least one new product with insufficient information for demand modeling that is being considered for inclusion in the product line, wherein the point of sales data and demand coefficients are received for the existing products and the point of sales data is received over a network from the one or more network nodes, and to analyze the point of sales data and generate a transition matrix including one or more pairs of existing products and, for each pair of products, a sum of a quantity of occurrences of transitions within a series of purchases to identify substitutable products, wherein a transition is represented by a switch from a first product of that pair in a first purchase to a second product of that pair in a second immediately succeeding purchase; an attribute engine configured to receive product data for each of the products in the product listing, and further configured to assign attributes to each of the products of the product listing based upon the product data, wherein the product data includes product descriptors, and assigning the attributes to the products includes natural language processing of the product descriptors via the at least one processor, wherein the product descriptors are provided in a natural language and the natural language processing enables the at least one processor to generate machine readable attribute data and indicate meanings by annotating terms of the product descriptors with information indicating corresponding characteristics to assign the attributes; a clustering engine configured to cluster data of the existing products and the at least one new product of the product listing by: clustering data of the existing products based on the received point of sales data and demand coefficients, the transition matrix, and the assigned attributes including the machine readable attribute data and meanings; and clustering data of the at least one new product by: determining a distance between the clustered data of the existing products and the assigned attributes of the at least one new product including the machine readable attribute data and meanings from the natural language processing of the product descriptors; and clustering the data of the at least one new product with the clustered data of the existing products based on the determined distance; a decision tree generator configured to generate a decision tree modeling consumer decisions for the existing products utilizing the point of sales data; a rule interface configured to receive at least one demand rule specifying one or more criteria for the demand groups; a rule based engine configured to generate demand groups of the substitutable products by applying the received at least one demand rule to at least one of the decision tree and the clusters of data of the products of the product listing; and a price optimization system for product price setting that utilizes the generated demand groups. 21. The system for generating the demand groups, as recited in claim 12 , wherein the rule based engine generates demand groups using decision trees by measuring distance of products to one another in the decision tree.
| 0.676991 |
8,856,871 | 1 | 4 |
1. A method for compiling a unique sample code for specific web content, comprising: defining at least one sample code template comprising multiple sample code segments to be used for building a sample code for specific web content, said sample code segments at least comprising: a sample owner identifying code segment, and a sample identifying code segment; specifying the content of the sample code segments to be used for building said sample code, wherein the sample owner identifying code segment is specified by an Internet address of an owner of the specific web content; stringing the specified sample code segments to form the sample code; defining a digital path to a digital location via which access can be gained to the specific web content and which is mutually distinctive from the sample code; creating a cross-reference between the sample code generated during the stringing of the specified sample code segments and the digital path defined during the defining of the digital path; and providing the sample code with a time stamp indicating a time dependency of the specific web content.
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1. A method for compiling a unique sample code for specific web content, comprising: defining at least one sample code template comprising multiple sample code segments to be used for building a sample code for specific web content, said sample code segments at least comprising: a sample owner identifying code segment, and a sample identifying code segment; specifying the content of the sample code segments to be used for building said sample code, wherein the sample owner identifying code segment is specified by an Internet address of an owner of the specific web content; stringing the specified sample code segments to form the sample code; defining a digital path to a digital location via which access can be gained to the specific web content and which is mutually distinctive from the sample code; creating a cross-reference between the sample code generated during the stringing of the specified sample code segments and the digital path defined during the defining of the digital path; and providing the sample code with a time stamp indicating a time dependency of the specific web content. 4. The method according to claim 1 , wherein the method comprises storing the sample code, the digital path, and the cross-reference between the sample code and the digital path in a database.
| 0.563636 |
7,567,922 | 17 | 22 |
17. A computer readable medium comprising data encoded therein for generating a normalized configuration model, wherein the data comprises code executable by a processor to: generate product configuration instances from one or more product configuration models that include non-normalized feature references; identify non-normalized feature references included in one or more of the product configuration instances; access a mapping file, wherein the mapping file includes a map of specific product feature references to normalized feature references; locate normalized feature references that correlate with non-normalized feature references included in the generated product configuration instances; replace non-normalized feature references with correlating normalized feature references in accordance with the mapping file; and generate a normalized configuration model corresponding to the generated product configuration instances using the normalized feature references replacements, wherein the normalized configuration model is configured for use with a configuration system which presents the normalized feature references to a user of the configuration system to allow the user to configure a product using the normalized feature references.
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17. A computer readable medium comprising data encoded therein for generating a normalized configuration model, wherein the data comprises code executable by a processor to: generate product configuration instances from one or more product configuration models that include non-normalized feature references; identify non-normalized feature references included in one or more of the product configuration instances; access a mapping file, wherein the mapping file includes a map of specific product feature references to normalized feature references; locate normalized feature references that correlate with non-normalized feature references included in the generated product configuration instances; replace non-normalized feature references with correlating normalized feature references in accordance with the mapping file; and generate a normalized configuration model corresponding to the generated product configuration instances using the normalized feature references replacements, wherein the normalized configuration model is configured for use with a configuration system which presents the normalized feature references to a user of the configuration system to allow the user to configure a product using the normalized feature references. 22. The computer readable medium of claim 17 wherein the data further comprises code encoded therein to cause the processor to: optimize the normalized configuration model for run-time data retrieval.
| 0.541284 |
9,104,670 | 15 | 19 |
15. A computer readable memory encoded with a set of program instructions that, when executed, causes a processor to execute a method, the method comprising: receiving a search request from an electronic device, the search request including one or more search criteria; searching a database in accordance with the one or more search criteria to obtain search results, the database including digital asset information pertaining to a plurality of digital media assets and the search results corresponding to different digital media assets; monitoring usage of the electronic device to determine usage data, wherein monitoring the usage includes determining a level of completion of a digital media asset consumed by the electronic device; determining, based on the level of completion of the digital media asset consumed by the electronic device, that a particular type of digital media asset is of more interest to a user of the electronic device compared to another type of digital media asset when the level of completion of the digital media asset consumed by the electronic device has exceeded a trigger point of the digital media asset, wherein the trigger point indicates a position in the digital media asset; ranking the search results based at least in part on the usage data and the particular type of digital media asset determined to be of more interest to the user compared to the other type of digital media asset, wherein ranking the search results includes increasing a ranking for digital media assets belonging to the determined particular type of digital media assets compared to digital media assets of the other type within the search results; and presenting the ranked search results via the electronic device.
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15. A computer readable memory encoded with a set of program instructions that, when executed, causes a processor to execute a method, the method comprising: receiving a search request from an electronic device, the search request including one or more search criteria; searching a database in accordance with the one or more search criteria to obtain search results, the database including digital asset information pertaining to a plurality of digital media assets and the search results corresponding to different digital media assets; monitoring usage of the electronic device to determine usage data, wherein monitoring the usage includes determining a level of completion of a digital media asset consumed by the electronic device; determining, based on the level of completion of the digital media asset consumed by the electronic device, that a particular type of digital media asset is of more interest to a user of the electronic device compared to another type of digital media asset when the level of completion of the digital media asset consumed by the electronic device has exceeded a trigger point of the digital media asset, wherein the trigger point indicates a position in the digital media asset; ranking the search results based at least in part on the usage data and the particular type of digital media asset determined to be of more interest to the user compared to the other type of digital media asset, wherein ranking the search results includes increasing a ranking for digital media assets belonging to the determined particular type of digital media assets compared to digital media assets of the other type within the search results; and presenting the ranked search results via the electronic device. 19. The computer readable storage medium of claim 15 , wherein presenting the search results comprises displaying information concerning a set of the digital media assets that match at least the one or more search criteria.
| 0.562745 |
10,152,299 | 1 | 4 |
1. A method for reducing response latency of intelligent automated assistants, the method comprising: at an electronic device: receiving, from a user, a speech input containing a user request; transmitting, to a server, a representation of the speech input; receiving, from the server, a domain signal defining a relevant domain of an actionable intent inferred from the user request; determining whether the relevant domain is associated with a predefined action of a set of predefined actions supported by the electronic device; in response to determining that the relevant domain is associated with a predefined action on the electronic device, performing the predefined action; after at least partially performing the predefined action, receiving, from the server, data content relevant to satisfying the user request, wherein the data content is generated according to an executed task flow corresponding to the actionable intent, and wherein performing the predefined action at least partially prepares the electronic device to process the received data content; and outputting a result based on the data content to at least partially satisfy the user request.
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1. A method for reducing response latency of intelligent automated assistants, the method comprising: at an electronic device: receiving, from a user, a speech input containing a user request; transmitting, to a server, a representation of the speech input; receiving, from the server, a domain signal defining a relevant domain of an actionable intent inferred from the user request; determining whether the relevant domain is associated with a predefined action of a set of predefined actions supported by the electronic device; in response to determining that the relevant domain is associated with a predefined action on the electronic device, performing the predefined action; after at least partially performing the predefined action, receiving, from the server, data content relevant to satisfying the user request, wherein the data content is generated according to an executed task flow corresponding to the actionable intent, and wherein performing the predefined action at least partially prepares the electronic device to process the received data content; and outputting a result based on the data content to at least partially satisfy the user request. 4. The method of claim 1 , further comprising: in response to determining that the relevant domain is not associated with any predefined action of the set of predefined actions supported by the electronic device, performing a task based on the data content.
| 0.763352 |
8,234,221 | 2 | 3 |
2. The graphical user interface of claim 1 , wherein the second display region further includes a marking for at least one occurrence of the searchable phrase for each said at least one job requirement.
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2. The graphical user interface of claim 1 , wherein the second display region further includes a marking for at least one occurrence of the searchable phrase for each said at least one job requirement. 3. The graphical user interface of claim 2 , wherein the marking includes highlighting, displaying in reverse video, or displaying in a different font type, font size, or font style.
| 0.5 |
7,548,912 | 14 | 15 |
14. The method of claim 13 , wherein the request packet further comprises a properties element for specifying the properties to be returned from a query.
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14. The method of claim 13 , wherein the request packet further comprises a properties element for specifying the properties to be returned from a query. 15. The method of claim 14 , wherein the request packet further comprises a sort by element for specifying how the search results returned from the query are sorted.
| 0.5 |
6,119,124 | 1 | 20 |
1. A computer-implemented method of determining the resemblance of a plurality of data objects, comprising the steps of: parsing each data object into a canonical sequence of tokens; grouping overlapping sequences of the tokens of each data object into shingles; assigning a unique identification element to each shingle; permuting the elements of the data objects to form image sets; selecting a predetermined number of minimum elements from each image to form a sketch; partitioning the selected elements of each sketch into a plurality of groups; and assigning another unique identification to each group to generate the features of each data object to determine a level of resemblance of the plurality of data objects.
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1. A computer-implemented method of determining the resemblance of a plurality of data objects, comprising the steps of: parsing each data object into a canonical sequence of tokens; grouping overlapping sequences of the tokens of each data object into shingles; assigning a unique identification element to each shingle; permuting the elements of the data objects to form image sets; selecting a predetermined number of minimum elements from each image to form a sketch; partitioning the selected elements of each sketch into a plurality of groups; and assigning another unique identification to each group to generate the features of each data object to determine a level of resemblance of the plurality of data objects. 20. The method of claim 1 wherein the data objects encode audio and video signals.
| 0.849817 |
9,351,109 | 15 | 19 |
15. A system for comprising: a mobile device configured to obtain location data indicative of a location of said mobile device, obtain additional data from one or more sensors of mobile device, said additional data comprising context information, the context information comprising at least one of information regarding whether the mobile device is moving, information regarding a surrounding environment of the mobile device, and information related to an activity that a user of the mobile device is engaged in— a computing device configured to: receive said additional data from the mobile device; and, process said additional data to obtain said context information and to determine enhanced location information for said mobile device, based at least in part on processing said location data in association with said context information, wherein the enhanced location information represents an improved location accuracy relative to the location information, and wherein processing said location data in association with said context information comprises further distinguishing the location data using the context information.
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15. A system for comprising: a mobile device configured to obtain location data indicative of a location of said mobile device, obtain additional data from one or more sensors of mobile device, said additional data comprising context information, the context information comprising at least one of information regarding whether the mobile device is moving, information regarding a surrounding environment of the mobile device, and information related to an activity that a user of the mobile device is engaged in— a computing device configured to: receive said additional data from the mobile device; and, process said additional data to obtain said context information and to determine enhanced location information for said mobile device, based at least in part on processing said location data in association with said context information, wherein the enhanced location information represents an improved location accuracy relative to the location information, and wherein processing said location data in association with said context information comprises further distinguishing the location data using the context information. 19. The system of claim 15 wherein the mobile device comprises a plurality of sensors, and wherein one or more of the plurality of sensors is an audio sensor configured to obtain audio data.
| 0.502618 |
9,940,744 | 11 | 13 |
11. A method comprising: receiving, at a computing device, a request to display text in a first font from a first font file, the first font file accessible remotely by the computing device via a network; accessing, by the computing device and via the network, the first font file to obtain data related to the first font; selecting, by the computing device as a font fallback, a second font having at least portions of a corresponding second font file that is stored locally at the computing device and that is usable as a substitution for the data related to the first font; rendering at least a portion of the text in the selected second font using the portions of the corresponding second font file during a temporary period of time when the data related to the first font is being obtained by the computing device via the network; and based at least in part on the data related to the first font being obtained locally at the computing device, rendering the portion of the text using the obtained data related to the first font.
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11. A method comprising: receiving, at a computing device, a request to display text in a first font from a first font file, the first font file accessible remotely by the computing device via a network; accessing, by the computing device and via the network, the first font file to obtain data related to the first font; selecting, by the computing device as a font fallback, a second font having at least portions of a corresponding second font file that is stored locally at the computing device and that is usable as a substitution for the data related to the first font; rendering at least a portion of the text in the selected second font using the portions of the corresponding second font file during a temporary period of time when the data related to the first font is being obtained by the computing device via the network; and based at least in part on the data related to the first font being obtained locally at the computing device, rendering the portion of the text using the obtained data related to the first font. 13. A method as described in claim 11 , wherein the data comprises characters of the first font from the first font file.
| 0.820475 |
7,493,603 | 29 | 33 |
29. The computer readable medium of claim 24 , further comprising instructions for: tokenizing the markup language document to generate a token; a generic XML parser performing a first validation of the token, the generic XML parser being associated with the runtime validation engine; and the markup language schema validation parser performing a second validation of the token responsive to the token being an element token or an attribute token.
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29. The computer readable medium of claim 24 , further comprising instructions for: tokenizing the markup language document to generate a token; a generic XML parser performing a first validation of the token, the generic XML parser being associated with the runtime validation engine; and the markup language schema validation parser performing a second validation of the token responsive to the token being an element token or an attribute token. 33. The computer readable medium of claim 29 , wherein responsive to the element token being a start tag name, then the instructions for the markup language schema validation parser performing a second validation comprises instructions for: finding a current annotation record based upon a previous annotation record and the start tag name; pushing the current annotation record onto a stack; obtaining a start tag token for the start tag name from the current annotation record; inputting the start tag token into an element validation module associated with the markup language schema validation parser; and determining if a validation of the start tag token is successful.
| 0.631148 |
8,712,956 | 33 | 39 |
33. A method comprising: receiving a user selection of a report; displaying the user selected report in a view in a graphical user interface; receiving, by a computer, a user selection of a part of the report displayed in the view in the graphical user interface, the user selected report part associated with queries of a semantic layer, the report including a report part other than the user selected report part; displaying, in a single view in a graphical user interface, (a) the user selected report part and (b) a control to initiate creation of a description of a Web Service call to return contents of the user selected report part; receiving, by the computer, a user selection of the control to initiate creation of a description of a Web Service call to return contents of the user selected report part; in response to the user selection of the control to initiate creation of the description of the Web Service call to return contents of the user selected report part, issuing, by the computer, an instruction to create the description of the Web Service call to return contents of the user selected report part; in response to the instruction to create the description of the Web Service call to return contents of the user selected report part, creating, by a computer, the description of the Web Service call to return contents of the user selected report part without creating a description of a Web Service call to return contents of the report part other than the user selected report part; and storing the description of the Web Service call in a repository.
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33. A method comprising: receiving a user selection of a report; displaying the user selected report in a view in a graphical user interface; receiving, by a computer, a user selection of a part of the report displayed in the view in the graphical user interface, the user selected report part associated with queries of a semantic layer, the report including a report part other than the user selected report part; displaying, in a single view in a graphical user interface, (a) the user selected report part and (b) a control to initiate creation of a description of a Web Service call to return contents of the user selected report part; receiving, by the computer, a user selection of the control to initiate creation of a description of a Web Service call to return contents of the user selected report part; in response to the user selection of the control to initiate creation of the description of the Web Service call to return contents of the user selected report part, issuing, by the computer, an instruction to create the description of the Web Service call to return contents of the user selected report part; in response to the instruction to create the description of the Web Service call to return contents of the user selected report part, creating, by a computer, the description of the Web Service call to return contents of the user selected report part without creating a description of a Web Service call to return contents of the report part other than the user selected report part; and storing the description of the Web Service call in a repository. 39. A method according to claim 33 , the method further comprising: creating a description of a second Web Service call corresponding to the selected report part, the second Web Service call providing formatting parameters to specify a format of the formatted contents, wherein the second Web Service call is to return formatted contents of the selected report part based on the formatting parameters.
| 0.73231 |
7,480,613 | 8 | 16 |
8. A speech recognition system with a device for supporting proof-reading that is continuous throughout a text obtained by speech recognition of a speech signal, said text being divided into text components having respective reliability levels for the correctness of their speech recognition, wherein the device is designed to control, during the continuous proof-reading, progression of replay speed of the speech signal as a function of the reliability level of the text component adjusted to allow a smooth transition from one component replay speed to another component replay speed.
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8. A speech recognition system with a device for supporting proof-reading that is continuous throughout a text obtained by speech recognition of a speech signal, said text being divided into text components having respective reliability levels for the correctness of their speech recognition, wherein the device is designed to control, during the continuous proof-reading, progression of replay speed of the speech signal as a function of the reliability level of the text component adjusted to allow a smooth transition from one component replay speed to another component replay speed. 16. The system of claim 8 , wherein at least three of said reliability levels mutually differ.
| 0.5 |
9,460,086 | 1 | 3 |
1. A method for performing bilingual word alignment on source and target text in bilingual documents, the method comprising: computing probability gains of adding a link between any pair of source and target words in the source and target text; applying a greedy algorithm to iteratively search for a plurality of word alignments that satisfy an inversion transduction grammar constraint, wherein applying the greedy algorithm includes: initializing a pending list; generating a local list by performing an expanding operation to each word alignment in the pending list, and adding to the local list new word alignments that satisfy the inversion transduction grammar constraint; determining whether to update the lists after each iteration according to whether the pending list is empty; and outputting the best alignment from the word alignments in the local list; and outputting a best word alignment among the plurality as a final alignment result.
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1. A method for performing bilingual word alignment on source and target text in bilingual documents, the method comprising: computing probability gains of adding a link between any pair of source and target words in the source and target text; applying a greedy algorithm to iteratively search for a plurality of word alignments that satisfy an inversion transduction grammar constraint, wherein applying the greedy algorithm includes: initializing a pending list; generating a local list by performing an expanding operation to each word alignment in the pending list, and adding to the local list new word alignments that satisfy the inversion transduction grammar constraint; determining whether to update the lists after each iteration according to whether the pending list is empty; and outputting the best alignment from the word alignments in the local list; and outputting a best word alignment among the plurality as a final alignment result. 3. The method of claim 1 , wherein the probability gains are computed as gain ( i , j ) = p ( f j , e i ) p ( f j , ε ) × p ( ε , e i ) where e i is an i th source word, f j is a j th target word, p(f j , e i ) is a probability of e i that is aligned to f j , p(ε, e i ) is a probability of e i that is not aligned to any word, and p(f j , ε) is a probability of f j that is not aligned to any word.
| 0.757701 |
8,219,407 | 1 | 2 |
1. A method for processing the output of a speech recognizer comprising: determining that a recognized command by a speech recognizer requires additional processing; storing a representation of the output of the speech recognizer in a command structure; iteratively determining if the command is sufficiently complete and ready for processing, and if so executing the command in a respective application or process and exiting said iteratively determining step; if the command is insufficiently complete or not ready for processing, prompting a user for further input; receiving, processing and storing in the command structure prompted user command-related input; and determining an abort condition, and if the abort condition exists, exiting the iterative determining, else continuing said iteratively determining step.
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1. A method for processing the output of a speech recognizer comprising: determining that a recognized command by a speech recognizer requires additional processing; storing a representation of the output of the speech recognizer in a command structure; iteratively determining if the command is sufficiently complete and ready for processing, and if so executing the command in a respective application or process and exiting said iteratively determining step; if the command is insufficiently complete or not ready for processing, prompting a user for further input; receiving, processing and storing in the command structure prompted user command-related input; and determining an abort condition, and if the abort condition exists, exiting the iterative determining, else continuing said iteratively determining step. 2. The method according to claim 1 , wherein at least one of: a command status with respect to at least one of a context, an entry in a commands dictionary and a status with respect to a status flag; and analysis of the speech input with respect to at least one of a context and a completeness are used to determine if a command requires additional processing.
| 0.64775 |
8,400,313 | 20 | 21 |
20. A non-transitory computer readable storage medium that stores an arousal state classifying program for classifying an arousal state of an object person, the program when executed causing a computer to perform: a blink data acquisition step acquiring blink data of at least one eye of the object person at the time of blinking; a first feature data extraction step extracting first feature data corresponding to a first pattern model generated by the arousal state classification model generating program according to claim 17 from the blink data acquired by the blink data acquisition step; a blink waveform identification step identifying a specific type of blink waveform corresponding to the first feature data extracted in the first feature data extraction step based on the first feature data and the first pattern model; a second feature data generation step generating second feature data including data on an occurrence ratio of each of the specific types of blink waveforms based on an identification result by the blink waveform identification step with respect to the blink data of the object person acquired in a sequence of analysis intervals; and an arousal state classification step classifying the arousal state of the object person based on the second feature data generated in the second feature data generation step and a second pattern model generated by the arousal state classification model generating program.
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20. A non-transitory computer readable storage medium that stores an arousal state classifying program for classifying an arousal state of an object person, the program when executed causing a computer to perform: a blink data acquisition step acquiring blink data of at least one eye of the object person at the time of blinking; a first feature data extraction step extracting first feature data corresponding to a first pattern model generated by the arousal state classification model generating program according to claim 17 from the blink data acquired by the blink data acquisition step; a blink waveform identification step identifying a specific type of blink waveform corresponding to the first feature data extracted in the first feature data extraction step based on the first feature data and the first pattern model; a second feature data generation step generating second feature data including data on an occurrence ratio of each of the specific types of blink waveforms based on an identification result by the blink waveform identification step with respect to the blink data of the object person acquired in a sequence of analysis intervals; and an arousal state classification step classifying the arousal state of the object person based on the second feature data generated in the second feature data generation step and a second pattern model generated by the arousal state classification model generating program. 21. The non-transitory computer readable storage medium according to claim 20 , wherein the data on the occurrence ratio is a time variation of the occurrence ratio or a time variation of the number of occurrences.
| 0.5 |
7,711,241 | 32 | 33 |
32. The short film generation/reproduction apparatus according to claim 28 , wherein the database unit further stores face information for individual authentication used to identify a face of an individual, wherein the input unit further includes a face authentication unit operable to authenticate a name of the object based on the face information and to store the authenticated name of the object in the object information, when the object extracted by the object information extraction unit is a person's face, and wherein the parameter setting unit generates the scenario by describing a parameter indicating processing to be performed on the object specified by the authenticated name.
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32. The short film generation/reproduction apparatus according to claim 28 , wherein the database unit further stores face information for individual authentication used to identify a face of an individual, wherein the input unit further includes a face authentication unit operable to authenticate a name of the object based on the face information and to store the authenticated name of the object in the object information, when the object extracted by the object information extraction unit is a person's face, and wherein the parameter setting unit generates the scenario by describing a parameter indicating processing to be performed on the object specified by the authenticated name. 33. The short film generation/reproduction apparatus according to claim 32 , further comprising an individual information storage unit operable to store individual information in which a name of an individual and an attribute of the individual are associated with each other, wherein the input unit further includes an individual information search unit operable to search, from the individual information, for the attribute of the individual corresponding to the name of the object authenticated by the face authentication unit, and to store the individual attribute obtained by the search in the object information, and wherein the parameter setting unit generates the scenario by describing a parameter indicating processing to be performed on the object specified by the individual attribute.
| 0.5 |
9,405,519 | 7 | 9 |
7. A system for register clearing in data flow analysis in decompilation, comprising a processor and a non-transitory storage medium accessible to the processor, the non-transitory storage medium being configured to store units comprising a reading unit, a register name judging unit, a binary tree creating unit, an end tag judging unit, an eliminating unit and a high-level language generating unit, wherein the reading unit is adapted to open a code file in assembly language before the register clearing, and to read all function statements in the code file; the register name judging unit is adapted to perform judgment on each of the read function statements sequentially to judge whether the function statement comprises a register name, and to trigger the binary tree creating unit in a case that the function statement comprises the register name; the binary tree creating unit is adapted to create a binary tree and input the function statement into the binary tree; the end tag judging unit is adapted to perform judgment on each of the function statements comprising the register name sequentially to judge whether the function statement comprises a right child end tag of the binary tree; to trigger the eliminating unit in a case that the function statement comprises the right child end tag of the binary tree; and to send a judging instruction to the register name judging unit to instruct the register name judging unit to judge whether a next function statement comprises a register name in a case that the function statement comprises no right child end tag of the binary tree; the eliminating unit is adapted to perform an elimination process on the created binary tree to remove the register name from the binary tree, to generate a simplest binary tree; and the high-level language generating unit is adapted to generate a function statement in high-level language based on the simplest binary tree.
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7. A system for register clearing in data flow analysis in decompilation, comprising a processor and a non-transitory storage medium accessible to the processor, the non-transitory storage medium being configured to store units comprising a reading unit, a register name judging unit, a binary tree creating unit, an end tag judging unit, an eliminating unit and a high-level language generating unit, wherein the reading unit is adapted to open a code file in assembly language before the register clearing, and to read all function statements in the code file; the register name judging unit is adapted to perform judgment on each of the read function statements sequentially to judge whether the function statement comprises a register name, and to trigger the binary tree creating unit in a case that the function statement comprises the register name; the binary tree creating unit is adapted to create a binary tree and input the function statement into the binary tree; the end tag judging unit is adapted to perform judgment on each of the function statements comprising the register name sequentially to judge whether the function statement comprises a right child end tag of the binary tree; to trigger the eliminating unit in a case that the function statement comprises the right child end tag of the binary tree; and to send a judging instruction to the register name judging unit to instruct the register name judging unit to judge whether a next function statement comprises a register name in a case that the function statement comprises no right child end tag of the binary tree; the eliminating unit is adapted to perform an elimination process on the created binary tree to remove the register name from the binary tree, to generate a simplest binary tree; and the high-level language generating unit is adapted to generate a function statement in high-level language based on the simplest binary tree. 9. The system according to claim 7 , wherein the binary tree creating unit comprises a binary tree creating subunit, a left child subunit and a right child subunit, the binary tree creating subunit is adapted to create the binary tree; the left child subunit is adapted to input a code on the left of an equal sign in the function statement into a left child of the binary tree; and the right child subunit is adapted to input a code on the right of the equal sign in the function statement into a right child of the binary tree.
| 0.5 |
8,892,446 | 19 | 20 |
19. The computer readable storage medium of claim 15 , wherein each service is associated with a respective service capability model comprising declarative descriptions of respective capabilities and properties of the service.
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19. The computer readable storage medium of claim 15 , wherein each service is associated with a respective service capability model comprising declarative descriptions of respective capabilities and properties of the service. 20. The computer readable storage medium of claim 19 , wherein selectively invoking the subset of the plurality of services further comprises: dynamically selecting the subset of the plurality of services for invocation based on the respective service capability models of the plurality of services.
| 0.5 |
8,437,506 | 10 | 11 |
10. A software pipeline for generating a state estimate for a given frame of captured image data, the state estimate representing an estimate of a position of a user within a field of view captured within the image data, comprising: a preprocessing routine for receiving the image data, removing a background from the image data, and processing a foreground into one or more body part proposals; one or more experts for receiving information including the one or more body part proposals and generating a plurality of computer models, each computer model representing an estimation of the position of the user in the given frame of captured image data; and an arbiter for receiving the plurality of computer models, scoring the computer models by one or more methodologies which compare the plurality of computer models against depth data from the given frame and/or state estimate data from a prior frame, and outputting at least one computer model estimated by the arbiter to best approximate the position of the user in the frame.
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10. A software pipeline for generating a state estimate for a given frame of captured image data, the state estimate representing an estimate of a position of a user within a field of view captured within the image data, comprising: a preprocessing routine for receiving the image data, removing a background from the image data, and processing a foreground into one or more body part proposals; one or more experts for receiving information including the one or more body part proposals and generating a plurality of computer models, each computer model representing an estimation of the position of the user in the given frame of captured image data; and an arbiter for receiving the plurality of computer models, scoring the computer models by one or more methodologies which compare the plurality of computer models against depth data from the given frame and/or state estimate data from a prior frame, and outputting at least one computer model estimated by the arbiter to best approximate the position of the user in the frame. 11. A software pipeline as recited in claim 10 , the arbiter further including a depth score methodology for scoring each of the plurality of computer models by examining the computer model against the depth data for the given frame.
| 0.757292 |
8,868,587 | 2 | 3 |
2. The system of claim 1 , wherein: determining that a term of the original query meets an inaccuracy criterion comprises determining that the term is typographically incorrect; generating one or more derivative queries from the original query comprises generating a derivative query that includes only the terms of the original query that are not the potentially inaccurate term.
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2. The system of claim 1 , wherein: determining that a term of the original query meets an inaccuracy criterion comprises determining that the term is typographically incorrect; generating one or more derivative queries from the original query comprises generating a derivative query that includes only the terms of the original query that are not the potentially inaccurate term. 3. The system of claim 2 , wherein determining that the term is typographically incorrect comprises determining a synonym quality measure that is a measure of quality of synonym terms that are synonyms of the term does not meet a synonym quality measure threshold.
| 0.772806 |
9,703,854 | 1 | 8 |
1. A method, in a data processing system comprising a processor and a memory coupled to the processor, for determining criticality of a Structured Query Language (SQL) statement, comprising: extracting, by an extracting apparatus in a criticality determining device executed by the processor, a plurality of elements in the SQL statement; calculating, by a calculating apparatus in the criticality determining device executed by the processor, a score of the SQL statement based on a correlation relation among respective elements in the plurality of elements and base scores of the respective elements, wherein calculating the score of the SQL statement based on a correlation relation among respective elements in the plurality of elements and base scores of the respective elements includes: determining, by the calculating apparatus in the criticality determining device executed by the processor, the score of the SQL statement as a first value in response to that the correlation relation does not exist between any two of the plurality of elements, the first value being a maximum one of the respective base scores of the plurality of elements; and determining, by the calculating apparatus in the criticality determining device executed by the processor, the score of the SQL statement as a second value in response to that the correlation relation exists between at least two of the plurality of elements, the second value being greater than the maximum one of the respective base scores of the plurality of elements; and determining, by a determining apparatus in the criticality determining device executed by the processor, the criticality of the SQL statement based on the score of the SQL statement.
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1. A method, in a data processing system comprising a processor and a memory coupled to the processor, for determining criticality of a Structured Query Language (SQL) statement, comprising: extracting, by an extracting apparatus in a criticality determining device executed by the processor, a plurality of elements in the SQL statement; calculating, by a calculating apparatus in the criticality determining device executed by the processor, a score of the SQL statement based on a correlation relation among respective elements in the plurality of elements and base scores of the respective elements, wherein calculating the score of the SQL statement based on a correlation relation among respective elements in the plurality of elements and base scores of the respective elements includes: determining, by the calculating apparatus in the criticality determining device executed by the processor, the score of the SQL statement as a first value in response to that the correlation relation does not exist between any two of the plurality of elements, the first value being a maximum one of the respective base scores of the plurality of elements; and determining, by the calculating apparatus in the criticality determining device executed by the processor, the score of the SQL statement as a second value in response to that the correlation relation exists between at least two of the plurality of elements, the second value being greater than the maximum one of the respective base scores of the plurality of elements; and determining, by a determining apparatus in the criticality determining device executed by the processor, the criticality of the SQL statement based on the score of the SQL statement. 8. The method according to claim 1 , wherein determining the criticality of the SQL statement based on the score of the SQL statement includes: comparing, by the determining apparatus in the criticality determining device executed by the processor, the score of the SQL statement with a threshold value; and determining, by the determining apparatus in the criticality determining device executed by the processor, the SQL statement to be critical in response to the score of the SQL statement being greater than the threshold value.
| 0.5 |
8,781,813 | 7 | 8 |
7. A method, comprising: logging queries received from a plurality of users by an enterprise information system; using a clustering engine to identify clusters of the logged queries; generating names for the clusters of logged queries; using the generated names to create intent categories pertinent to the queries in the same clusters; using a linguistic matching language to match the queries in the same clusters with the intent categories; identifying ontologies associated with the intent categories; presenting concepts in the identified ontologies for selection by a user; assigning any of the selected concepts as ontology parameters for the associated intent categories; displaying intent responses for the ontology parameters assigned to the intent categories; configuring the intent responses for at least some of the intent categories; after matching queries to the intent categories, identifying ones of the intent categories matched with at least a first threshold number of the queries, and configuring all of the intent responses associated with said identified intent categories to be displayed together on an enterprise home web page if not currently configured to be displayed, wherein said display of all of the intent responses is visible to a user of the enterprise home web page; after matching queries to the intent categories, identifying ones of the intent categories that are not matched with at least a second threshold number of the queries, and removing a display configuration for intent responses for any of said identified intent categories if currently configured to be displayed; and after matching queries to the intent categories, for those ones of the intent categories with no associated intent response, identifying ones of the intent categories matched with at least a third threshold number of the questions, and initiating generation of an intent response for each of said identified intent categories.
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7. A method, comprising: logging queries received from a plurality of users by an enterprise information system; using a clustering engine to identify clusters of the logged queries; generating names for the clusters of logged queries; using the generated names to create intent categories pertinent to the queries in the same clusters; using a linguistic matching language to match the queries in the same clusters with the intent categories; identifying ontologies associated with the intent categories; presenting concepts in the identified ontologies for selection by a user; assigning any of the selected concepts as ontology parameters for the associated intent categories; displaying intent responses for the ontology parameters assigned to the intent categories; configuring the intent responses for at least some of the intent categories; after matching queries to the intent categories, identifying ones of the intent categories matched with at least a first threshold number of the queries, and configuring all of the intent responses associated with said identified intent categories to be displayed together on an enterprise home web page if not currently configured to be displayed, wherein said display of all of the intent responses is visible to a user of the enterprise home web page; after matching queries to the intent categories, identifying ones of the intent categories that are not matched with at least a second threshold number of the queries, and removing a display configuration for intent responses for any of said identified intent categories if currently configured to be displayed; and after matching queries to the intent categories, for those ones of the intent categories with no associated intent response, identifying ones of the intent categories matched with at least a third threshold number of the questions, and initiating generation of an intent response for each of said identified intent categories. 8. The method according to claim 7 , including using ontology elements associated with the enterprise information system as features for the clustering engine and then using at least some of the cluster names generated by the clustering engine to create the intent categories.
| 0.7792 |
8,886,856 | 12 | 19 |
12. A method of utilizing a bi-directional multi-lane link, the method comprising: transmitting a first plurality of words, wherein words of the first plurality of words that belong to a predetermined word category are transmitted only over a designated lane of the multi-lane link; striping words of the first plurality of words that belong to other word categories, other than the predetermined category, onto next available lanes of the multi-lane link; determining a word category of a word in a second plurality of words received over the designated lane; responsive to a determination that the word is of the predetermined word category, reading the word from the designated lane before lane-to-lane deskew is completed; and responsive to a determination that the word is not of the predetermined word category, reading the word from the designated lane after lane-to-lane deskew is completed.
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12. A method of utilizing a bi-directional multi-lane link, the method comprising: transmitting a first plurality of words, wherein words of the first plurality of words that belong to a predetermined word category are transmitted only over a designated lane of the multi-lane link; striping words of the first plurality of words that belong to other word categories, other than the predetermined category, onto next available lanes of the multi-lane link; determining a word category of a word in a second plurality of words received over the designated lane; responsive to a determination that the word is of the predetermined word category, reading the word from the designated lane before lane-to-lane deskew is completed; and responsive to a determination that the word is not of the predetermined word category, reading the word from the designated lane after lane-to-lane deskew is completed. 19. The method of claim 12 further comprising: reading words of the second plurality of words that are received over lanes other than the designated lane after lane-to-lane deskew is completed.
| 0.5 |
8,290,910 | 1 | 16 |
1. A method of replicating IP address assignment changes in a distributed database having a plurality of nodes, comprising: receiving a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database, and wherein the semantic command is defined by one or more instructions or operations; interpreting the semantic command; provisionally applying the semantic command to the first local version of the database before sending the semantic command to the master node; sending the semantic command to the master node to reconcile the semantic command with the master version of the database based on any IP address assignment changes associated with the semantic command; and reconciling the semantic command with the master version of the database, wherein reconciling the semantic command with the master version of the database includes determining whether the semantic command includes any IP address assignment changes that would result in an IP address assignment conflict with IP address assignment data stored in the master version of the database on the master node.
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1. A method of replicating IP address assignment changes in a distributed database having a plurality of nodes, comprising: receiving a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database, and wherein the semantic command is defined by one or more instructions or operations; interpreting the semantic command; provisionally applying the semantic command to the first local version of the database before sending the semantic command to the master node; sending the semantic command to the master node to reconcile the semantic command with the master version of the database based on any IP address assignment changes associated with the semantic command; and reconciling the semantic command with the master version of the database, wherein reconciling the semantic command with the master version of the database includes determining whether the semantic command includes any IP address assignment changes that would result in an IP address assignment conflict with IP address assignment data stored in the master version of the database on the master node. 16. A method as recited in claim 1 , wherein each of the plurality of nodes includes a semantic processor configured to interpret the semantic command and apply the semantic command to the local version of the database.
| 0.701635 |
7,548,651 | 21 | 22 |
21. The data process unit according to any of claims 18 to 20 , wherein the region dividing means divides the plurality of low dimensional vectors corresponding to pattern models by an outer circle and n inner circles (n is an integer equal to or larger than 1) and further divides ring-shaped regions formed by the concentric outer and inner circles therebetween into a plurality of regions by lines extending radially, where the outer circle is centered at the center of gravity of the coordinate points of all the low dimensional vectors corresponding to pattern models and has a radius equal to the distance between the center of gravity and the coordinate point of the low dimensional vector corresponding to pattern model farthest from the center of gravity while the inner circle is centered at the center of gravity and has a radius smaller than that of the outer circle.
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21. The data process unit according to any of claims 18 to 20 , wherein the region dividing means divides the plurality of low dimensional vectors corresponding to pattern models by an outer circle and n inner circles (n is an integer equal to or larger than 1) and further divides ring-shaped regions formed by the concentric outer and inner circles therebetween into a plurality of regions by lines extending radially, where the outer circle is centered at the center of gravity of the coordinate points of all the low dimensional vectors corresponding to pattern models and has a radius equal to the distance between the center of gravity and the coordinate point of the low dimensional vector corresponding to pattern model farthest from the center of gravity while the inner circle is centered at the center of gravity and has a radius smaller than that of the outer circle. 22. The data process unit according to claim 21 , wherein the region dividing means divides the low dimensional vectors corresponding to pattern models more finely with increasing radial distance from the innermost circle.
| 0.5 |
10,055,702 | 11 | 15 |
11. A non-transitory machine-readable medium comprising a plurality of instructions which, when executed by a hardware processing device of a visual workflow-management server computing device of a database system in a multi-tenant environment having tenants including organization, cause the hardware processing device to perform operations comprising: receiving a query to perform a collection of data relating to a tenant including an organization, wherein the query represents creating a new business process relating to workings of the organization; collecting the data from one or more accounts relating to the organization; assigning one or more tasks to the collected data; performing the one or more tasks; dynamically generating a visual workflow in response to the one or more tasks, wherein the visual workflow to facilitate the new business process based on the one or more tasks; and displaying the visual workflow at a display device.
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11. A non-transitory machine-readable medium comprising a plurality of instructions which, when executed by a hardware processing device of a visual workflow-management server computing device of a database system in a multi-tenant environment having tenants including organization, cause the hardware processing device to perform operations comprising: receiving a query to perform a collection of data relating to a tenant including an organization, wherein the query represents creating a new business process relating to workings of the organization; collecting the data from one or more accounts relating to the organization; assigning one or more tasks to the collected data; performing the one or more tasks; dynamically generating a visual workflow in response to the one or more tasks, wherein the visual workflow to facilitate the new business process based on the one or more tasks; and displaying the visual workflow at a display device. 15. The non-transitory machine-readable medium of claim 11 , wherein facilitating the new business process comprises amending or deleting an existing business process relating to the workings of the organization, wherein the organization comprises one or more of a business organization, a government agency, a non-profit organization, and an educational institution.
| 0.558894 |
9,135,244 | 1 | 16 |
1. A method for transforming an input data stream comprising data that is expressed in a non-linguistic format into a format that can be expressed linguistically in a textual output, the method comprising: accessing a document plan containing one or more messages, wherein messages represent a phrase or a simple sentence and are created in an instance in which the input data stream comprises data that satisfies one or more message requirements; generating a text specification containing one or more phrase specifications that correspond to the one or more messages in the document plan; applying, using a processor, a set of lexicalization rules to each of the one or more messages to populate the one or more phrase specifications, wherein the set of lexicalization rules are specified using a microplanning rule specification language that is configured to hide linguistic complexities from a user and comprise a set of message-level rules and a set of slot-level rules; and realizing the text specification to generate a textual output that linguistically describes at least a portion of the input data stream, wherein the textual output is displayable via a user interface.
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1. A method for transforming an input data stream comprising data that is expressed in a non-linguistic format into a format that can be expressed linguistically in a textual output, the method comprising: accessing a document plan containing one or more messages, wherein messages represent a phrase or a simple sentence and are created in an instance in which the input data stream comprises data that satisfies one or more message requirements; generating a text specification containing one or more phrase specifications that correspond to the one or more messages in the document plan; applying, using a processor, a set of lexicalization rules to each of the one or more messages to populate the one or more phrase specifications, wherein the set of lexicalization rules are specified using a microplanning rule specification language that is configured to hide linguistic complexities from a user and comprise a set of message-level rules and a set of slot-level rules; and realizing the text specification to generate a textual output that linguistically describes at least a portion of the input data stream, wherein the textual output is displayable via a user interface. 16. The method according to claim 1 , further comprising: applying one or more reference strategies.
| 0.86911 |
8,838,079 | 16 | 17 |
16. A system for providing keyword-based services to a user recipient of a message on a mobile device, the mobile device having a processor for executing computer-executable instructions, the system comprising: a memory storing computer-executable instructions of: a market segment component configured to determine a market segment of the user based on observed user activity on the mobile device and further based on profiling messages received by the user; an identification component configured to identify a plurality of keywords in a received text message by comparing text in the text message with the contents of a keyword inventory that is maintained on the mobile device; a filtering component configured to select a subset of keywords from the identified plurality of keywords, the filtering component selecting the subset of keywords based at least in part on user-specific information, including the market segment of the user, that is maintained on the mobile device, each of the subset of keywords having an associated one or more advertisements and contextual services; a display component configured to display the received text message to the user and to display one or more advertisements and contextual services associated with a keyword when a user selects one of the subset of keywords in the received text message; and a communication component configured to receive a selection of a keyword and an associated advertisement or contextual service by a user, the communication component invoking the advertisement or contextual service to obtain additional information associated with the selected keyword for display to the user, wherein invoking the selected advertisement or contextual service comprises transmitting the user-specific information to the selected advertisement or contextual service provided that the user has authorized such transmittal.
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16. A system for providing keyword-based services to a user recipient of a message on a mobile device, the mobile device having a processor for executing computer-executable instructions, the system comprising: a memory storing computer-executable instructions of: a market segment component configured to determine a market segment of the user based on observed user activity on the mobile device and further based on profiling messages received by the user; an identification component configured to identify a plurality of keywords in a received text message by comparing text in the text message with the contents of a keyword inventory that is maintained on the mobile device; a filtering component configured to select a subset of keywords from the identified plurality of keywords, the filtering component selecting the subset of keywords based at least in part on user-specific information, including the market segment of the user, that is maintained on the mobile device, each of the subset of keywords having an associated one or more advertisements and contextual services; a display component configured to display the received text message to the user and to display one or more advertisements and contextual services associated with a keyword when a user selects one of the subset of keywords in the received text message; and a communication component configured to receive a selection of a keyword and an associated advertisement or contextual service by a user, the communication component invoking the advertisement or contextual service to obtain additional information associated with the selected keyword for display to the user, wherein invoking the selected advertisement or contextual service comprises transmitting the user-specific information to the selected advertisement or contextual service provided that the user has authorized such transmittal. 17. The system of claim 16 , wherein the user-specific information includes a user location, a date and time, user interests, user behavior, or user preferences and settings.
| 0.534759 |
7,698,266 | 1 | 2 |
1. A method, comprising: organizing advertisements according to their meaning into a lexicon, the lexicon defining elements of a semantic space represented by a network of interconnected meanings; receiving a concept; determining one or more concepts close in meaning to the received concept; identifying one or more advertisements in the semantic space related to the received concept and the one or more concepts close in meaning to the received concept based on meanings of the advertisements; and transmitting for display the one or more advertisements based on an order, the order corresponding to a relationship between monetary values determined for each of the one or more advertisements identified as related to the received concept and the one or more concepts close in meaning to the received concept.
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1. A method, comprising: organizing advertisements according to their meaning into a lexicon, the lexicon defining elements of a semantic space represented by a network of interconnected meanings; receiving a concept; determining one or more concepts close in meaning to the received concept; identifying one or more advertisements in the semantic space related to the received concept and the one or more concepts close in meaning to the received concept based on meanings of the advertisements; and transmitting for display the one or more advertisements based on an order, the order corresponding to a relationship between monetary values determined for each of the one or more advertisements identified as related to the received concept and the one or more concepts close in meaning to the received concept. 2. The method of claim 1 , wherein the order is additionally based on a predicted relevance of the one or more advertisements to the received concept.
| 0.617347 |
7,970,723 | 5 | 6 |
5. A method for enabling use of a custom expression in a rules engine, the method comprising: providing the custom expression with access to validation context provided by the rules engine; validating the custom expression using the validation context using at least one processing unit; if the custom expression passes validation: determining which variables the custom expression reads from or writes to, providing the custom expression with access to execution context, and evaluating the custom expression; receiving a string representation of the custom expression; and parsing the string representation into a form understood by the rules engine.
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5. A method for enabling use of a custom expression in a rules engine, the method comprising: providing the custom expression with access to validation context provided by the rules engine; validating the custom expression using the validation context using at least one processing unit; if the custom expression passes validation: determining which variables the custom expression reads from or writes to, providing the custom expression with access to execution context, and evaluating the custom expression; receiving a string representation of the custom expression; and parsing the string representation into a form understood by the rules engine. 6. The method as recited in claim 5 wherein the string representation comprises an expression type, wherein further the expression type comprises a public constructor that takes a parameter that is understood by the rules engine.
| 0.5 |
9,189,568 | 7 | 8 |
7. A system comprising at least one server to: receive, for a plurality of item listings within a plurality of categories, item attributes expressed in a plurality of languages, each item attribute comprising an item attribute name and an item attribute value; convert the item attribute names and the item attribute values of the item attributes from the plurality of languages into language-independent symbols and store the item attributes for the plurality of item listings, expressed with the language-independent symbols, in an item listing table; receive one or more search attributes expressed in a language that is different from one or more of the plurality of languages of the item attributes, each search attribute comprising a search attribute name and a search attribute value; convert the search attribute name and the search attribute value of each of the one or more search attributes into the language-independent symbols; perform a search within the item listing table to identify at least one item listing with one or more item attributes expressed in the language-independent symbols that match the one or more search attributes expressed in the language-independent symbols; and display the item attributes of the at least one identified item listing in the language in which the search attributes as received were expressed.
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7. A system comprising at least one server to: receive, for a plurality of item listings within a plurality of categories, item attributes expressed in a plurality of languages, each item attribute comprising an item attribute name and an item attribute value; convert the item attribute names and the item attribute values of the item attributes from the plurality of languages into language-independent symbols and store the item attributes for the plurality of item listings, expressed with the language-independent symbols, in an item listing table; receive one or more search attributes expressed in a language that is different from one or more of the plurality of languages of the item attributes, each search attribute comprising a search attribute name and a search attribute value; convert the search attribute name and the search attribute value of each of the one or more search attributes into the language-independent symbols; perform a search within the item listing table to identify at least one item listing with one or more item attributes expressed in the language-independent symbols that match the one or more search attributes expressed in the language-independent symbols; and display the item attributes of the at least one identified item listing in the language in which the search attributes as received were expressed. 8. The system of claim 7 , wherein the language-independent symbols comprise punctuations marks.
| 0.87027 |
8,321,467 | 6 | 11 |
6. A computer-implemented system for communicating between an application and a database, the system comprising: a code generator to generate a code of databinding files to bind data of the database to a program of the application wherein said code identifies tables to persist the data in the database, wherein said code generates a table of metadata from the identified tables, wherein said code generates stored procedures from the metadata table, generates value objects (VO) from the metadata table and generates at least one XML binding definition from the metadata table; and at least one run-time component coupled to the code generator to integrate the generated code of the stored procedures to the VOs via the XML binding definitions into the application when the application is run.
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6. A computer-implemented system for communicating between an application and a database, the system comprising: a code generator to generate a code of databinding files to bind data of the database to a program of the application wherein said code identifies tables to persist the data in the database, wherein said code generates a table of metadata from the identified tables, wherein said code generates stored procedures from the metadata table, generates value objects (VO) from the metadata table and generates at least one XML binding definition from the metadata table; and at least one run-time component coupled to the code generator to integrate the generated code of the stored procedures to the VOs via the XML binding definitions into the application when the application is run. 11. The system of claim 6 wherein the database comprises a relational SQL SERVER database.
| 0.763158 |
7,668,806 | 1 | 32 |
1. A method of processing a query, comprising the computer-implemented steps of: receiving the query, wherein the query specifies certain operations to be performed, wherein the certain operations comprise a first set of one or more operations that are to be performed on a markup language data source; wherein the first set of one or more operations includes a second set of one or more operations; determining that the first set of one or more operations can be performed at any one of a plurality of entities; wherein the plurality of entities includes one or more of an XML database server, a relational database server, and a middle-tier engine; generating a plurality of execution plans for executing the query, wherein the plurality of execution plans include: a first execution plan indicating a first entity at which the second set of one or more operations are to be performed; and a second execution plan indicating a second entity at which the second set of one or more operations are to be performed; selecting, based on a particular set of criteria, a particular execution plan from the plurality of execution plans; wherein selecting the particular execution plan from the plurality of execution plans comprises one or more of: selecting the particular execution plan based at least in part on costs determined for the plurality of execution plans; and selecting the particular execution plan by using one or more rules to determine which execution plan, of the plurality of execution plans, to use for executing the query; wherein the selected particular execution plan indicates a first server at which the second set of one or more operations are to be performed; determining that a third set of one or more operations are to be performed at the middle-tier engine, wherein the first set of one or more operations include all operations in the third set of one or more operations, and the third set of one or more operations include no operation that are in the second set of one or more operations; sending a request to the first server to perform the second set of one or more operations; receiving a response to the request, wherein the response contains results of performing the second set of one or more operations on the markup language data source; and generating results for the query based at least in part on the results of performing the second set of one or more operations; wherein the steps of generating the plurality of execution plans and selecting the particular execution plan are performed by one or more computing devices.
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1. A method of processing a query, comprising the computer-implemented steps of: receiving the query, wherein the query specifies certain operations to be performed, wherein the certain operations comprise a first set of one or more operations that are to be performed on a markup language data source; wherein the first set of one or more operations includes a second set of one or more operations; determining that the first set of one or more operations can be performed at any one of a plurality of entities; wherein the plurality of entities includes one or more of an XML database server, a relational database server, and a middle-tier engine; generating a plurality of execution plans for executing the query, wherein the plurality of execution plans include: a first execution plan indicating a first entity at which the second set of one or more operations are to be performed; and a second execution plan indicating a second entity at which the second set of one or more operations are to be performed; selecting, based on a particular set of criteria, a particular execution plan from the plurality of execution plans; wherein selecting the particular execution plan from the plurality of execution plans comprises one or more of: selecting the particular execution plan based at least in part on costs determined for the plurality of execution plans; and selecting the particular execution plan by using one or more rules to determine which execution plan, of the plurality of execution plans, to use for executing the query; wherein the selected particular execution plan indicates a first server at which the second set of one or more operations are to be performed; determining that a third set of one or more operations are to be performed at the middle-tier engine, wherein the first set of one or more operations include all operations in the third set of one or more operations, and the third set of one or more operations include no operation that are in the second set of one or more operations; sending a request to the first server to perform the second set of one or more operations; receiving a response to the request, wherein the response contains results of performing the second set of one or more operations on the markup language data source; and generating results for the query based at least in part on the results of performing the second set of one or more operations; wherein the steps of generating the plurality of execution plans and selecting the particular execution plan are performed by one or more computing devices. 32. A machine-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 1 .
| 0.912898 |
9,213,682 | 1 | 4 |
1. A business document auditing device comprising: a receiver configured to receive: a set of universal presentation rules comprising one or more parameters, said universal presentation rules configured to override all other presentation rules, wherein said universal presentation rules are enforced, irrespective of a user's wishes, across substantially every business document of the user, wherein the universal presentation rules comprise: page word count rules which limit the total word count on each page of each business document of the user; bullet point word count rules which limit the total word count on each bullet point included on each business document of the user; line count rules which limit the total number of lines on each page of each business document of the user; color rules which limit the palette of colors used on each page of each business document of the user; and density rules which limit the amount of white space on each page of each business document of the user; and a set of customized presentation rules comprising one or more parameters, said customized presentation rules customized by the user, wherein said customized presentation rules allow the user to enforce the customized presentation rules on a single business document, wherein the customized presentation rules are included on a displayable audit panel, wherein the displayable audit panel is viewable adjacent to the business document; a memory configured to store: execution instructions; one or more business documents; the set of universal presentation rules; and the set of customized presentation rules; and a processor coupled with the memory, the processor configured to execute the instructions, the instructions configured to cause the processor to: compare a parameter of an element of a business document of the one or more business documents to a first parameter of the universal presentation rules, wherein, when the parameter of the element of the business document is a non-compliant parameter, the processor is further configured to conform the element of the business document to the first parameter of the universal presentation rules; and compare the universal presentation rules to the customized presentation rules, wherein: when the universal presentation rules are in conflict with the customized presentation rules, the processor is further configured to cause the universal presentation rules to override the customized presentation rules; and when the universal presentation rules are not in conflict with the customized presentation rules, the processor is further configured to: compare the parameter of the element of the business document to a second parameter of the customized presentation rules, and cause the processor to, when the parameter of the element of the business document is a non-compliant parameter, present an option to the user to conform the element of the business document to the second parameter of the customized presentation rules.
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1. A business document auditing device comprising: a receiver configured to receive: a set of universal presentation rules comprising one or more parameters, said universal presentation rules configured to override all other presentation rules, wherein said universal presentation rules are enforced, irrespective of a user's wishes, across substantially every business document of the user, wherein the universal presentation rules comprise: page word count rules which limit the total word count on each page of each business document of the user; bullet point word count rules which limit the total word count on each bullet point included on each business document of the user; line count rules which limit the total number of lines on each page of each business document of the user; color rules which limit the palette of colors used on each page of each business document of the user; and density rules which limit the amount of white space on each page of each business document of the user; and a set of customized presentation rules comprising one or more parameters, said customized presentation rules customized by the user, wherein said customized presentation rules allow the user to enforce the customized presentation rules on a single business document, wherein the customized presentation rules are included on a displayable audit panel, wherein the displayable audit panel is viewable adjacent to the business document; a memory configured to store: execution instructions; one or more business documents; the set of universal presentation rules; and the set of customized presentation rules; and a processor coupled with the memory, the processor configured to execute the instructions, the instructions configured to cause the processor to: compare a parameter of an element of a business document of the one or more business documents to a first parameter of the universal presentation rules, wherein, when the parameter of the element of the business document is a non-compliant parameter, the processor is further configured to conform the element of the business document to the first parameter of the universal presentation rules; and compare the universal presentation rules to the customized presentation rules, wherein: when the universal presentation rules are in conflict with the customized presentation rules, the processor is further configured to cause the universal presentation rules to override the customized presentation rules; and when the universal presentation rules are not in conflict with the customized presentation rules, the processor is further configured to: compare the parameter of the element of the business document to a second parameter of the customized presentation rules, and cause the processor to, when the parameter of the element of the business document is a non-compliant parameter, present an option to the user to conform the element of the business document to the second parameter of the customized presentation rules. 4. The device of claim 1 wherein, when the customized presentation rules are a first set of customized presentation rules the device further comprises: the receiver further configured to receive a second set of customized presentation rules; and the processor further configured to conform the element of the business document to the second set of customized presentation rules.
| 0.5 |
7,716,252 | 10 | 12 |
10. A method implemented on a computing device having instructions executable by a processor, the method comprising: receiving data related to an object that is contained in a data store by at least one relationship provider, wherein the at least one relationship provider is a Cmdlet, that corresponds to the data store; exposing the data by the at least one relationship provider to a relationship provider engine, wherein the relationship provider engine loads, manipulates, and surfaces a relationship corresponding to the object that is contained in the data store through an application programming interface consumed by the at least one relationship provider; adding the data store to the assembly; accessing the data received at the at least one relationship provider by the relationship provider engine, each relationship provider corresponding to one or more data stores, wherein the relationship provider engine shows the relationship between objects in one or more data stores to a user; implementing a relationship provider base class on the at least one relationship provider, wherein the relationship provider base class is an abstract class and the relationship provider base class comprises: one or more attributes that represent a relationship between the first object and the second object by; a relationship name field that identifies the relationship; a first relationship provider field that identifies a first relationship provider or a data store from which the relationship originates; a second relationship provider field that identifies a second relationship provider or a data store to which the relationship maps; a Description Property that describes the relationship as a localized string; and one or more functions to respond to a command from a user comprising: an IsRelationshipValid function that returns true if the relationship is valid for a path, a property, and a target; a GetRelationshipTargets function that returns targets possible to traverse based on a specified path; a ResolveRelationship function that receives a path in the first relationship provider and returns a path to the second relationship provider, and a CanResolveRelationship function that returns true if an input relationship can be resolved from the first relationship provider to the second relationship provider; analyzing the data received by the at least one relationship provider by utilizing the one or more attributes, which are of the implemented relationship provider base class on the at least one relationship provider and which correspond to the first object and second object, to determine dynamically the relationship between the first object and the second object, wherein the analyzing is performed by the relationship provider engine using an application programming interface (API); receiving the command from the user; and depicting visually the relationship between the first object and the second object to the user using at least one function of the implemented relationship provider base class on the at least one relationship provider, wherein the depicting visually comprises rendering a depiction in a manner distinguishable from a static directory content, the manner comprising at least one of: a coloration, a typeface, a hyper-text, or a graphic icon.
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10. A method implemented on a computing device having instructions executable by a processor, the method comprising: receiving data related to an object that is contained in a data store by at least one relationship provider, wherein the at least one relationship provider is a Cmdlet, that corresponds to the data store; exposing the data by the at least one relationship provider to a relationship provider engine, wherein the relationship provider engine loads, manipulates, and surfaces a relationship corresponding to the object that is contained in the data store through an application programming interface consumed by the at least one relationship provider; adding the data store to the assembly; accessing the data received at the at least one relationship provider by the relationship provider engine, each relationship provider corresponding to one or more data stores, wherein the relationship provider engine shows the relationship between objects in one or more data stores to a user; implementing a relationship provider base class on the at least one relationship provider, wherein the relationship provider base class is an abstract class and the relationship provider base class comprises: one or more attributes that represent a relationship between the first object and the second object by; a relationship name field that identifies the relationship; a first relationship provider field that identifies a first relationship provider or a data store from which the relationship originates; a second relationship provider field that identifies a second relationship provider or a data store to which the relationship maps; a Description Property that describes the relationship as a localized string; and one or more functions to respond to a command from a user comprising: an IsRelationshipValid function that returns true if the relationship is valid for a path, a property, and a target; a GetRelationshipTargets function that returns targets possible to traverse based on a specified path; a ResolveRelationship function that receives a path in the first relationship provider and returns a path to the second relationship provider, and a CanResolveRelationship function that returns true if an input relationship can be resolved from the first relationship provider to the second relationship provider; analyzing the data received by the at least one relationship provider by utilizing the one or more attributes, which are of the implemented relationship provider base class on the at least one relationship provider and which correspond to the first object and second object, to determine dynamically the relationship between the first object and the second object, wherein the analyzing is performed by the relationship provider engine using an application programming interface (API); receiving the command from the user; and depicting visually the relationship between the first object and the second object to the user using at least one function of the implemented relationship provider base class on the at least one relationship provider, wherein the depicting visually comprises rendering a depiction in a manner distinguishable from a static directory content, the manner comprising at least one of: a coloration, a typeface, a hyper-text, or a graphic icon. 12. The method of claim 10 , further comprising enabling the user to navigate directly from the first object to the second object.
| 0.697674 |
10,031,749 | 17 | 18 |
17. A context specific help file embodied in a computer readable medium comprising: a non-transitory computer readable medium; a first component, the first component including a text file received from a first object of a user model that models a software application related process selected by a user, wherein the user model represents a network of related concepts, wherein the user model defines a plurality of objects and a plurality of linked relationships between the plurality of objects wherein the user model provides a navigation model for a user to move between annotations and meta-model elements in a user interface, wherein the user model specifies requirements for the user interface, wherein the plurality of objects provide a plurality of menu lists as entry points to the context-specific help file and wherein the software application related process is any of an install software task, an uninstall software task, or a refresh installed software task; all additional objects of the user model not selected by the user and corresponding with the first component and to present at least one additional object to the user, the at least one additional object connected with the first object as defined by the user model and corresponding with the first component, and wherein the at least one additional component comprises at least a link to a respective text file of the at least one additional object connected to the first object.
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17. A context specific help file embodied in a computer readable medium comprising: a non-transitory computer readable medium; a first component, the first component including a text file received from a first object of a user model that models a software application related process selected by a user, wherein the user model represents a network of related concepts, wherein the user model defines a plurality of objects and a plurality of linked relationships between the plurality of objects wherein the user model provides a navigation model for a user to move between annotations and meta-model elements in a user interface, wherein the user model specifies requirements for the user interface, wherein the plurality of objects provide a plurality of menu lists as entry points to the context-specific help file and wherein the software application related process is any of an install software task, an uninstall software task, or a refresh installed software task; all additional objects of the user model not selected by the user and corresponding with the first component and to present at least one additional object to the user, the at least one additional object connected with the first object as defined by the user model and corresponding with the first component, and wherein the at least one additional component comprises at least a link to a respective text file of the at least one additional object connected to the first object. 18. The context-specific help file of claim 17 , wherein the context-specific help file is configured to automatically regenerate in response to a detected underlying structural change in the user model without user intervention.
| 0.636508 |
7,774,301 | 22 | 23 |
22. A computer-implemented method for transforming unstructured information and associated metadata into content in a uniform context, comprising: using a federation service of a computer including a processor that presents a single view of source content repositories to a user: receiving a query specifying source content groups in a set of the source content repositories; running the query to retrieve metadata schemas of the source content groups specified in the query, wherein each source content group has a metadata schema that describes a structure of metadata associated with the unstructured information in the source content group; extracting the unstructured information and metadata associated with the unstructured information from the set of the source content repositories; in response to user input, receiving selection of target content groups in another set of target content repositories; in response to receiving the selection of the target content groups, identifying metadata schemas of the target content groups, wherein each metadata schema describes a structure of metadata associated with the unstructured information in a target content group; creating a schema definition file including the extracted metadata schemas of the source content groups and the identified metadata schemas of the target content groups; forwarding the unstructured information, metadata, and schema definition file to a transformation service of the computer; using the transformation service, performing one or more custom mappings on at least one of the unstructured information and the associated metadata by mapping elements of the extracted metadata schemas of the source content groups to the identified metadata schemas of the target content groups; transforming at least one of the unstructured information and the associated metadata with custom transformations; and forwarding the mapped and transformed unstructured information and the associated metadata to the federation service.
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22. A computer-implemented method for transforming unstructured information and associated metadata into content in a uniform context, comprising: using a federation service of a computer including a processor that presents a single view of source content repositories to a user: receiving a query specifying source content groups in a set of the source content repositories; running the query to retrieve metadata schemas of the source content groups specified in the query, wherein each source content group has a metadata schema that describes a structure of metadata associated with the unstructured information in the source content group; extracting the unstructured information and metadata associated with the unstructured information from the set of the source content repositories; in response to user input, receiving selection of target content groups in another set of target content repositories; in response to receiving the selection of the target content groups, identifying metadata schemas of the target content groups, wherein each metadata schema describes a structure of metadata associated with the unstructured information in a target content group; creating a schema definition file including the extracted metadata schemas of the source content groups and the identified metadata schemas of the target content groups; forwarding the unstructured information, metadata, and schema definition file to a transformation service of the computer; using the transformation service, performing one or more custom mappings on at least one of the unstructured information and the associated metadata by mapping elements of the extracted metadata schemas of the source content groups to the identified metadata schemas of the target content groups; transforming at least one of the unstructured information and the associated metadata with custom transformations; and forwarding the mapped and transformed unstructured information and the associated metadata to the federation service. 23. The computer-implemented method of claim 22 , further comprising: using the federation service: receiving, from the transformation service, mapped and transformed unstructured information and the associated metadata; and loading the mapped and transformed unstructured information and the associated metadata into the target content groups.
| 0.5 |
9,355,169 | 12 | 21 |
12. A system for extracting a set of phrases from a plurality of documents, the system comprising: one or more computer readable media comprising executable instructions; and one or more processors configured to execute the instructions, wherein execution of the instructions causes the system to: for each document: identify a plurality of candidate phrases occurring in the document, wherein a candidate phrase includes two or more consecutive words that are determined to occur in the document; score candidate phrases in the document to produce respective document phrase scores for the candidate phrases for the document, the document phrase score for a candidate phrase being based on attributes of individual occurrences of the candidate phrase in the document, with at least some candidate phrases appearing repeatedly having a higher document phrase score than candidate phrases appearing once, and for a candidate phrase of the plurality of the candidate phrases: create, via the one or more processors, a combined score for the candidate phrase based on a plurality of different document phrase scores for the candidate phrase for respective different documents; and selecting the candidate phrase for inclusion in the extracted set based on the combined score for the candidate phrase and based on the document phrase scores for the candidate phrase.
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12. A system for extracting a set of phrases from a plurality of documents, the system comprising: one or more computer readable media comprising executable instructions; and one or more processors configured to execute the instructions, wherein execution of the instructions causes the system to: for each document: identify a plurality of candidate phrases occurring in the document, wherein a candidate phrase includes two or more consecutive words that are determined to occur in the document; score candidate phrases in the document to produce respective document phrase scores for the candidate phrases for the document, the document phrase score for a candidate phrase being based on attributes of individual occurrences of the candidate phrase in the document, with at least some candidate phrases appearing repeatedly having a higher document phrase score than candidate phrases appearing once, and for a candidate phrase of the plurality of the candidate phrases: create, via the one or more processors, a combined score for the candidate phrase based on a plurality of different document phrase scores for the candidate phrase for respective different documents; and selecting the candidate phrase for inclusion in the extracted set based on the combined score for the candidate phrase and based on the document phrase scores for the candidate phrase. 21. The system of claim 12 , wherein selecting the candidate phrase for inclusion in the extracted set based on the combined score and based on the document phrase scores includes: selecting the candidate phrase when a maximum value of the document phrase scores exceeds a first threshold, or when the combined score exceeds a second threshold, or when the number of documents for which the candidate phrase had at least a minimum document phrase score exceeds a third threshold.
| 0.5 |
8,589,161 | 6 | 7 |
6. The method of claim 3 , wherein collating the intent determination responses further includes terminating the collating in response to determining that a predetermined amount of time has lapsed, a predetermined amount of resources have been consumed, or one or more of the interleaved intent determination responses received from the one or more secondary devices meets or exceeds an acceptable confidence level.
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6. The method of claim 3 , wherein collating the intent determination responses further includes terminating the collating in response to determining that a predetermined amount of time has lapsed, a predetermined amount of resources have been consumed, or one or more of the interleaved intent determination responses received from the one or more secondary devices meets or exceeds an acceptable confidence level. 7. The method of claim 6 , wherein the input device that initially received the multi-modal natural language input communicates the multi-modal natural language input to the central device in response to an initial intent determination generated on the input device failing to meet or exceed the acceptable confidence level.
| 0.5 |
8,635,173 | 1 | 8 |
1. A system for hosting data, comprising: at least one computing device in a first region of control that: receives from at least one computing device in a second region of control via at least one network, a data request applicable to at least one data set stored by the at least one computing device in the first region of control; in response to the data request, extracts a subset of results from the at least one data set based on the data request; infers from the subset of the results additional semantic information that describes the at least one data set; and forms or updates mapping information that describes an identifier of the at least one data set based on the additional semantic information.
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1. A system for hosting data, comprising: at least one computing device in a first region of control that: receives from at least one computing device in a second region of control via at least one network, a data request applicable to at least one data set stored by the at least one computing device in the first region of control; in response to the data request, extracts a subset of results from the at least one data set based on the data request; infers from the subset of the results additional semantic information that describes the at least one data set; and forms or updates mapping information that describes an identifier of the at least one data set based on the additional semantic information. 8. The system according to claim 1 , wherein the at least one computing device in the first region of control extracts the subset of results returned from executing at least one data request derived from the data request.
| 0.599638 |
7,477,697 | 9 | 10 |
9. The method according to claim 6 , wherein at least the data words of data blocks relating to the periodic structures are multiplexed in space-frequency.
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9. The method according to claim 6 , wherein at least the data words of data blocks relating to the periodic structures are multiplexed in space-frequency. 10. The method according to claim 9 , wherein the data words of data blocks relating to the user data section are multiplexed in space-time.
| 0.5 |
9,026,851 | 1 | 13 |
1. A computer-implemented method for proactive customer experience management in a communication network, comprising: a) obtaining a performance-indicating alert (PA) from at least one probe; b) identifying relevant alerts from an alert database in absence of possible fault condition from the PA; c) determining a possible problem condition from the PA and the identified relevant alerts; d) raising trace trigger for gathering relevant trace data; e) determining specific problem condition and relevant cause, based on gathered trace data and relevant data from PM/FM, CDR and OSS systems; f) determining appropriate recommendation for resolution of the determined specific problem condition; g) recalculating a probe alert threshold value for triggering the performance-indicating probe alert; h) providing the recalculated probe alert threshold value for modifying a configuration of a performance-indicating probe; i) updating a user interface dashboard using the determination of a root cause of the possible problem and the recommendation for resolution of the possible problem; and j) updating new knowledge into a knowledge base with problem-context, resolution, relevant adjustments to alerts, thresholds and rules.
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1. A computer-implemented method for proactive customer experience management in a communication network, comprising: a) obtaining a performance-indicating alert (PA) from at least one probe; b) identifying relevant alerts from an alert database in absence of possible fault condition from the PA; c) determining a possible problem condition from the PA and the identified relevant alerts; d) raising trace trigger for gathering relevant trace data; e) determining specific problem condition and relevant cause, based on gathered trace data and relevant data from PM/FM, CDR and OSS systems; f) determining appropriate recommendation for resolution of the determined specific problem condition; g) recalculating a probe alert threshold value for triggering the performance-indicating probe alert; h) providing the recalculated probe alert threshold value for modifying a configuration of a performance-indicating probe; i) updating a user interface dashboard using the determination of a root cause of the possible problem and the recommendation for resolution of the possible problem; and j) updating new knowledge into a knowledge base with problem-context, resolution, relevant adjustments to alerts, thresholds and rules. 13. The method of claim 1 , further comprising: triggering, based on the root cause analysis, the gathering of the trace data via the selective trace trigger.
| 0.70632 |
8,768,731 | 18 | 19 |
18. A computer implemented method, comprising: generating a syndicated data feed using a microprocessor of the computer executing instructions stored in a non-transitory computer memory that includes aggregated ultrasound echo data from a plurality of medical devices secured using a conditional access mechanism, the syndicated data feed using a format selected from the group consisting of: Really Simple Syndication, Resource Description Framework Site Summary, Rich Site Summary and Outline Processor Markup Language; publishing the syndicated data feed to a publicly-accessible network using the microprocessor of the computer executing instructions stored in a non-transitory computer memory; extracting information relating to an abnormality in the ultrasound echo data from the syndicated data feed; extracting information relating to patient treatment data and patient characteristics from the syndicated data feed; searching for abnormalities in the ultrasound echo data; comparing the extracted data related to the abnormality in the ultrasound data with comparable ultrasound echo data from a normal specimen; and correlating the abnormalities in the ultrasound echo data with the patient treatment data.
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18. A computer implemented method, comprising: generating a syndicated data feed using a microprocessor of the computer executing instructions stored in a non-transitory computer memory that includes aggregated ultrasound echo data from a plurality of medical devices secured using a conditional access mechanism, the syndicated data feed using a format selected from the group consisting of: Really Simple Syndication, Resource Description Framework Site Summary, Rich Site Summary and Outline Processor Markup Language; publishing the syndicated data feed to a publicly-accessible network using the microprocessor of the computer executing instructions stored in a non-transitory computer memory; extracting information relating to an abnormality in the ultrasound echo data from the syndicated data feed; extracting information relating to patient treatment data and patient characteristics from the syndicated data feed; searching for abnormalities in the ultrasound echo data; comparing the extracted data related to the abnormality in the ultrasound data with comparable ultrasound echo data from a normal specimen; and correlating the abnormalities in the ultrasound echo data with the patient treatment data. 19. The computer implemented method of claim 18 further comprising extracting information from the syndicated data feed, the information selected from the group consisting of a virus, a virus parameter and an indication of a virus; and filtering the syndicated data feed based on the extracted information.
| 0.5 |
9,137,401 | 1 | 2 |
1. An electric apparatus comprising: a touch panel; a content storage unit that stores content to be displayed on the touch panel in different languages; a selected language storage unit that stores a selected language; a content display unit that displays, on the touch panel, content corresponding to the selected language stored in the selected language storage unit, of pieces of content stored in the content storage unit in the languages; and a language setting unit that displays a first language selection screen including items corresponding to regions of the world on the touch panel if a particular operation is accepted in a non-explicit area other than an explicit area that is explicitly indicated as being ready for accepting an operation, the first language selection screen being one of screens displayed on the touch panel, specifies an item if a portion touched on the touch panel reaches an explicit area on the first language selection screen by moving the portion touched on the touch panel, displays a second language selection screen including items corresponding to each of the languages corresponding to the specified item on the first language selection screen, specifies an item if a portion touched on the touch panel reaches an explicit area on the second language selection screen by moving the portion touched on the touch panel, and stores, in the selected language storage unit, a language corresponding to the specified item on the second language selection screen, wherein after the first or second language selection screen has been displayed on the touch panel, if an operation to cancel a state in which the touch panel is touched is accepted before the portion touched on the touch panel reaches the explicit area on the first or second language selection screen, the language setting unit turns off the first or second language selection screen displayed on the touch panel.
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1. An electric apparatus comprising: a touch panel; a content storage unit that stores content to be displayed on the touch panel in different languages; a selected language storage unit that stores a selected language; a content display unit that displays, on the touch panel, content corresponding to the selected language stored in the selected language storage unit, of pieces of content stored in the content storage unit in the languages; and a language setting unit that displays a first language selection screen including items corresponding to regions of the world on the touch panel if a particular operation is accepted in a non-explicit area other than an explicit area that is explicitly indicated as being ready for accepting an operation, the first language selection screen being one of screens displayed on the touch panel, specifies an item if a portion touched on the touch panel reaches an explicit area on the first language selection screen by moving the portion touched on the touch panel, displays a second language selection screen including items corresponding to each of the languages corresponding to the specified item on the first language selection screen, specifies an item if a portion touched on the touch panel reaches an explicit area on the second language selection screen by moving the portion touched on the touch panel, and stores, in the selected language storage unit, a language corresponding to the specified item on the second language selection screen, wherein after the first or second language selection screen has been displayed on the touch panel, if an operation to cancel a state in which the touch panel is touched is accepted before the portion touched on the touch panel reaches the explicit area on the first or second language selection screen, the language setting unit turns off the first or second language selection screen displayed on the touch panel. 2. The electric apparatus according to claim 1 , wherein the particular operation is to continue to touch a portion touched on the touch panel.
| 0.828947 |
9,501,566 | 1 | 4 |
1. A computer-implemented method comprising: receiving, from an input device, an input phrase defining an initial scope of a concept search; identifying, by a processing device, a plurality of concept terms related to the input phrase in view of an analysis of documents in a data set; determining, by the processing device, a relevance score for each of the plurality of concept terms; determining, by the processing device, a set of concept terms from the plurality of concept terms that have a relevance score that exceeds a threshold value; displaying the set of concept terms at a first section of a graphical user interface (GUI); displaying the input phrase at a second section of the GUI; receiving, from the input device, a selection of a concept term from the set of concept terms; displaying, in the second section of the GUI, a visual representation of a relationship between the selected concept term and the input phrase in response to the selection of the concept term; identifying, by the processing device, one or more of the documents related to the selection of the concept term and the input phrase; displaying, in a third section of the GUI, a count of the one or more documents related to the selection of the concept term and the input phrase; receiving, from the input device, a selection of an additional concept term from the set of concept terms; identifying, by the processing device, one or more of the documents related to the selected concept term, the input phrase, and the additional concept term; updating the visual representation to indicate a relationship between the selected concept term, the additional concept term, and the input phrase; and displaying the one or more documents to a user.
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1. A computer-implemented method comprising: receiving, from an input device, an input phrase defining an initial scope of a concept search; identifying, by a processing device, a plurality of concept terms related to the input phrase in view of an analysis of documents in a data set; determining, by the processing device, a relevance score for each of the plurality of concept terms; determining, by the processing device, a set of concept terms from the plurality of concept terms that have a relevance score that exceeds a threshold value; displaying the set of concept terms at a first section of a graphical user interface (GUI); displaying the input phrase at a second section of the GUI; receiving, from the input device, a selection of a concept term from the set of concept terms; displaying, in the second section of the GUI, a visual representation of a relationship between the selected concept term and the input phrase in response to the selection of the concept term; identifying, by the processing device, one or more of the documents related to the selection of the concept term and the input phrase; displaying, in a third section of the GUI, a count of the one or more documents related to the selection of the concept term and the input phrase; receiving, from the input device, a selection of an additional concept term from the set of concept terms; identifying, by the processing device, one or more of the documents related to the selected concept term, the input phrase, and the additional concept term; updating the visual representation to indicate a relationship between the selected concept term, the additional concept term, and the input phrase; and displaying the one or more documents to a user. 4. The method of claim 1 , further comprising: executing a search of the data set to locate the one or more documents based on the selection of the concept term and the input phrase.
| 0.764858 |
8,050,918 | 7 | 9 |
7. A tangible computer-readable storage device encoded with instructions which, when executed by a computer, cause the computer to perform a method of evaluating grammars associated with a voice portal, the method comprising: generating, for a current grammar of the voice portal representing a valid input for a first menu of the voice portal, a test input, the test input for the current grammar including a test pattern; providing the test input to the voice portal; receiving at least one measure of how distinguishable the current grammar is from other grammars of a set of active grammars that are active when the current grammar is active, the set of active grammars including the current grammar and at least one grammar from a second menu of the voice portal, the at least one measure based at least in part on analysis of the test pattern with respect to the set of active grammars, the at least one measure comprising at least one measure of how distinguishable the current grammar is from the at least one grammar from the second menu of the voice portal; and determining, based at least in part on the at least one measure, whether to modify the current grammar from the first menu to be distinguishable from the at least one grammar from the second menu.
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7. A tangible computer-readable storage device encoded with instructions which, when executed by a computer, cause the computer to perform a method of evaluating grammars associated with a voice portal, the method comprising: generating, for a current grammar of the voice portal representing a valid input for a first menu of the voice portal, a test input, the test input for the current grammar including a test pattern; providing the test input to the voice portal; receiving at least one measure of how distinguishable the current grammar is from other grammars of a set of active grammars that are active when the current grammar is active, the set of active grammars including the current grammar and at least one grammar from a second menu of the voice portal, the at least one measure based at least in part on analysis of the test pattern with respect to the set of active grammars, the at least one measure comprising at least one measure of how distinguishable the current grammar is from the at least one grammar from the second menu of the voice portal; and determining, based at least in part on the at least one measure, whether to modify the current grammar from the first menu to be distinguishable from the at least one grammar from the second menu. 9. The tangible computer-readable storage device of claim 7 , wherein the method further comprises modifying the current grammar to create a modified grammar if the at least one measure indicates that the current grammar is not sufficiently distinguishable from the other grammars of the set of active grammars.
| 0.710967 |
7,797,673 | 1 | 13 |
1. A computer-implemented method for applying a coding standard to a simulatable graphical model in a graphical modeling environment, the method comprising the steps of: providing a coding standard in the graphical modeling environment; applying the coding standard to the simulatable graphical model to detect violations of the coding standard in the simulatable graphical model; displaying violating segments of the simulatable graphical model differently than non-violating segments of the simulatable graphical model; and in response to users' selection of a selected one of violating segments, displaying information on a violation of the coding standard in the selected violating segment.
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1. A computer-implemented method for applying a coding standard to a simulatable graphical model in a graphical modeling environment, the method comprising the steps of: providing a coding standard in the graphical modeling environment; applying the coding standard to the simulatable graphical model to detect violations of the coding standard in the simulatable graphical model; displaying violating segments of the simulatable graphical model differently than non-violating segments of the simulatable graphical model; and in response to users' selection of a selected one of violating segments, displaying information on a violation of the coding standard in the selected violating segment. 13. The method of claim 1 , wherein the coding standard is a software coding standard.
| 0.876437 |
9,361,401 | 6 | 8 |
6. A non-transitory machine-readable medium storing instructions for relevance map linking executable by a computer to cause the computer to: identify a first node in a relevance map that is associated with a user; receive a user issued edit operation from the user adjusting a weight that is associated with a link between a user node that represents the user and the first node wherein the weight reflects a relevance of the first node to the user; adjust the weight that is associated with the link between the user node and the first node by implementing the user issued edit operation; adjust a number of other weights that are associated with a number of other links between a number of other nodes and the user node based on an adjusted weight of the link between the user node and the first node and based on a number of different relevance maps of the first node and the number of other nodes, wherein: the weight and the number of other weights are numerical values that define a relevance of the first node and the number of other nodes to the user node; a different relevance map from the number of different relevance maps is association with the first node and each of the number of other nodes; and each of the different relevance maps defines the relevance of the number of other nodes to a different particular one of the number of other nodes; and save a state of the relevance map after the weight has been adjusted and the number of other weights have been adjusted by associating the user issued edit operation with the saved state of the relevance map.
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6. A non-transitory machine-readable medium storing instructions for relevance map linking executable by a computer to cause the computer to: identify a first node in a relevance map that is associated with a user; receive a user issued edit operation from the user adjusting a weight that is associated with a link between a user node that represents the user and the first node wherein the weight reflects a relevance of the first node to the user; adjust the weight that is associated with the link between the user node and the first node by implementing the user issued edit operation; adjust a number of other weights that are associated with a number of other links between a number of other nodes and the user node based on an adjusted weight of the link between the user node and the first node and based on a number of different relevance maps of the first node and the number of other nodes, wherein: the weight and the number of other weights are numerical values that define a relevance of the first node and the number of other nodes to the user node; a different relevance map from the number of different relevance maps is association with the first node and each of the number of other nodes; and each of the different relevance maps defines the relevance of the number of other nodes to a different particular one of the number of other nodes; and save a state of the relevance map after the weight has been adjusted and the number of other weights have been adjusted by associating the user issued edit operation with the saved state of the relevance map. 8. The medium of claim 6 , wherein the instructions executable to adjust the weight that is associated with the link between the user node and the first node by implementing the user issued edit operation include instructions executable to increase the value of the weight or decrease the value of the weight to reflect a correlation between the user node and the first node.
| 0.5 |
9,940,476 | 1 | 4 |
1. A method for selective exposure of document tags associated with a plurality of online search engine content based on a predetermined user criteria to facilitate selective exposure of documents by specifying additional qualifications on a search tag, the method comprising: adding, by a computing device, a content tag associated with the plurality of search engine content with a plurality of metadata, wherein the plurality of metadata includes a text and an access control, wherein the text comprises at least one of a phrase, a keyword, and a string, and wherein the access control is a group of users that is defined by a criteria comprising of at least one of a membership, a credential, an age group, and an authentication; accepting, by the computing device, key words and a user group id, wherein the user group id corresponds to the access control; searching, by the computing device, the plurality of online search engine content with key words; collecting, by the computing device, the searched plurality of online search engine content, wherein the key words match the content tag; removing, by the computing device, the collected plurality of online search engine content that is not associated with the user group id to create a filtered list; and returning, by the computing device, the filtered list.
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1. A method for selective exposure of document tags associated with a plurality of online search engine content based on a predetermined user criteria to facilitate selective exposure of documents by specifying additional qualifications on a search tag, the method comprising: adding, by a computing device, a content tag associated with the plurality of search engine content with a plurality of metadata, wherein the plurality of metadata includes a text and an access control, wherein the text comprises at least one of a phrase, a keyword, and a string, and wherein the access control is a group of users that is defined by a criteria comprising of at least one of a membership, a credential, an age group, and an authentication; accepting, by the computing device, key words and a user group id, wherein the user group id corresponds to the access control; searching, by the computing device, the plurality of online search engine content with key words; collecting, by the computing device, the searched plurality of online search engine content, wherein the key words match the content tag; removing, by the computing device, the collected plurality of online search engine content that is not associated with the user group id to create a filtered list; and returning, by the computing device, the filtered list. 4. The method of claim 1 , further comprising: receiving, by the computing device, the returned filtered list by an application programming interface (API), wherein the receiving is based on an input string; and pushing, by the computing device, the returned filtered list by the application programming interface (API).
| 0.5 |
8,112,708 | 13 | 16 |
13. A method of populating a predictive text dictionary, comprising: a server detecting a location of a handheld electronic device operable to allow a user to enter text, said handheld electronic device having a predictive text dictionary and being operable to repeatedly receive and place words in said predictive text dictionary; the server providing said handheld electronic device with a set of words specific to said location of said handheld electronic device for placement in said predictive text dictionary.
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13. A method of populating a predictive text dictionary, comprising: a server detecting a location of a handheld electronic device operable to allow a user to enter text, said handheld electronic device having a predictive text dictionary and being operable to repeatedly receive and place words in said predictive text dictionary; the server providing said handheld electronic device with a set of words specific to said location of said handheld electronic device for placement in said predictive text dictionary. 16. A method of populating a predictive text dictionary according to claim 13 , wherein said handheld electronic device is capable of cellular communications and said detecting is comprised of: determining said location of said handheld electronic device based on cellular triangulation.
| 0.5 |
8,879,697 | 1 | 21 |
1. A method comprising: receiving a call from a caller; establishing from the call an identity of the caller; retrieving a social network context associated with the identity of the caller; identifying a topic of the call; retrieving customer relationship information pertaining to a previous interaction with the caller; determining an importance score for the call by assigning respective weights to the social network context, the topic, and the customer relationship information, a proportional distribution of the respective weights being based on one of resource availability, a call type, or a call time; and providing a level of customer service to the caller based on the importance score.
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1. A method comprising: receiving a call from a caller; establishing from the call an identity of the caller; retrieving a social network context associated with the identity of the caller; identifying a topic of the call; retrieving customer relationship information pertaining to a previous interaction with the caller; determining an importance score for the call by assigning respective weights to the social network context, the topic, and the customer relationship information, a proportional distribution of the respective weights being based on one of resource availability, a call type, or a call time; and providing a level of customer service to the caller based on the importance score. 21. The method of claim 1 , wherein the level of customer service relates to an amount of customer service resources to be used to assist the caller.
| 0.665919 |
10,061,985 | 1 | 5 |
1. A method comprising: by one or more computing devices, accessing a first feature vector representing a video-content object corresponding to a node in a social graph of a social-networking system, wherein: the video-content object comprises frames and audio and is associated with text; the first feature vector is based on one or more of the frames of the video-content object; and the social graph comprises a plurality of nodes and edges connecting the nodes; by one or more computing devices, accessing a second feature vector representing the video-content object, wherein the second feature vector is based on at least some of the text; by one or more computing devices, accessing a third feature vector representing the video-content object, wherein the third feature vector is based on one or more portions of the audio; by one or more computing devices, determining a fourth feature vector representing the video-content object, wherein the fourth feature vector is based on a combination of the first, second, and third feature vectors; and by one or more computing devices, determining a context of the video-content object based on the fourth feature vector and social-graph information based at least in part on one or more nodes or edges connected to the node corresponding to the video-content object.
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1. A method comprising: by one or more computing devices, accessing a first feature vector representing a video-content object corresponding to a node in a social graph of a social-networking system, wherein: the video-content object comprises frames and audio and is associated with text; the first feature vector is based on one or more of the frames of the video-content object; and the social graph comprises a plurality of nodes and edges connecting the nodes; by one or more computing devices, accessing a second feature vector representing the video-content object, wherein the second feature vector is based on at least some of the text; by one or more computing devices, accessing a third feature vector representing the video-content object, wherein the third feature vector is based on one or more portions of the audio; by one or more computing devices, determining a fourth feature vector representing the video-content object, wherein the fourth feature vector is based on a combination of the first, second, and third feature vectors; and by one or more computing devices, determining a context of the video-content object based on the fourth feature vector and social-graph information based at least in part on one or more nodes or edges connected to the node corresponding to the video-content object. 5. The method of claim 1 , further comprising, by one or more computing devices, removing a second video-content object based on determining that the video-content object and the second video-content object are similar based on the feature vector for the video-content object and a feature vector for the second video-content object, wherein determining the context of the video-content object comprises determining that the video-content object is inappropriate.
| 0.74973 |
10,140,370 | 1 | 3 |
1. A computer-implemented method for maintaining encrypted search indexes on third party storage systems, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying, as part of a plugin of a search engine, a dynamic search index used by the search engine, wherein: the dynamic search index comprises a plurality of data chunks; each of the plurality of data chunks comprises one or more data blocks; each of the plurality of data chunks has been encrypted using a unique nonce; and a search-index initialization vector is designated and stored for encrypting the dynamic search index; and enabling a single data chunk in the plurality of data chunks to be accessed by decrypting, as part of the plugin of the search engine, the single data chunk by: calculating a chunk initialization vector for decrypting the single data chunk by: identifying the unique nonce used to encrypt the single data chunk; and deriving the chunk initialization vector by summing the search-index initialization vector with a product of the unique nonce and a number of the one or more data blocks; and using the chunk initialization vector to decrypt the single data chunk; and reencrypting, as part of the plugin of the search engine after the single data chunk has been accessed, the single data chunk by: calculating a new chunk initialization vector for encrypting the single data chunk such that no two data chunks in the plurality of data chunks have identical initialization vectors by: calculating a new unique nonce for the single data chunk; and deriving the new chunk initialization vector by summing the search-index initialization vector with a product of the new unique nonce and the number of the one or more data blocks; and using the new chunk initialization vector to encrypt the single data chunk.
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1. A computer-implemented method for maintaining encrypted search indexes on third party storage systems, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying, as part of a plugin of a search engine, a dynamic search index used by the search engine, wherein: the dynamic search index comprises a plurality of data chunks; each of the plurality of data chunks comprises one or more data blocks; each of the plurality of data chunks has been encrypted using a unique nonce; and a search-index initialization vector is designated and stored for encrypting the dynamic search index; and enabling a single data chunk in the plurality of data chunks to be accessed by decrypting, as part of the plugin of the search engine, the single data chunk by: calculating a chunk initialization vector for decrypting the single data chunk by: identifying the unique nonce used to encrypt the single data chunk; and deriving the chunk initialization vector by summing the search-index initialization vector with a product of the unique nonce and a number of the one or more data blocks; and using the chunk initialization vector to decrypt the single data chunk; and reencrypting, as part of the plugin of the search engine after the single data chunk has been accessed, the single data chunk by: calculating a new chunk initialization vector for encrypting the single data chunk such that no two data chunks in the plurality of data chunks have identical initialization vectors by: calculating a new unique nonce for the single data chunk; and deriving the new chunk initialization vector by summing the search-index initialization vector with a product of the new unique nonce and the number of the one or more data blocks; and using the new chunk initialization vector to encrypt the single data chunk. 3. The method of claim 1 , wherein a size of each of the one or more data blocks of each of the plurality of data chunks is equal to a size of a block of data that is encrypted by a block cipher in a single operation.
| 0.640728 |
9,924,306 | 1 | 8 |
1. A computer-implemented method performed by one or more processors, comprising: automatically determining, based on the one or more processors inferring usage behaviors by a plurality of users with respect to a computer-implemented system, a mutual interest in establishing contact between a first user and a second user of the plurality of users; based on the determined mutual interest, generating a first recommendation, comprising a representation of the second user, for delivery to the first user; based on the determined mutual interest, generating a second recommendation, comprising a representation of the first user, for delivery to the second user; determining a first expression of interest in the second user based on one or more behaviors exhibited by the first user in response to receiving the first recommendation; determining a second expression of interest in the first user based on one or more behaviors exhibited by the second user in response to receiving the second recommendation; determining a bilateral expression of interest between the first user and the second user based on the first expression of interest and the second expression of interest; and revealing to the first user and the second user the bilateral expression of interest.
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1. A computer-implemented method performed by one or more processors, comprising: automatically determining, based on the one or more processors inferring usage behaviors by a plurality of users with respect to a computer-implemented system, a mutual interest in establishing contact between a first user and a second user of the plurality of users; based on the determined mutual interest, generating a first recommendation, comprising a representation of the second user, for delivery to the first user; based on the determined mutual interest, generating a second recommendation, comprising a representation of the first user, for delivery to the second user; determining a first expression of interest in the second user based on one or more behaviors exhibited by the first user in response to receiving the first recommendation; determining a second expression of interest in the first user based on one or more behaviors exhibited by the second user in response to receiving the second recommendation; determining a bilateral expression of interest between the first user and the second user based on the first expression of interest and the second expression of interest; and revealing to the first user and the second user the bilateral expression of interest. 8. The method of claim 1 , further comprising: providing a contact feature to enable the first user to contact the second user.
| 0.777193 |
7,634,398 | 21 | 23 |
21. A computer-readable storage medium having encoded thereon computer-executable instructions that when executed by a processor cause the processor to perform steps comprising: generating an initial parse tree for a text segment; identifying a target node and a reattach node in the initial parse tree, wherein the reattach node is not combined with the target node by a rule to form another node in the initial parse tree but is combined with an initial node in the initial parse tree; identifying a reattachment rule for attaching the reattach node to the target node; deconstructing the initial parse tree to form an ordered list of nodes and rules wherein the ordered list of nodes and rules includes at least one node that is not affected by attaching the reattach node to the target node instead of the initial node; adding the reattachment rule to the ordered list of nodes and rules in a position that will cause the reattachment rule to attach the reattach node to the target node when executed; and executing the reattachment rule based on its position in the ordered list of nodes and rules to form a node in a reconstructed parse tree such that the reattach node is attached to the target node by the node formed by the reattachment rule and is not attached to the initial node wherein executing the reattachment rule comprises: sequentially retrieving entries from the ordered list based on the order of the entries in the ordered list; for each node retrieved from the ordered list, placing the node in a working stack; and for each rule retrieved from the ordered list, including the reattachment rule: determining a number of nodes required by the rule; removing the determined number of nodes from the top of the working stack; executing the rule using the nodes removed from the working stack to form a resulting node for the reconstructed parse structure; and placing the resulting node at the top of the working stack.
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21. A computer-readable storage medium having encoded thereon computer-executable instructions that when executed by a processor cause the processor to perform steps comprising: generating an initial parse tree for a text segment; identifying a target node and a reattach node in the initial parse tree, wherein the reattach node is not combined with the target node by a rule to form another node in the initial parse tree but is combined with an initial node in the initial parse tree; identifying a reattachment rule for attaching the reattach node to the target node; deconstructing the initial parse tree to form an ordered list of nodes and rules wherein the ordered list of nodes and rules includes at least one node that is not affected by attaching the reattach node to the target node instead of the initial node; adding the reattachment rule to the ordered list of nodes and rules in a position that will cause the reattachment rule to attach the reattach node to the target node when executed; and executing the reattachment rule based on its position in the ordered list of nodes and rules to form a node in a reconstructed parse tree such that the reattach node is attached to the target node by the node formed by the reattachment rule and is not attached to the initial node wherein executing the reattachment rule comprises: sequentially retrieving entries from the ordered list based on the order of the entries in the ordered list; for each node retrieved from the ordered list, placing the node in a working stack; and for each rule retrieved from the ordered list, including the reattachment rule: determining a number of nodes required by the rule; removing the determined number of nodes from the top of the working stack; executing the rule using the nodes removed from the working stack to form a resulting node for the reconstructed parse structure; and placing the resulting node at the top of the working stack. 23. The computer-readable storage medium of claim 21 wherein the reattach node is not found in any structure beneath the target node in the initial parse tree.
| 0.592308 |
4,439,161 | 7 | 8 |
7. The learning aid according to claim 6 wherein said means for communicating to the operator said first response data includes voice synthesis means.
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7. The learning aid according to claim 6 wherein said means for communicating to the operator said first response data includes voice synthesis means. 8. The learning aid according to claim 7 wherein said operator interface means includes means to communicate to the operator said randomly chosen incorrect response data in a human language via said voice synthesis means.
| 0.5 |
9,203,623 | 1 | 3 |
1. An apparatus configured to match a list of keywords against a target document, the apparatus comprising: data storage configured to store computer-readable instruction code and data; a processor configured to access the data storage and to execute said computer-readable instruction code; a keyword searcher implemented using the instruction code and configured to receive the list of keywords and a textual string corresponding to the target document file, and search the textual string for instances of the keywords so as to generate a sequence of keyword instances; a keyword object generator implemented using the instruction code and configured to receive the sequence of keyword instances, and generate a keyword object, wherein the keyword object includes a range-dependent match function.
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1. An apparatus configured to match a list of keywords against a target document, the apparatus comprising: data storage configured to store computer-readable instruction code and data; a processor configured to access the data storage and to execute said computer-readable instruction code; a keyword searcher implemented using the instruction code and configured to receive the list of keywords and a textual string corresponding to the target document file, and search the textual string for instances of the keywords so as to generate a sequence of keyword instances; a keyword object generator implemented using the instruction code and configured to receive the sequence of keyword instances, and generate a keyword object, wherein the keyword object includes a range-dependent match function. 3. The apparatus of claim 1 , wherein the range-dependent-match function is configured to return an ordered sequence of offset values for the identified keywords if match conditions are met.
| 0.5 |
8,533,224 | 7 | 12 |
7. A computer-implemented system comprising: one or more computers; and one or more data storage devices coupled to the one or more computers, storing: a training data repository that includes a set of retained data samples, wherein the set of retained data samples includes at least some data samples from an initial training data set and some data samples from a plurality of previously received update data sets, wherein each data sample includes input data and corresponding output data; a predictive model repository that includes trained predictive models that were each trained with the initial training data set, wherein at least some of the trained predictive models are updateable and were each retrained with the plurality of previously received update data sets, and instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a first data set of data samples, each data sample comprising input data and corresponding output data, wherein the first data set is new relative to (i) the initial training data set and (ii) the plurality of previously received update data sets; assigning a richness score to each of the data samples included in the first data set and to each of the set of retained data samples included in the training data repository, wherein the richness score for a particular data sample indicates how information rich the particular data sample is, relative to other data samples in the set of retained data samples and the first data set, for determining an accuracy of a trained predictive model; ranking the data samples included in the first data set and the retained data samples based on the assigned richness scores; selecting a first set of test data from the data samples included in the first data set and the set of retained data samples based on the ranking; testing how accurate each of the trained predictive models in the repository is in determining predictive output data for given input data using the first set of test data and determining respective accuracy scores for each of the trained predictive models based on the testing; and selecting a first trained predictive model from the repository based on the accuracy scores and providing access to the first trained predictive model to a client computing system for generating predictive output data based on input data received from the client computing system.
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7. A computer-implemented system comprising: one or more computers; and one or more data storage devices coupled to the one or more computers, storing: a training data repository that includes a set of retained data samples, wherein the set of retained data samples includes at least some data samples from an initial training data set and some data samples from a plurality of previously received update data sets, wherein each data sample includes input data and corresponding output data; a predictive model repository that includes trained predictive models that were each trained with the initial training data set, wherein at least some of the trained predictive models are updateable and were each retrained with the plurality of previously received update data sets, and instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a first data set of data samples, each data sample comprising input data and corresponding output data, wherein the first data set is new relative to (i) the initial training data set and (ii) the plurality of previously received update data sets; assigning a richness score to each of the data samples included in the first data set and to each of the set of retained data samples included in the training data repository, wherein the richness score for a particular data sample indicates how information rich the particular data sample is, relative to other data samples in the set of retained data samples and the first data set, for determining an accuracy of a trained predictive model; ranking the data samples included in the first data set and the retained data samples based on the assigned richness scores; selecting a first set of test data from the data samples included in the first data set and the set of retained data samples based on the ranking; testing how accurate each of the trained predictive models in the repository is in determining predictive output data for given input data using the first set of test data and determining respective accuracy scores for each of the trained predictive models based on the testing; and selecting a first trained predictive model from the repository based on the accuracy scores and providing access to the first trained predictive model to a client computing system for generating predictive output data based on input data received from the client computing system. 12. The system of claim 7 , further comprising: after determining the accuracy score for the trained predictive model, retraining the trained predictive model using the first data set of data samples.
| 0.830221 |
8,705,707 | 1 | 6 |
1. A method performed by at least one processor of a communication device, the method comprising: determining, by the communication device, that a call has been answered, missed, or terminated by the communication device; generating, at a graphical user interface associated with the communication device, an indication of the call being answered, missed, or terminated; responsive to determining that the call has been answered, missed, or terminated by the communication device, automatically: determining, by the communication device, one or more contextual identifiers associated with the call, wherein the one or more contextual identifiers are based on a geographic location of the communication device at a time of the call, and storing the one or more contextual identifiers in association with the indication of the call in at least one data structure that includes other contextual identifiers associated with other indications of other calls, wherein the one or more contextual identifiers and the other contextual identifiers included in the at least one data structure are searchable; and determining that the one or more contextual identifiers satisfy a search query based at least in part on a second input received at the graphical user interface, wherein the one or more contextual identifiers and the indication of the call are determined in response to the search query.
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1. A method performed by at least one processor of a communication device, the method comprising: determining, by the communication device, that a call has been answered, missed, or terminated by the communication device; generating, at a graphical user interface associated with the communication device, an indication of the call being answered, missed, or terminated; responsive to determining that the call has been answered, missed, or terminated by the communication device, automatically: determining, by the communication device, one or more contextual identifiers associated with the call, wherein the one or more contextual identifiers are based on a geographic location of the communication device at a time of the call, and storing the one or more contextual identifiers in association with the indication of the call in at least one data structure that includes other contextual identifiers associated with other indications of other calls, wherein the one or more contextual identifiers and the other contextual identifiers included in the at least one data structure are searchable; and determining that the one or more contextual identifiers satisfy a search query based at least in part on a second input received at the graphical user interface, wherein the one or more contextual identifiers and the indication of the call are determined in response to the search query. 6. The method of claim 1 , wherein at least one contextual identifier in the at least one data structure is further based on at least one of motion data, video data, and audio data.
| 0.844768 |
8,160,901 | 5 | 6 |
5. A method of identification of a possible personalized intervention for a patient experiencing at least one side effect associated with a present intervention, the method comprising: providing a database communicatively coupled with a server computer, the database containing patient information for a plurality of patients including one or more attributes for each patient in the database; providing a graphical user interface on a client computer, the graphical user interface allowing a patient to formulate a request specifying one or more attributes of the patient including: one or more diseases currently affecting the patient; one or more interventions currently employed by patient; and one or more side effects currently experienced by the patient; searching the database of patient information for a set of other patients that previoulsy experienced at least one of the specified side effects when employing at least one of the specified interventions; for each of the other patients in the set of other patients that previously experienced at least one of the specified side effects when employing the at least one of the specified interventions, identifying an alternative intervention that was employed most-recently by that other patient; and returning a set of the one or more alternative interventions that were most-commonly employed most-recently by the set of other patients that experienced the one or more specified side effects when employing the one or more specified interventions; wherein the intervention is selected from the group consisting of: administration of a medication, administration of a remedy, administration of a nutritional supplement, administration of a vitamin, exercise, physical therapy, message, stretching, consumuption of food, rest, sleep, and a modification of any of the foregoing.
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5. A method of identification of a possible personalized intervention for a patient experiencing at least one side effect associated with a present intervention, the method comprising: providing a database communicatively coupled with a server computer, the database containing patient information for a plurality of patients including one or more attributes for each patient in the database; providing a graphical user interface on a client computer, the graphical user interface allowing a patient to formulate a request specifying one or more attributes of the patient including: one or more diseases currently affecting the patient; one or more interventions currently employed by patient; and one or more side effects currently experienced by the patient; searching the database of patient information for a set of other patients that previoulsy experienced at least one of the specified side effects when employing at least one of the specified interventions; for each of the other patients in the set of other patients that previously experienced at least one of the specified side effects when employing the at least one of the specified interventions, identifying an alternative intervention that was employed most-recently by that other patient; and returning a set of the one or more alternative interventions that were most-commonly employed most-recently by the set of other patients that experienced the one or more specified side effects when employing the one or more specified interventions; wherein the intervention is selected from the group consisting of: administration of a medication, administration of a remedy, administration of a nutritional supplement, administration of a vitamin, exercise, physical therapy, message, stretching, consumuption of food, rest, sleep, and a modification of any of the foregoing. 6. The method of claim 5 , wherein the one or more attributes includes at least one selected from the group consisting of: age, race, ethnicity, gender, height, weight, body mass index (BMI), body volume index (BVI), genotype, phenotype, disease, disease severity, disease progression rate, measures of functional ability, quality of life, interventions, and remedies.
| 0.66787 |
9,275,037 | 1 | 4 |
1. A method for managing textual content of phrases, the method comprising the steps of: determining, by one or more processors, if a phrase is entered into a first field in a display, wherein the phrase contains textual content; determining, by one or more processors, a user name associated with the phrase entered into the first field of the display; querying, by one or more processors, a directory for information associated with the determined user name, wherein the information includes at least a list of titles and associated responsibilities of the determined user name; determining, by one or more processors, if a portion of the textual content of the phrase is present in a phrase dictionary, wherein the phrase dictionary contains textual content of one or more topics; and responsive to determining that the portion of the textual content of the phrase is not present in the phrase dictionary, determining, by or more processors, to not enter the portion of the textual content of the phrase in a second field of the display.
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1. A method for managing textual content of phrases, the method comprising the steps of: determining, by one or more processors, if a phrase is entered into a first field in a display, wherein the phrase contains textual content; determining, by one or more processors, a user name associated with the phrase entered into the first field of the display; querying, by one or more processors, a directory for information associated with the determined user name, wherein the information includes at least a list of titles and associated responsibilities of the determined user name; determining, by one or more processors, if a portion of the textual content of the phrase is present in a phrase dictionary, wherein the phrase dictionary contains textual content of one or more topics; and responsive to determining that the portion of the textual content of the phrase is not present in the phrase dictionary, determining, by or more processors, to not enter the portion of the textual content of the phrase in a second field of the display. 4. The method of claim 1 , further comprising the step of: responsive to determining, another portion of the textual content of the phrase present in the phrase dictionary does exceed a threshold, wherein the threshold is a total number of words, entering, by one or more processors, the other portion of the textual content of the phrase in the second field of the display.
| 0.5 |
9,547,423 | 1 | 9 |
1. A method comprising: storing in a memory an executable graphical model including a plurality of components including hierarchically arranged child components disposed within parent components, the child components configured to send and receive messages during execution of the graphical model in an order, the messages persist for determined time intervals between a model execution start time and a model execution end time, and have payloads that remain fixed for a given send-receive interaction; identifying, by a processor coupled to the memory: the child components configured to send and receive messages, and the determined time intervals of the messages; automatically generating, by the processor, a message view window for the graphical model, the message view window including: an execution time scale corresponding to a time of execution of the graphical model, parent lifelines corresponding to the parent components, the parent lifelines extending across the execution time scale, and a plurality of first graphical affordances associated with the parent lifelines, the plurality of first graphical affordances representing the messages, the plurality of first graphical affordances arranged in the order of the messages; and expanding a given parent lifeline corresponding to a given parent component of the executable graphical model to show child lifelines corresponding to at least two of the child components of the given parent component.
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1. A method comprising: storing in a memory an executable graphical model including a plurality of components including hierarchically arranged child components disposed within parent components, the child components configured to send and receive messages during execution of the graphical model in an order, the messages persist for determined time intervals between a model execution start time and a model execution end time, and have payloads that remain fixed for a given send-receive interaction; identifying, by a processor coupled to the memory: the child components configured to send and receive messages, and the determined time intervals of the messages; automatically generating, by the processor, a message view window for the graphical model, the message view window including: an execution time scale corresponding to a time of execution of the graphical model, parent lifelines corresponding to the parent components, the parent lifelines extending across the execution time scale, and a plurality of first graphical affordances associated with the parent lifelines, the plurality of first graphical affordances representing the messages, the plurality of first graphical affordances arranged in the order of the messages; and expanding a given parent lifeline corresponding to a given parent component of the executable graphical model to show child lifelines corresponding to at least two of the child components of the given parent component. 9. The method of claim 1 wherein the time scale is organized into a plurality of time bands that correspond to time periods between the execution start time and the execution end time, the method further comprising: receiving a designation of a given one of the plurality of time bands; and in response to the receiving, providing finer execution time granularity within the given one of the plurality of time bands.
| 0.5 |
7,840,546 | 7 | 8 |
7. A method for optimizing data queries for related records in a reliable fashion, to be used with a system having a first computing device communicatively coupled with a second and a third computing device, and communicatively coupled to a first database that stores real-world entity data, having said second computing device communicatively coupled with said first and said third computing device, and communicatively coupled to a second database that stores real-world entity data, having said third computing device communicatively coupled with said first and said second computing device, and communicatively coupled to a third database that stores real-world entity data, comprising the steps of: creating a hierarchical system of Consolidation Strings for said first database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said database, wherein the information represented in each Consolidation String is represented in a character format, and wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty; creating a hierarchical system of Consolidation Strings for said second database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said database, wherein the information represented in each Consolidation String is represented in a character format, and wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty; creating a hierarchical system of Consolidation Strings for said third database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said database, wherein the information represented in each Consolidation String is represented in a character format, and wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty; providing the capability of said first computing device to query said first database and cause said first database to also query said second and third databases, wherein an entity-record match between said first and second databases will be found and said matching entity records are consolidated from an end-user's point of view, if a pair of entity records have Consolidation Strings on the same priority level that are character-wise identical, and wherein an entity-record match between said first and third databases will be found and said matching entity records are consolidated from an end-user's point of view, if a pair of entity records have Consolidation Strings on the same priority level that are character-wise identical; providing the capability of said second computing device to query said second database and cause said second database to also query said first and third databases, wherein an entity-record match between said second and first databases will be found and said matching entity records are consolidated from an end-user's point of view, if a pair of entity records have Consolidation Strings on the same priority level that are character-wise identical, and wherein an entity-record match between said second and third databases will be found and said matching entity records are consolidated from an end-user's point of view, if a pair of entity records have Consolidation Strings on the same priority level that are character-wise identical; and providing the capability of said third computing device to query said third database and cause said third database to also query said first and second databases, wherein an entity-record match between said third and first databases will be found and said matching entity records are consolidated from an end-user's point of view, if a pair of entity records have Consolidation Strings on the same priority level that are character-wise identical, and wherein an entity-record match between said third and second databases will be found and said matching entity records are consolidated from an end-user's point of view, if a pair of entity records have Consolidation Strings on the same priority level that are character-wise identical.
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7. A method for optimizing data queries for related records in a reliable fashion, to be used with a system having a first computing device communicatively coupled with a second and a third computing device, and communicatively coupled to a first database that stores real-world entity data, having said second computing device communicatively coupled with said first and said third computing device, and communicatively coupled to a second database that stores real-world entity data, having said third computing device communicatively coupled with said first and said second computing device, and communicatively coupled to a third database that stores real-world entity data, comprising the steps of: creating a hierarchical system of Consolidation Strings for said first database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said database, wherein the information represented in each Consolidation String is represented in a character format, and wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty; creating a hierarchical system of Consolidation Strings for said second database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said database, wherein the information represented in each Consolidation String is represented in a character format, and wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty; creating a hierarchical system of Consolidation Strings for said third database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said database, wherein the information represented in each Consolidation String is represented in a character format, and wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty; providing the capability of said first computing device to query said first database and cause said first database to also query said second and third databases, wherein an entity-record match between said first and second databases will be found and said matching entity records are consolidated from an end-user's point of view, if a pair of entity records have Consolidation Strings on the same priority level that are character-wise identical, and wherein an entity-record match between said first and third databases will be found and said matching entity records are consolidated from an end-user's point of view, if a pair of entity records have Consolidation Strings on the same priority level that are character-wise identical; providing the capability of said second computing device to query said second database and cause said second database to also query said first and third databases, wherein an entity-record match between said second and first databases will be found and said matching entity records are consolidated from an end-user's point of view, if a pair of entity records have Consolidation Strings on the same priority level that are character-wise identical, and wherein an entity-record match between said second and third databases will be found and said matching entity records are consolidated from an end-user's point of view, if a pair of entity records have Consolidation Strings on the same priority level that are character-wise identical; and providing the capability of said third computing device to query said third database and cause said third database to also query said first and second databases, wherein an entity-record match between said third and first databases will be found and said matching entity records are consolidated from an end-user's point of view, if a pair of entity records have Consolidation Strings on the same priority level that are character-wise identical, and wherein an entity-record match between said third and second databases will be found and said matching entity records are consolidated from an end-user's point of view, if a pair of entity records have Consolidation Strings on the same priority level that are character-wise identical. 8. The method of claim 7 , wherein: the highest-ranked Consolidation Strings are based on positive identifiers; the intermediate-ranked Consolidation Strings are based on demographic information; and the lowest-ranked Consolidation Strings are based on associative information that spans multiple-entity types.
| 0.5 |
9,436,438 | 15 | 16 |
15. The non-transitory computer-accessible memory medium of claim 1 , wherein the program instructions are further executable to: determine a configuration scope for the at least one functional block when the at least one functional block is connected; and configure the at least one functional block at runtime in accordance with the determined configuration scope; wherein said configuring determines values for IP and OP for the at least one functional block.
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15. The non-transitory computer-accessible memory medium of claim 1 , wherein the program instructions are further executable to: determine a configuration scope for the at least one functional block when the at least one functional block is connected; and configure the at least one functional block at runtime in accordance with the determined configuration scope; wherein said configuring determines values for IP and OP for the at least one functional block. 16. The non-transitory computer-accessible memory medium of claim 15 , wherein the program instructions are further executable to perform: automatically determining harnessing logic for the at least one functional block to ensure that runtime updates to the at least one functional block's configuration occur on iteration boundaries.
| 0.5 |
8,468,142 | 43 | 53 |
43. A system comprising: a memory comprising instructions executable by one or more processors; and one or more processors coupled to the memory and operable to execute the instructions, the one or more processors being operable when executing the instructions to: construct a plurality of first binary decision diagrams (BDDs), each of the first BDDs representing a different one of a plurality of words, each of the words having a unique word identifier (ID), each first BDD being constructed based on the word ID of the word represented by the first BDD; construct a plurality of second BDDs, each of the second BDDs representing a different one of a plurality of search queries, each of the search queries comprising one or more of the words, each second BDD being constructed by performing an AND operation on the first BDDs representing the words in the search query represented by the second BDD, wherein the plurality of search queries comprise a plurality of cached searched queries that have been previously submitted to a search engine; construct a plurality of third BDDs, each of the third BDDs representing a different one of a plurality of web pages, each of the web pages having a unique page ID, each of the third BDDs being constructed based on the page ID of the web page represented by the third BDD; construct a plurality of fourth BDDs, each of the fourth BDDs representing a different one of a plurality of search results generated in response to the search queries, each of the search results comprising one or more of the web pages, each fourth BDD being constructed by performing an OR operation on the third BDDs representing the web pages in the search result represented by the fourth BDD; construct a plurality of fifth BDDs, each of the fifth BDDs representing a different one of a plurality of search tuples, each of the search tuples comprising a different one of the search queries and a different one of the search results corresponding to the search query, each fifth BDD being constructed by performing an AND operation on the second BDD representing the search query and the fourth BDD representing the search result that the search tuple represented by the fifth BDD; and constructing a sixth BDD by performing an OR operation on the fifth BDDs, the sixth BDD representing the search queries and the search results.
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43. A system comprising: a memory comprising instructions executable by one or more processors; and one or more processors coupled to the memory and operable to execute the instructions, the one or more processors being operable when executing the instructions to: construct a plurality of first binary decision diagrams (BDDs), each of the first BDDs representing a different one of a plurality of words, each of the words having a unique word identifier (ID), each first BDD being constructed based on the word ID of the word represented by the first BDD; construct a plurality of second BDDs, each of the second BDDs representing a different one of a plurality of search queries, each of the search queries comprising one or more of the words, each second BDD being constructed by performing an AND operation on the first BDDs representing the words in the search query represented by the second BDD, wherein the plurality of search queries comprise a plurality of cached searched queries that have been previously submitted to a search engine; construct a plurality of third BDDs, each of the third BDDs representing a different one of a plurality of web pages, each of the web pages having a unique page ID, each of the third BDDs being constructed based on the page ID of the web page represented by the third BDD; construct a plurality of fourth BDDs, each of the fourth BDDs representing a different one of a plurality of search results generated in response to the search queries, each of the search results comprising one or more of the web pages, each fourth BDD being constructed by performing an OR operation on the third BDDs representing the web pages in the search result represented by the fourth BDD; construct a plurality of fifth BDDs, each of the fifth BDDs representing a different one of a plurality of search tuples, each of the search tuples comprising a different one of the search queries and a different one of the search results corresponding to the search query, each fifth BDD being constructed by performing an AND operation on the second BDD representing the search query and the fourth BDD representing the search result that the search tuple represented by the fifth BDD; and constructing a sixth BDD by performing an OR operation on the fifth BDDs, the sixth BDD representing the search queries and the search results. 53. The system of claim 43 , wherein the one or more processors are further operable, when executing the instructions, to partition the sixth BDD into a plurality of seventh BDDs, wherein a sum of sizes of the seventh BDDs is less than a size of the sixth BDD.
| 0.747573 |
8,001,195 | 1 | 8 |
1. A method for identifying spam in an email, the method comprising: (a) normalizing an email text morphologically and identifying unique words in the email text; (b) filtering words from the email text, including filtering multi-symbol meaningless human-language words and noise human-language words; (c) determining a number of occurrences of each unique word in the email text; (d) creating a unique numerical identifier for each unique word, the identifier being based on a numerical value corresponding to the unique word; (e) assigning an unique numerical identifier to each unique word in the email text; (f) generating a lexical vector of the email text as a plurality of the assigned identifiers and a frequency of occurrence of each corresponding unique word in the email text; (g) generating a histogram of the lexical vector for each unique numerical identifier of each corresponding unique word in the email text; (h) performing only a single comparison of the histogram of the lexical vector to histograms of lexical vectors of known spam texts; and (i) determining if the email text is spam based on a result of comparison of the histograms.
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1. A method for identifying spam in an email, the method comprising: (a) normalizing an email text morphologically and identifying unique words in the email text; (b) filtering words from the email text, including filtering multi-symbol meaningless human-language words and noise human-language words; (c) determining a number of occurrences of each unique word in the email text; (d) creating a unique numerical identifier for each unique word, the identifier being based on a numerical value corresponding to the unique word; (e) assigning an unique numerical identifier to each unique word in the email text; (f) generating a lexical vector of the email text as a plurality of the assigned identifiers and a frequency of occurrence of each corresponding unique word in the email text; (g) generating a histogram of the lexical vector for each unique numerical identifier of each corresponding unique word in the email text; (h) performing only a single comparison of the histogram of the lexical vector to histograms of lexical vectors of known spam texts; and (i) determining if the email text is spam based on a result of comparison of the histograms. 8. The method of claim 1 , wherein the lexical vectors of the known spam texts are stored in a lexical vector database.
| 0.699495 |
8,837,906 | 1 | 10 |
1. A video tagging method based on an incident report and an associated incident-specific dictionary, comprising: capturing keywords from the incident report related to an incident of interest at a first time period; creating an incident-specific dictionary for the incident of interest based on the captured keywords; capturing updated keywords at a second time period as the incident of interest unfolds; updating the incident-specific dictionary with the updated keywords; providing the updated incident-specific dictionary to at least one video camera capturing video based on a plurality of factors or providing the updated incident-specific dictionary to a back-end server communicatively coupled to the at least one video camera; and utilizing the keywords and updated keywords from the incident report by the at least one video camera to tag captured video.
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1. A video tagging method based on an incident report and an associated incident-specific dictionary, comprising: capturing keywords from the incident report related to an incident of interest at a first time period; creating an incident-specific dictionary for the incident of interest based on the captured keywords; capturing updated keywords at a second time period as the incident of interest unfolds; updating the incident-specific dictionary with the updated keywords; providing the updated incident-specific dictionary to at least one video camera capturing video based on a plurality of factors or providing the updated incident-specific dictionary to a back-end server communicatively coupled to the at least one video camera; and utilizing the keywords and updated keywords from the incident report by the at least one video camera to tag captured video. 10. The video tagging method of claim 1 , wherein the at least one video camera comprises a surveillance camera and one of the plurality of factors comprises proximity to the incident of interest.
| 0.755 |
10,095,788 | 9 | 10 |
9. The one or more computer storage media of claim 8 , wherein identifying deeplinks for the web page based on the deeplink hierarchy comprises: comparing the search query with one or more keywords associated with each node in the deeplink hierarchy to identify a relevant node in the deeplink hierarchy; and identifying the deeplinks from the relevant node in the deeplink hierarchy.
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9. The one or more computer storage media of claim 8 , wherein identifying deeplinks for the web page based on the deeplink hierarchy comprises: comparing the search query with one or more keywords associated with each node in the deeplink hierarchy to identify a relevant node in the deeplink hierarchy; and identifying the deeplinks from the relevant node in the deeplink hierarchy. 10. The one or more computer storage media of claim 9 , wherein identifying the deeplinks from the relevant node in the deeplink hierarchy comprises ranking a plurality of deeplinks from the relevant node and selecting a subset of the plurality of deeplinks based on the ranking.
| 0.5 |
9,142,217 | 30 | 31 |
30. A system for facilitating streamed speech recognition and/or structured transcription among users having heterogeneous system protocols the system comprising: (a) at least one system transaction manager and at least one post processing manager, both using a uniform system protocol, wherein the transaction manager is i) adapted to receive a streamed speech information request from at least one user employing a first user legacy protocol, and flag the information request requiring post processing, and, ii) configured to route a requested response to one or more users employing a second user legacy protocol, the speech information request comprised of free form dictation of speech, including spoken text and commands, including spoken commands, wherein the requested response comprises a transcription of spoken text and the post processed information requested, and, wherein the post processing manager is configured to i) receive structured transcription from a speech recognition and/or transcription engine, ii) operate upon the transcribed speech, including spoken commands in accordance with the speech information request, and, iii) rout the requested response to a post processing application, if requested in the speech information request; (b) a user interface, including an application service adapter configured to provide bi-directional conversion between the first user legacy protocol and the uniform system protocol and between the second user legacy protocol and the uniform system protocol, and, capable of bi-directional communication with the system transaction manager and supporting dictation applications, including prompts to direct user dictation in response to user system protocol commands and system transaction manager commands, the user interface being in bi-directional communication with the system transaction manager; and (c) at least one speech recognition and/or transcription engine for constrained speech recognition, communicating with the system transaction manager, wherein the speech recognition and/or transcription engine is configured to receive the flagged speech information request containing spoken text and commands, including spoken commands from the system transaction manager, to generate a structured transcription in response to the speech information request and to route the response comprised of structured transcribed spoken text and transcribed spoken commands to the post processing manager.
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30. A system for facilitating streamed speech recognition and/or structured transcription among users having heterogeneous system protocols the system comprising: (a) at least one system transaction manager and at least one post processing manager, both using a uniform system protocol, wherein the transaction manager is i) adapted to receive a streamed speech information request from at least one user employing a first user legacy protocol, and flag the information request requiring post processing, and, ii) configured to route a requested response to one or more users employing a second user legacy protocol, the speech information request comprised of free form dictation of speech, including spoken text and commands, including spoken commands, wherein the requested response comprises a transcription of spoken text and the post processed information requested, and, wherein the post processing manager is configured to i) receive structured transcription from a speech recognition and/or transcription engine, ii) operate upon the transcribed speech, including spoken commands in accordance with the speech information request, and, iii) rout the requested response to a post processing application, if requested in the speech information request; (b) a user interface, including an application service adapter configured to provide bi-directional conversion between the first user legacy protocol and the uniform system protocol and between the second user legacy protocol and the uniform system protocol, and, capable of bi-directional communication with the system transaction manager and supporting dictation applications, including prompts to direct user dictation in response to user system protocol commands and system transaction manager commands, the user interface being in bi-directional communication with the system transaction manager; and (c) at least one speech recognition and/or transcription engine for constrained speech recognition, communicating with the system transaction manager, wherein the speech recognition and/or transcription engine is configured to receive the flagged speech information request containing spoken text and commands, including spoken commands from the system transaction manager, to generate a structured transcription in response to the speech information request and to route the response comprised of structured transcribed spoken text and transcribed spoken commands to the post processing manager. 31. The system of claim 30 wherein said first user legacy protocol is the same as or different than the second user legacy protocol.
| 0.897356 |
5,465,317 | 6 | 7 |
6. A speech recognition apparatus as claimed in claim 5, characterized in that the output means outputs an unrecognizable-sound indication signal if the best match score for the current sound is worse than the recognition threshold score for the current sound.
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6. A speech recognition apparatus as claimed in claim 5, characterized in that the output means outputs an unrecognizable-sound indication signal if the best match score for the current sound is worse than the recognition threshold score for the current sound. 7. A speech recognition apparatus as claimed in claim 6, characterized in that the output means displays an unrecognizable-sound indicator if the best match score for the current sound is worse than the recognition threshold score for the current sound.
| 0.5 |
8,914,376 | 24 | 26 |
24. A method according to claim 1 and also comprising: executing a plurality of learning iterations each characterized by precision and recall, only until a diminishing returns criterion is true, including: executing at least one learning iteration; computing the diminishing returns criterion; and subsequently executing at least one additional learning iteration only if the diminishing returns criterion is not true, wherein said diminishing returns criterion returns a true value if and only if a non-decreasing function of one of the precision and the recall is approaching a steady state, said non-decreasing function comprises an F-measure, and said diminishing returns criterion is computed by using a linear regression to compute a linear function estimating an F-measure obtained in previous iterations as a function of a log of a corresponding iteration number, generating a prediction of at least one F-measure at least one future iteration by finding a value along the linear function corresponding to a log of said future iteration, comparing said prediction to a currently known F-measure, and returning true if the prediction is close to said currently known F-measure to a predetermined degree.
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24. A method according to claim 1 and also comprising: executing a plurality of learning iterations each characterized by precision and recall, only until a diminishing returns criterion is true, including: executing at least one learning iteration; computing the diminishing returns criterion; and subsequently executing at least one additional learning iteration only if the diminishing returns criterion is not true, wherein said diminishing returns criterion returns a true value if and only if a non-decreasing function of one of the precision and the recall is approaching a steady state, said non-decreasing function comprises an F-measure, and said diminishing returns criterion is computed by using a linear regression to compute a linear function estimating an F-measure obtained in previous iterations as a function of a log of a corresponding iteration number, generating a prediction of at least one F-measure at least one future iteration by finding a value along the linear function corresponding to a log of said future iteration, comparing said prediction to a currently known F-measure, and returning true if the prediction is close to said currently known F-measure to a predetermined degree. 26. The method according to claim 24 wherein said F-measure comprises a most recent F-measure.
| 0.740331 |
7,487,095 | 1 | 45 |
1. A method comprising: receiving an arbitrary natural language communication from a user; applying a concept recognition process to automatically derive a representation of concepts embodied in the communication; using the concept representation to provide to a human agent information useful in responding to the natural language communication, wherein the information provided to the human agent includes a plurality of possible responses to the user's communication; enabling the human agent to select a response from the plurality of possible responses; and delivering the selected response to the user.
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1. A method comprising: receiving an arbitrary natural language communication from a user; applying a concept recognition process to automatically derive a representation of concepts embodied in the communication; using the concept representation to provide to a human agent information useful in responding to the natural language communication, wherein the information provided to the human agent includes a plurality of possible responses to the user's communication; enabling the human agent to select a response from the plurality of possible responses; and delivering the selected response to the user. 45. The method of claim 1 , wherein the selected response is delivered to the user in real time relative to the communication.
| 0.789298 |
9,239,657 | 1 | 2 |
1. A character input method comprising the steps of: displaying, when a user brings a mouse cursor into contact with a term input box of a web browser or website or clicks the term input box, a character input window in abutment with the term input box, the character input window comprising a first section that includes a plurality of character buttons and a second section that includes a completion button for enabling input of a signal indicative of completion of character entry; entering, when a character button of the plurality of character buttons is clicked, a character corresponding to the clicked character button into the term input box; generating, when the completion button is clicked, an activation signal that causes a search engine associated with the term input box to run is run using as search data the character entered into the term input box; making, when the user locates the mouse cursor on a portion of a screen outside the character input window, the character input window disappear and the portion of the screen outside the character input window remains visible; and displaying an extended term window that displays an extended term including the character entered in the term input box, wherein the extended term window is displayed in contact with a contour of the term input box or the character input window, wherein the character input window is displayed in contact with one side of the contour of the term input box, and the extended term window is displayed in contact with opposite side of the contour of the term input box.
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1. A character input method comprising the steps of: displaying, when a user brings a mouse cursor into contact with a term input box of a web browser or website or clicks the term input box, a character input window in abutment with the term input box, the character input window comprising a first section that includes a plurality of character buttons and a second section that includes a completion button for enabling input of a signal indicative of completion of character entry; entering, when a character button of the plurality of character buttons is clicked, a character corresponding to the clicked character button into the term input box; generating, when the completion button is clicked, an activation signal that causes a search engine associated with the term input box to run is run using as search data the character entered into the term input box; making, when the user locates the mouse cursor on a portion of a screen outside the character input window, the character input window disappear and the portion of the screen outside the character input window remains visible; and displaying an extended term window that displays an extended term including the character entered in the term input box, wherein the extended term window is displayed in contact with a contour of the term input box or the character input window, wherein the character input window is displayed in contact with one side of the contour of the term input box, and the extended term window is displayed in contact with opposite side of the contour of the term input box. 2. The character input method as set forth in claim 1 , wherein the second section, which includes the completion button, surrounds the first section, which includes the character buttons.
| 0.705329 |
7,613,687 | 1 | 22 |
1. An information gathering system implemented in a computer system for optimizing searching comprising: a processor and memory; a data extraction tool executing in the computer system, in communication with a database, extracting website content to enable full text searching, the website content being extracted from a plurality of websites associated with business entities that are classified according to a standard industry classification system (SIC), which is a predefined taxonomy of business activities having verified information about the business entities; the database, in communication with the data extraction tool, storing the extracted website content according to a classification system that is based on the predefined taxonomy of SIC business activities; a content analyzer, in communication with the database, identifying commonly occurring keywords in the extracted website content from the websites of business entities that are similarly classified in the SIC predefined taxonomy of SIC business activities, where the commonly occurring keywords identified are used to update the classification system, the updated classification system being used to optimize searching in response to search queries; the content analyzer identifying commonly occurring keywords that are used to create a new category to update the classification system by: identifying keyword matches in the extracted website content by identifying any commonly occurring keywords or phrases in the extracted website content; and processing the matches identified by determining whether any of the keywords or phrases in the identified matches contain one or more keywords associated with any of the business activities in the SIC predefined taxonomy; and a full text indexed search engine, in communication with the database, processing a search query by matching the search query against the database, where at least a portion of the search results are clustered based on their respective SIC business activity category.
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1. An information gathering system implemented in a computer system for optimizing searching comprising: a processor and memory; a data extraction tool executing in the computer system, in communication with a database, extracting website content to enable full text searching, the website content being extracted from a plurality of websites associated with business entities that are classified according to a standard industry classification system (SIC), which is a predefined taxonomy of business activities having verified information about the business entities; the database, in communication with the data extraction tool, storing the extracted website content according to a classification system that is based on the predefined taxonomy of SIC business activities; a content analyzer, in communication with the database, identifying commonly occurring keywords in the extracted website content from the websites of business entities that are similarly classified in the SIC predefined taxonomy of SIC business activities, where the commonly occurring keywords identified are used to update the classification system, the updated classification system being used to optimize searching in response to search queries; the content analyzer identifying commonly occurring keywords that are used to create a new category to update the classification system by: identifying keyword matches in the extracted website content by identifying any commonly occurring keywords or phrases in the extracted website content; and processing the matches identified by determining whether any of the keywords or phrases in the identified matches contain one or more keywords associated with any of the business activities in the SIC predefined taxonomy; and a full text indexed search engine, in communication with the database, processing a search query by matching the search query against the database, where at least a portion of the search results are clustered based on their respective SIC business activity category. 22. An information gathering system for optimizing searching as in claim 1 wherein the updated classification system is used by the full text indexed search engine to process queries for business entities.
| 0.824486 |
9,766,879 | 1 | 5 |
1. A method of providing supplemental functionalities to an executable program via an ontology instance, the method comprising: causing, by a computer system, an executable program to be run; obtaining, by a computer system, a general ontology and a domain-specific ontology, wherein the domain-specific ontology is associated with a domain of interest, and the executable program is configured to use at least a portion of the general ontology to interpret the domain-specific ontology; validating, by a computer system, the general ontology; obtaining, by a computer system, an instance of the general ontology, wherein the general ontology instance is based on the domain-specific ontology and corresponds to an application associated with the domain of interest; generating, by a computer system, based on the general ontology instance, supplemental information for the executable program, wherein the supplemental information is related to one or more functionalities of the application to be added to the executable program; and providing, by a computer system, the supplemental information as input to the executable program, wherein the supplemental information, at least in part, causes the one or more functionalities of the application to be made available via the executable program.
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1. A method of providing supplemental functionalities to an executable program via an ontology instance, the method comprising: causing, by a computer system, an executable program to be run; obtaining, by a computer system, a general ontology and a domain-specific ontology, wherein the domain-specific ontology is associated with a domain of interest, and the executable program is configured to use at least a portion of the general ontology to interpret the domain-specific ontology; validating, by a computer system, the general ontology; obtaining, by a computer system, an instance of the general ontology, wherein the general ontology instance is based on the domain-specific ontology and corresponds to an application associated with the domain of interest; generating, by a computer system, based on the general ontology instance, supplemental information for the executable program, wherein the supplemental information is related to one or more functionalities of the application to be added to the executable program; and providing, by a computer system, the supplemental information as input to the executable program, wherein the supplemental information, at least in part, causes the one or more functionalities of the application to be made available via the executable program. 5. The method of claim 1 , further comprising: assigning, by a computer system, a freeze to the general ontology and the domain-specific ontology that disables further modification to the general ontology and the domain-specific ontology.
| 0.895614 |
9,037,573 | 11 | 15 |
11. A computer system for personalizing a search of a document collection to a user, comprising: a processor; and memory storing instructions that, when executed by the processor, cause the computer system to: monitor a plurality of documents accessed by the user, identify a plurality of first phrases present in one or more of the accessed documents, receive a query from the user, the query including one or more second phrases, select a plurality of documents responsive to the query as a search result, identify one or more of the first phrases as related phrases that are related to the one or more second phrases, wherein a particular related phrase is related to a particular second phrase when an information gain exceeds a threshold, the information gain being a ratio of an actual co-occurrence rate of the particular related phrase and the particular second phrase in documents of the document collection and an expected occurrence rate of the particular related phrase and the particular second phrase in the documents, weight a plurality of scores, each score corresponding to a respective document in the plurality of documents responsive to the query, wherein the score of the respective document that includes the one or more related phrases is boosted, rank the plurality of documents responsive to the query for presentation to the user according to the weighted scores to provide personalized search results, and present the personalized search results to the user.
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11. A computer system for personalizing a search of a document collection to a user, comprising: a processor; and memory storing instructions that, when executed by the processor, cause the computer system to: monitor a plurality of documents accessed by the user, identify a plurality of first phrases present in one or more of the accessed documents, receive a query from the user, the query including one or more second phrases, select a plurality of documents responsive to the query as a search result, identify one or more of the first phrases as related phrases that are related to the one or more second phrases, wherein a particular related phrase is related to a particular second phrase when an information gain exceeds a threshold, the information gain being a ratio of an actual co-occurrence rate of the particular related phrase and the particular second phrase in documents of the document collection and an expected occurrence rate of the particular related phrase and the particular second phrase in the documents, weight a plurality of scores, each score corresponding to a respective document in the plurality of documents responsive to the query, wherein the score of the respective document that includes the one or more related phrases is boosted, rank the plurality of documents responsive to the query for presentation to the user according to the weighted scores to provide personalized search results, and present the personalized search results to the user. 15. The system of claim 11 , wherein identifying the one or more related phrases includes: for a particular second phrase of the one or more second phrases, accessing a related phrase bit vector for the particular second phrase, wherein each bit of the related phrase bit vector indicates the presence or absence of a related phrase of the particular second phrase; determining from the related phrase bit vector which of the related phrases are also first phrases; and forming a related phrase bit mask corresponding to the related phrases that are also first phrases.
| 0.5 |
9,177,080 | 5 | 6 |
5. The method of claim 1 , further comprising: determining that a segment boundary occurs between the first set of nodes and the second set of nodes based on the plurality of connections.
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5. The method of claim 1 , further comprising: determining that a segment boundary occurs between the first set of nodes and the second set of nodes based on the plurality of connections. 6. The method of claim 5 , further comprising: determining a segment of the content item based on the segment boundary.
| 0.5 |
9,514,123 | 13 | 18 |
13. A method comprising: storing a set of tokens for a current version of a document; tokenizing a new version of the document and generating a set of tokens for the new version of the document; identifying differences between the set of tokens for the new version of the document and the set of tokens for the current version of the document; determining one or more tokens to use to index the document based on the identified differences; generating an index mutation comprising the one or more tokens to use to index the document; storing, in an index mutation journal, the generated index mutation in association with a timestamp; providing, from the generated index mutation, to an index server, the one or more tokens to use to index the document, if the timestamp associated with the generated index mutation in the index mutation journal is newer than a timestamp specified by the index server; receiving, at the index server, the one or more tokens to use to index the document; updating an index of a plurality of documents at the index server to index the document by the one or more tokens to use to index the document; wherein, at a time prior to the updating, the index at the index server indexes the plurality of documents but does not index the document by the one or more tokens to use to index the document; and wherein the method is performed by one or more computing devices.
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13. A method comprising: storing a set of tokens for a current version of a document; tokenizing a new version of the document and generating a set of tokens for the new version of the document; identifying differences between the set of tokens for the new version of the document and the set of tokens for the current version of the document; determining one or more tokens to use to index the document based on the identified differences; generating an index mutation comprising the one or more tokens to use to index the document; storing, in an index mutation journal, the generated index mutation in association with a timestamp; providing, from the generated index mutation, to an index server, the one or more tokens to use to index the document, if the timestamp associated with the generated index mutation in the index mutation journal is newer than a timestamp specified by the index server; receiving, at the index server, the one or more tokens to use to index the document; updating an index of a plurality of documents at the index server to index the document by the one or more tokens to use to index the document; wherein, at a time prior to the updating, the index at the index server indexes the plurality of documents but does not index the document by the one or more tokens to use to index the document; and wherein the method is performed by one or more computing devices. 18. The method of claim 13 , further comprising: determining the timestamp to associate with the generated index mutation.
| 0.848635 |
9,898,654 | 11 | 12 |
11. The method of claim 1 , further comprising: recognizing, using a gesture recognition system, gestures from the user activity; and evaluating, by the computer processing system, a progress of the user in performing the procedure by correlating the gestures with images from the procedure documentation or a text representation of the images from the procedure documentation.
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11. The method of claim 1 , further comprising: recognizing, using a gesture recognition system, gestures from the user activity; and evaluating, by the computer processing system, a progress of the user in performing the procedure by correlating the gestures with images from the procedure documentation or a text representation of the images from the procedure documentation. 12. The method of claim 11 , wherein said evaluating step comprises comparing labels, generated by the gesture recognition system for classifying the user activity, to the text representation of the images from the procedure documentation.
| 0.525794 |
8,793,265 | 51 | 52 |
51. The client module of claim 48 , wherein the updating module is further configured for obtaining an intermediate score based on the weighted sum of frequencies of occurrences.
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51. The client module of claim 48 , wherein the updating module is further configured for obtaining an intermediate score based on the weighted sum of frequencies of occurrences. 52. The client module of claim 51 , wherein the updating module is further configured for calculating a new score based on the weighted sum of the intermediate score and the accumulated scores.
| 0.5 |
8,560,466 | 1 | 5 |
1. An article of manufacture comprising a program storage medium having a non-transitory computer readable code embodied therein, the computer readable code being configured for handling at least a target document, said target document having been transmitted electronically and involving an encoding scheme, the article of manufacture comprising: code for ascertaining, using identification rules, whether a charset employed to encode said target document belongs to an excluded charset group, said excluded charset group having at least two charsets, each charset in said excluded charset group selected based on charset inherent characteristics; code for performing, if said charset employed to encode said target document does not belong to said excluded charset group, further processing of said target document, wherein said code for performing including at least: code for training, using a plurality of text document samples that have been encoded with different encoding schemes and selected for training purposes said different encoding schemes pertaining to charset encoding, to obtain a set of machine learning models, said training including using a SVM (Support Vector Machine) technique to generate said set of machine learning models from feature vectors converted from said plurality of text document samples, said feature vectors are grouped by charsets, wherein said training including generating fundamental units from said plurality of text document samples and extracting a subset of said fundamental units to form a set of feature lists, said feature vectors are converted from said set of feature lists and said plurality of text document samples, said extracting said subset of said fundamental units includes filtering said fundamental units to obtain fundamental units that are more discriminatory in describing differences among said different encoding schemes; code for applying said set of machine learning models against a set of target document feature vectors converted from said target document, said applying including analyzing said set of target document feature vectors using said set of machine learning models to compute similarity indicia between said set of target document feature vectors and said set of machine learning models associated with said different encoding schemes, wherein a first encoding scheme associated with said set of machine learning models is designated as said encoding scheme if characteristics of said first encoding scheme as represented by said set of machine learning models are computed to be most similar, relative to other encoding schemes of said different encoding schemes, to said set of target document feature vectors; and code for decoding said target document to obtain decoded content of said target document based on at least said first encoding scheme.
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1. An article of manufacture comprising a program storage medium having a non-transitory computer readable code embodied therein, the computer readable code being configured for handling at least a target document, said target document having been transmitted electronically and involving an encoding scheme, the article of manufacture comprising: code for ascertaining, using identification rules, whether a charset employed to encode said target document belongs to an excluded charset group, said excluded charset group having at least two charsets, each charset in said excluded charset group selected based on charset inherent characteristics; code for performing, if said charset employed to encode said target document does not belong to said excluded charset group, further processing of said target document, wherein said code for performing including at least: code for training, using a plurality of text document samples that have been encoded with different encoding schemes and selected for training purposes said different encoding schemes pertaining to charset encoding, to obtain a set of machine learning models, said training including using a SVM (Support Vector Machine) technique to generate said set of machine learning models from feature vectors converted from said plurality of text document samples, said feature vectors are grouped by charsets, wherein said training including generating fundamental units from said plurality of text document samples and extracting a subset of said fundamental units to form a set of feature lists, said feature vectors are converted from said set of feature lists and said plurality of text document samples, said extracting said subset of said fundamental units includes filtering said fundamental units to obtain fundamental units that are more discriminatory in describing differences among said different encoding schemes; code for applying said set of machine learning models against a set of target document feature vectors converted from said target document, said applying including analyzing said set of target document feature vectors using said set of machine learning models to compute similarity indicia between said set of target document feature vectors and said set of machine learning models associated with said different encoding schemes, wherein a first encoding scheme associated with said set of machine learning models is designated as said encoding scheme if characteristics of said first encoding scheme as represented by said set of machine learning models are computed to be most similar, relative to other encoding schemes of said different encoding schemes, to said set of target document feature vectors; and code for decoding said target document to obtain decoded content of said target document based on at least said first encoding scheme. 5. The article of manufacture of claim 1 wherein said target document represents an email message.
| 0.679739 |
9,836,538 | 1 | 7 |
1. A computer-readable storage device that stores executable instructions that, when executed by a computer, cause the computer to perform operations comprising: receiving a query; calculating scores for a plurality of documents obtained with respect to the received query by comparing terms in said query with terms in said documents; calling a same first function implemented by each of a plurality of domain-based scorers of different types, to determine, without utilizing one or more documents of the plurality of documents, which of said domain-based scorers will contribute and which will not contribute to scoring of said documents in response to the calculation of said scores for the plurality of documents, wherein the same first function is used to determine whether the received query is too vague and will not be scored or is not too vaoue and will be scored, and wherein determining whether the received query is too vague or not too vague is based upon each domain-based scorer using its own set of first criteria for determining whether the received query is too vague or not too vague, each of said domain-based scorers calculating a domain-based score based on features of said documents or of said query that are specific to a substantive field of knowledge after the calculation of the scores for the plurality of documents, said each of said plurality of domain-based scorers implementing its own version of a same second function to calculate the domain-based score of said documents without obtaining said documents again with respect to the received query, wherein the same second function includes receiving document identifiers to identify said documents in a database and returning scores for said documents and using the returned scores as input into an aggregation formula, wherein each domain-based scorer uses its own set of second criteria within the aggregation formula, wherein said same second function of each of the plurality of domain-based scorers utilizes said documents which have already received scores based on the terms in said query to calculate the domain-based scores of said documents; including, on a list, those domain-based scorers that indicate, through said same first function, that they will contribute to scoring of said documents; using a configurable parameter selected based on a different scoring scheme by those ones of said domain-based scorers that are on said list to adjust said scores, whereby adjusted scores of said documents are created by combining the contributions from all of the said domain-based scorers; creating a set of search results based on the adjusted scores of said documents; and presenting said search results to a user.
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1. A computer-readable storage device that stores executable instructions that, when executed by a computer, cause the computer to perform operations comprising: receiving a query; calculating scores for a plurality of documents obtained with respect to the received query by comparing terms in said query with terms in said documents; calling a same first function implemented by each of a plurality of domain-based scorers of different types, to determine, without utilizing one or more documents of the plurality of documents, which of said domain-based scorers will contribute and which will not contribute to scoring of said documents in response to the calculation of said scores for the plurality of documents, wherein the same first function is used to determine whether the received query is too vague and will not be scored or is not too vaoue and will be scored, and wherein determining whether the received query is too vague or not too vague is based upon each domain-based scorer using its own set of first criteria for determining whether the received query is too vague or not too vague, each of said domain-based scorers calculating a domain-based score based on features of said documents or of said query that are specific to a substantive field of knowledge after the calculation of the scores for the plurality of documents, said each of said plurality of domain-based scorers implementing its own version of a same second function to calculate the domain-based score of said documents without obtaining said documents again with respect to the received query, wherein the same second function includes receiving document identifiers to identify said documents in a database and returning scores for said documents and using the returned scores as input into an aggregation formula, wherein each domain-based scorer uses its own set of second criteria within the aggregation formula, wherein said same second function of each of the plurality of domain-based scorers utilizes said documents which have already received scores based on the terms in said query to calculate the domain-based scores of said documents; including, on a list, those domain-based scorers that indicate, through said same first function, that they will contribute to scoring of said documents; using a configurable parameter selected based on a different scoring scheme by those ones of said domain-based scorers that are on said list to adjust said scores, whereby adjusted scores of said documents are created by combining the contributions from all of the said domain-based scorers; creating a set of search results based on the adjusted scores of said documents; and presenting said search results to a user. 7. The computer-readable storage device of claim 1 , further comprising: determining a number of concepts from a domain that appears in the at least one document; determining that the number falls within a range; and modifying a domain-based score of the at least one document based on the number falls within the range, wherein the domain-based score is increased on determining that the number falls within a first range, the domain-based score remains same on determining that the number falls within a second range, and the domain-based score is decreased on determining that the number falls within a third range.
| 0.5 |
10,074,102 | 11 | 12 |
11. The non-transitory computer readable storage medium as recited in claim 10 , further comprising instructions that, when executed by the at least one processor, cause the computer system to identify one or more engagement indicators associated with each of the plurality of social media posts associated with the social media group of users having the plurality of characteristics and including the keyword.
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11. The non-transitory computer readable storage medium as recited in claim 10 , further comprising instructions that, when executed by the at least one processor, cause the computer system to identify one or more engagement indicators associated with each of the plurality of social media posts associated with the social media group of users having the plurality of characteristics and including the keyword. 12. The non-transitory computer readable storage medium as recited in claim 11 , wherein the instructions, when executed by the at least one processor, cause the computer system to identify one or more engagement indicators associated with each of the plurality of social media posts associated with the social media group of users having the plurality of characteristics and including the keyword by identifying one or more of a social media reply, a social media share, a social media “like,” or a social media comment for each of the plurality of social media posts associated with the social media group of users having the plurality of characteristics and including the keyword.
| 0.5 |
8,799,317 | 8 | 15 |
8. A forensic method for acquiring digital information recorded on a plurality of computers or a server to analyze the acquired digital information, the method comprising: acquiring digital information containing digital document information composed of a plurality of document files, acquiring user information about users using the plurality of computers or the server, and acquiring access history information which shows a fact that the users accessed a document file recorded in the server; recording the acquired digital information; displaying, on a first display unit usable by a first operator, the recorded digital information; displaying, on a second display unit usable by a second operator, the recorded digital information; selecting, via at least one of the first display unit or the second display unit, a specific first individual and a specific second individual from the users contained in the user information, wherein the first operator, the second operator, the specific first individual, and the specific second individual are different from each other; extracting, by an extracting unit operable on a first server, only digital document information which was accessed by the specific first individual and the specific second individual based on the access history information related with the selected specific first individual and the selected specific second individual; analyzing, by a file analysis function, a kind of document file which was accessed or possessed by the specific first individual and the specific second individual; causing the extraction unit, by a kind selection function, to extract a particular kind of document file; preserving, by a preservation function, the extracted document file as a separate file and controlling the status thereof; when newly acquiring digital information, clocking by a clock unit a time and date of the acquisition of the digital information, the digital information further including folder information saving digital document information; acquiring, by the digital information acquiring unit, the digital document information and the folder information which were produced after a time and date previously clocked by the clock unit, and acquiring user information and access history information related with the acquired digital document information and the folder information; simultaneously setting additional information, by a first additional information setting unit usable by the first operator via the first display unit and a second additional information setting unit usable by the second operator via the second display unit, indicating which document files in the extracted digital document information are each related with litigation, and which document files in the extracted digital document information are each not related with litigation; searching, by a multi-language full-text searching unit operable on a second server, the full-text of the document files based on the extracted digital document information; setting, by an access right control function of a managing unit, one or more rights for each account of a browser; and outputting a document file related with the litigation based on the additional information.
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8. A forensic method for acquiring digital information recorded on a plurality of computers or a server to analyze the acquired digital information, the method comprising: acquiring digital information containing digital document information composed of a plurality of document files, acquiring user information about users using the plurality of computers or the server, and acquiring access history information which shows a fact that the users accessed a document file recorded in the server; recording the acquired digital information; displaying, on a first display unit usable by a first operator, the recorded digital information; displaying, on a second display unit usable by a second operator, the recorded digital information; selecting, via at least one of the first display unit or the second display unit, a specific first individual and a specific second individual from the users contained in the user information, wherein the first operator, the second operator, the specific first individual, and the specific second individual are different from each other; extracting, by an extracting unit operable on a first server, only digital document information which was accessed by the specific first individual and the specific second individual based on the access history information related with the selected specific first individual and the selected specific second individual; analyzing, by a file analysis function, a kind of document file which was accessed or possessed by the specific first individual and the specific second individual; causing the extraction unit, by a kind selection function, to extract a particular kind of document file; preserving, by a preservation function, the extracted document file as a separate file and controlling the status thereof; when newly acquiring digital information, clocking by a clock unit a time and date of the acquisition of the digital information, the digital information further including folder information saving digital document information; acquiring, by the digital information acquiring unit, the digital document information and the folder information which were produced after a time and date previously clocked by the clock unit, and acquiring user information and access history information related with the acquired digital document information and the folder information; simultaneously setting additional information, by a first additional information setting unit usable by the first operator via the first display unit and a second additional information setting unit usable by the second operator via the second display unit, indicating which document files in the extracted digital document information are each related with litigation, and which document files in the extracted digital document information are each not related with litigation; searching, by a multi-language full-text searching unit operable on a second server, the full-text of the document files based on the extracted digital document information; setting, by an access right control function of a managing unit, one or more rights for each account of a browser; and outputting a document file related with the litigation based on the additional information. 15. The method of claim 8 , wherein setting further includes setting an access right.
| 0.527778 |
9,043,319 | 2 | 3 |
2. The method of claim 1 , wherein determining whether real-time search results should be included in a response to the search query includes: receiving data for the search query; generating one or more scores from the data; and determining that each of the one or more scores satisfies a respective threshold.
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2. The method of claim 1 , wherein determining whether real-time search results should be included in a response to the search query includes: receiving data for the search query; generating one or more scores from the data; and determining that each of the one or more scores satisfies a respective threshold. 3. The method of claim 2 , wherein the data includes a rate with which new documents responsive to the query are identified.
| 0.586667 |
7,684,991 | 11 | 15 |
11. An apparatus for searching audio files in a portable audio player in combination with an automobile audio system, comprising: means for reading meta-tag data associated with each audio file and producing voice data files for information retrieved from the meta-tag data; means for creating a play list that lists the voice data files produced based on the meta-tag data in an predetermined order where each of the voice data files and audio files is accompanied by address data; means for storing the play list and the audio files in the portable audio player; means for connecting the portable audio player with the automobile audio system for sending the voice data files in the play list and the audio files to the automobile audio system and receiving command signals from the automobile audio system; means for generating speech sounds that successively and automatically read aloud the data in the voice data files in the play list by the automobile audio system in a predetermined order and speed; means for accepting user's commands made in response to the speech sounds where the user's commands are transmitted through the automobile audio system to the portable audio player; and means for searching an audio file in the portable audio player based on the user's commands; wherein the speech sounds generated from the automobile audio system include a series of information on audio files so that a particular audio file is specified when both the information on the particular audio file is announced by the speech sounds and the user's commands are issued.
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11. An apparatus for searching audio files in a portable audio player in combination with an automobile audio system, comprising: means for reading meta-tag data associated with each audio file and producing voice data files for information retrieved from the meta-tag data; means for creating a play list that lists the voice data files produced based on the meta-tag data in an predetermined order where each of the voice data files and audio files is accompanied by address data; means for storing the play list and the audio files in the portable audio player; means for connecting the portable audio player with the automobile audio system for sending the voice data files in the play list and the audio files to the automobile audio system and receiving command signals from the automobile audio system; means for generating speech sounds that successively and automatically read aloud the data in the voice data files in the play list by the automobile audio system in a predetermined order and speed; means for accepting user's commands made in response to the speech sounds where the user's commands are transmitted through the automobile audio system to the portable audio player; and means for searching an audio file in the portable audio player based on the user's commands; wherein the speech sounds generated from the automobile audio system include a series of information on audio files so that a particular audio file is specified when both the information on the particular audio file is announced by the speech sounds and the user's commands are issued. 15. An apparatus for searching an audio file as defined in claim 11 , wherein said means for creating the play list that lists the voice data files includes means for arranging the voice data files in a user defined order so that the automobile audio system produces the speech sounds associated with the audio files in the user defined order.
| 0.707836 |
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