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9,092,792 | 1 | 12 | 1. A method executing on a server computer comprising: receiving a connection request from a seller application that is customizable by configuration information that includes a hierarchal product category structure for generating a listing for a product for sale, the seller application executing on a client machine; determining that the seller application has not been customized by a current version of the configuration information; transmitting the current version of the configuration information to the seller application, receiving, from the seller application, a product listing request and a configuration confirmation, the configuration confirmation indicating the seller application on the client machine has been configured using the current version of the configuration information to include the hierarchal product category structure; and generating a product listing using the product listing request. | 1. A method executing on a server computer comprising: receiving a connection request from a seller application that is customizable by configuration information that includes a hierarchal product category structure for generating a listing for a product for sale, the seller application executing on a client machine; determining that the seller application has not been customized by a current version of the configuration information; transmitting the current version of the configuration information to the seller application, receiving, from the seller application, a product listing request and a configuration confirmation, the configuration confirmation indicating the seller application on the client machine has been configured using the current version of the configuration information to include the hierarchal product category structure; and generating a product listing using the product listing request. 12. The method of claim 1 , wherein: the configuration information further includes a currency; and the seller application is configured by the configuration information, in response to the transmitting of the configuration information, to display a fee in the identified currency. | 0.590379 |
9,262,486 | 5 | 6 | 5. A computer-implemented method, comprising: receiving a threshold error distance; receiving a first search term and a second search term; querying an inverted token next valid character tree with the first search term and the second search term, wherein each branch through the tree defines a token and a document set for the token is stored at a leaf node; wherein each branch has an error distance which comprises the number of edit operations to transform the token associated with the branch to at least one of the search tokens; calculating a first document error list of error distances for the first search term and inverted token next valid character tree; calculating a second document error list of error distances for the second search term and the inverted token next valid character tree; comparing the first document error list and the second document error list to identify common document identifiers in both the first document error list and the second document list with a sum of error distances from the first and second document error list that is less than or equal to the threshold error distance; and providing a result set of the common document identifiers with the sum of error distances from the first and second document error list that is less than or equal to the threshold error distance. | 5. A computer-implemented method, comprising: receiving a threshold error distance; receiving a first search term and a second search term; querying an inverted token next valid character tree with the first search term and the second search term, wherein each branch through the tree defines a token and a document set for the token is stored at a leaf node; wherein each branch has an error distance which comprises the number of edit operations to transform the token associated with the branch to at least one of the search tokens; calculating a first document error list of error distances for the first search term and inverted token next valid character tree; calculating a second document error list of error distances for the second search term and the inverted token next valid character tree; comparing the first document error list and the second document error list to identify common document identifiers in both the first document error list and the second document list with a sum of error distances from the first and second document error list that is less than or equal to the threshold error distance; and providing a result set of the common document identifiers with the sum of error distances from the first and second document error list that is less than or equal to the threshold error distance. 6. The method of claim 5 , wherein the search tokens include at least one token prefix. | 0.654762 |
9,055,074 | 1 | 5 | 1. A method for aggregating social media content items that are relevant to geographically definable locations, the method being implemented in a computer that includes one or more processors programmed with computer program instructions that, when executed by the one or more physical processors, programs the one or more physical processors to perform the method, the method comprising: obtaining, by the one or more physical processors, at least a first parameter that specifies one or more geographically definable locations; generating, by the one or more physical processors, a first request that specifies the one or more geographically definable locations in a first format used by a first social media content provider; generating, by the one or more physical processors, a second request that specifies the one or more geographically definable locations in a second format used by a second social media content provider; communicating, by the one or more physical processors, the first request to the first social media content provider; communicating, by the one or more physical processors, the second request to the second social media content provider; receiving, by the one or more physical processors, a first set of social media content items from the first social media content provider, wherein the first set of social media content items includes at least a first social media content item associated with information that indicates that the first social media content item is relevant to the one or more geographically definable locations; receiving, by the one or more physical processors, a second set of social media content items from the second social media content provider, wherein the second set of social media content items includes at least a second social media item associated with information that indicates that the second social media content item is relevant to the one or more geographically definable locations; and communicating, by the one or more physical processors, at least a portion of the first set of social media content items and at least a portion of the second set of social media content items. | 1. A method for aggregating social media content items that are relevant to geographically definable locations, the method being implemented in a computer that includes one or more processors programmed with computer program instructions that, when executed by the one or more physical processors, programs the one or more physical processors to perform the method, the method comprising: obtaining, by the one or more physical processors, at least a first parameter that specifies one or more geographically definable locations; generating, by the one or more physical processors, a first request that specifies the one or more geographically definable locations in a first format used by a first social media content provider; generating, by the one or more physical processors, a second request that specifies the one or more geographically definable locations in a second format used by a second social media content provider; communicating, by the one or more physical processors, the first request to the first social media content provider; communicating, by the one or more physical processors, the second request to the second social media content provider; receiving, by the one or more physical processors, a first set of social media content items from the first social media content provider, wherein the first set of social media content items includes at least a first social media content item associated with information that indicates that the first social media content item is relevant to the one or more geographically definable locations; receiving, by the one or more physical processors, a second set of social media content items from the second social media content provider, wherein the second set of social media content items includes at least a second social media item associated with information that indicates that the second social media content item is relevant to the one or more geographically definable locations; and communicating, by the one or more physical processors, at least a portion of the first set of social media content items and at least a portion of the second set of social media content items. 5. The method of claim 1 , further comprising: spatially arranging, by the one or more processors, at least the first social media content item and the second social media content item on a map display. | 0.802734 |
9,286,618 | 6 | 7 | 6. A system for determining whether a subject merchant location database entry and a candidate merchant location database entry are describing the same merchant location, the system comprising: a machine-readable database storing merchant location database entries, each merchant location database entry having a DBA name text field designating the doing business as (DBA) name of each respective merchant location, a street address text field designating the street address of the location of each respective merchant location, and one or more additional descriptive fields descriptive of one or more predetermined characteristics of the respective merchant location; a processor; and a tangible machine-readable memory device storing a program of instructions thereon which, when executed by the processor, cause the processor to: designate a merchant location database entry appearing in a master merchant location database or a transaction data stream to be compared as a subject merchant location database entry; populate a set with one or more candidate merchant location database entries located in a data warehouse database maintained by a network operator for comparison to the subject merchant location database entry, wherein each candidate merchant location database entry selected as a member of the set is chosen from the machine-readable database for having a predetermined minimum textural similarity with the subject merchant location database entry on the basis of each database entry's respective DBA name text field or street address text field; compare the subject merchant location database entry with each of the candidate database entries on the basis of the one or more additional descriptive fields retrieved from the data warehouse database; perform a logistic regression using the results of the comparing to calculate a probability that the merchant location corresponding to the subject merchant location database entry and the merchant location corresponding to one or more of the candidate merchant location database entries are the same merchant location; and output the results of the logistic regression, wherein the one or more additional descriptive fields retrieved from the data warehouse include a classification code, the classification code derived from a hierarchical classification, and the comparing determines whether the subject merchant location database entry or the candidate merchant location database entry includes a classification code related to an industry which is experientially known to have merchant location identification data that is either more stable than or less stable than other industries, and the logistic regression weights a merchant location classification code with regard to whether the related industry is known to have more or less stable merchant location identification data. | 6. A system for determining whether a subject merchant location database entry and a candidate merchant location database entry are describing the same merchant location, the system comprising: a machine-readable database storing merchant location database entries, each merchant location database entry having a DBA name text field designating the doing business as (DBA) name of each respective merchant location, a street address text field designating the street address of the location of each respective merchant location, and one or more additional descriptive fields descriptive of one or more predetermined characteristics of the respective merchant location; a processor; and a tangible machine-readable memory device storing a program of instructions thereon which, when executed by the processor, cause the processor to: designate a merchant location database entry appearing in a master merchant location database or a transaction data stream to be compared as a subject merchant location database entry; populate a set with one or more candidate merchant location database entries located in a data warehouse database maintained by a network operator for comparison to the subject merchant location database entry, wherein each candidate merchant location database entry selected as a member of the set is chosen from the machine-readable database for having a predetermined minimum textural similarity with the subject merchant location database entry on the basis of each database entry's respective DBA name text field or street address text field; compare the subject merchant location database entry with each of the candidate database entries on the basis of the one or more additional descriptive fields retrieved from the data warehouse database; perform a logistic regression using the results of the comparing to calculate a probability that the merchant location corresponding to the subject merchant location database entry and the merchant location corresponding to one or more of the candidate merchant location database entries are the same merchant location; and output the results of the logistic regression, wherein the one or more additional descriptive fields retrieved from the data warehouse include a classification code, the classification code derived from a hierarchical classification, and the comparing determines whether the subject merchant location database entry or the candidate merchant location database entry includes a classification code related to an industry which is experientially known to have merchant location identification data that is either more stable than or less stable than other industries, and the logistic regression weights a merchant location classification code with regard to whether the related industry is known to have more or less stable merchant location identification data. 7. The system according to claim 6 , wherein the one or more additional descriptive fields retrieved from the data warehouse include at least one field containing data selected from the group comprising a classification code related to the respective merchant location's line of business, a merchant location city, a merchant location zip code, a flag related to whether the merchant location has a taxpayer identification number, a merchant location taxpayer identification number, a flag related to whether the merchant location has an acquirer-defined merchant location identification, an acquirer-defined merchant location identification, a flag related to whether the merchant location is part of a group of merchant locations that are considered in the aggregate, a label related to a group of merchant locations with which the individual merchant location is considered in the aggregate, and an identifier applied to the merchant location by a third party service provider. | 0.5 |
6,134,322 | 1 | 9 | 1. An echo suppressor for a speech input dialogue system, said speech input dialogue system producing a system input request and receiving an input speech signal, said echo suppressor comprising: fast Fourier transformation means for fast Fourier transforming each of said system input request and said input speech signal for producing a short-term magnitude spectrum of said system input request and a short-term magnitude spectrum of said input speech signal, each of said short-term magnitude spectra being comprised of frequency components; band reduction means, supplied with said short-term magnitude spectrum of said system input request and said short-term magnitude spectrum of said input speech signal, for dividing said short-term magnitude spectrum of said system input request into a first set of sub-band signals based on said frequency components of said short-term magnitude spectrum of said system input request, and for dividing said short-term magnitude spectrum of said input speech signal into a second set of sub-band signals based on said frequency components of said short-term magnitude spectrum of said input speech signal; a plurality of adaptive filters, supplied with said first set of sub-band signals, for simulating a pulse response of a line echo, produced by said system input request, on a path traversed by said input speech signal, said plurality of adaptive filters respectively having adaptation coefficients; adaption means for adapting said adaptation coefficients dependent on respective outputs of said adaptive filters and on said second set of sub-band signals; band restoration means, supplied with said outputs of said plurality of adaptive filters, for restoring a full-band signal from said outputs of said plurality of adaptive filters to replicate said line echo; and subtraction means for subtracting said replicated echo from said short-term magnitude spectrum of the input speech signal. | 1. An echo suppressor for a speech input dialogue system, said speech input dialogue system producing a system input request and receiving an input speech signal, said echo suppressor comprising: fast Fourier transformation means for fast Fourier transforming each of said system input request and said input speech signal for producing a short-term magnitude spectrum of said system input request and a short-term magnitude spectrum of said input speech signal, each of said short-term magnitude spectra being comprised of frequency components; band reduction means, supplied with said short-term magnitude spectrum of said system input request and said short-term magnitude spectrum of said input speech signal, for dividing said short-term magnitude spectrum of said system input request into a first set of sub-band signals based on said frequency components of said short-term magnitude spectrum of said system input request, and for dividing said short-term magnitude spectrum of said input speech signal into a second set of sub-band signals based on said frequency components of said short-term magnitude spectrum of said input speech signal; a plurality of adaptive filters, supplied with said first set of sub-band signals, for simulating a pulse response of a line echo, produced by said system input request, on a path traversed by said input speech signal, said plurality of adaptive filters respectively having adaptation coefficients; adaption means for adapting said adaptation coefficients dependent on respective outputs of said adaptive filters and on said second set of sub-band signals; band restoration means, supplied with said outputs of said plurality of adaptive filters, for restoring a full-band signal from said outputs of said plurality of adaptive filters to replicate said line echo; and subtraction means for subtracting said replicated echo from said short-term magnitude spectrum of the input speech signal. 9. An echo suppressor as claimed in claim 1 further comprising a speech recognition system to which an output of said subtraction means is supplied. | 0.851703 |
9,805,006 | 15 | 16 | 15. The system of claim 11 , wherein the variable is further configured to: insert, via an executable push system of the variable, a new item into the variable. | 15. The system of claim 11 , wherein the variable is further configured to: insert, via an executable push system of the variable, a new item into the variable. 16. The system of claim 15 , wherein the script is further configured to: convert the variable to an object type defined in the script. | 0.5 |
8,799,234 | 8 | 10 | 8. The process of claim 7 , wherein the process action of identifying formatting instructions which are capable of formatting an output item so as to match the formatting of the desired output item of the input-output example, comprises an action of associating formatting instructions from a library of formatting instructions, for each semantic entity field identified in the parse descriptor of the parse descriptor tuple associated with the output item of the input-output example, which produces the corresponding field of the semantic entity of that descriptor tuple in the format exhibited by the portion of the output item associated with the semantic entity field. | 8. The process of claim 7 , wherein the process action of identifying formatting instructions which are capable of formatting an output item so as to match the formatting of the desired output item of the input-output example, comprises an action of associating formatting instructions from a library of formatting instructions, for each semantic entity field identified in the parse descriptor of the parse descriptor tuple associated with the output item of the input-output example, which produces the corresponding field of the semantic entity of that descriptor tuple in the format exhibited by the portion of the output item associated with the semantic entity field. 10. The process of claim 8 , wherein the entity class of each semantic entity identifies a prescribed canonical form of the semantic entity, said process further comprising a process actions of, for each weighted semantic entity and parse descriptor tuple, converting the semantic entity to the prescribed canonical form of the semantic entity, and wherein the process action of applying the transform to the semantic entities of the identified parse descriptor tuples associated with the input items to produce the entity of the identified parse descriptor tuple associated with the output item, comprises an action of producing the entity of the identified parse descriptor tuple associated with the output item in the prescribed canonical form, and wherein the process action of identifying formatting instructions which are capable of formatting an output item so as to match the formatting of the desired output item of the input-output example, further comprises an action of converting the output item from the prescribed canonical form to a form consistent with the desired output item of the input-output example. | 0.688679 |
8,909,651 | 1 | 7 | 1. A method, the method comprising: identifying search engine optimization keywords associated with an entity; identifying social media correspondence from social media referencing the search engine optimization keywords; designating one or more of the search engine optimization keywords as selected keywords based on the social media correspondence; requesting search results from a search engine that result from a search of the selected keywords on the search engine; identifying one or more non-social media webpages that are associated with the entity and that are included in the search results; and generating an electronic notification for sending to the entity, the electronic notification recommending material for engagement in the social media, the material including information located on the identified one or more non-social media webpages. | 1. A method, the method comprising: identifying search engine optimization keywords associated with an entity; identifying social media correspondence from social media referencing the search engine optimization keywords; designating one or more of the search engine optimization keywords as selected keywords based on the social media correspondence; requesting search results from a search engine that result from a search of the selected keywords on the search engine; identifying one or more non-social media webpages that are associated with the entity and that are included in the search results; and generating an electronic notification for sending to the entity, the electronic notification recommending material for engagement in the social media, the material including information located on the identified one or more non-social media webpages. 7. The method of claim 1 , wherein the one or more of the search engine optimization keywords are designated as selected keywords based on the selected keywords being included in the social media correspondence provided by a social media participant with higher than average social media participation. | 0.766975 |
8,868,648 | 10 | 15 | 10. A non-transitory computer readable medium having stored thereon instructions which when executed by a processor cause the processor to perform the method of: receiving at a server a relational database query from an application running on a client computer coupled to an electronic communication network; parsing by a parsing engine the relational database query; creating an execution plan based on the results of the parsing step; transmitting an opendata query to an opendata provider coupled to the electronic communication network, the opendata query including at least a portion of the execution plan; retrieving, at the server, document metadata from the opendata provider; building an internal model of the document metadata; mapping content of at least one opendata entity data model located at the opendata provider and the document metadata to at least one relational model catalog; transforming at the server a response from the opendata provider into a relational format; and providing the transformed response to the client computer application. | 10. A non-transitory computer readable medium having stored thereon instructions which when executed by a processor cause the processor to perform the method of: receiving at a server a relational database query from an application running on a client computer coupled to an electronic communication network; parsing by a parsing engine the relational database query; creating an execution plan based on the results of the parsing step; transmitting an opendata query to an opendata provider coupled to the electronic communication network, the opendata query including at least a portion of the execution plan; retrieving, at the server, document metadata from the opendata provider; building an internal model of the document metadata; mapping content of at least one opendata entity data model located at the opendata provider and the document metadata to at least one relational model catalog; transforming at the server a response from the opendata provider into a relational format; and providing the transformed response to the client computer application. 15. The non-transitory computer readable medium of claim 10 , wherein the parsing step includes executable instructions to cause a processor to perform the step of creating an abstract syntax tree based on objects of the relational database query. | 0.642029 |
9,864,767 | 8 | 11 | 8. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining a resource that includes a first term that includes at least a first word and a second word; identifying a second term that (i) includes at least a third word and a fourth word, and (ii) that is indicated as a substitute term for the first term; storing, as a first entry in a search index, (i) data referencing the first word included in the first term, and (ii) data referencing the resource; storing, as a second entry in the search index, (i) data referencing the second word included in the first term, and (ii) data referencing the resource; storing, as a third entry in the search index, (i) data referencing the third word included in a second term that is indicated as a substitute term of the first term, (ii) data indicating that the third word included in the second term is a part of a substitute term and does not actually occur in the resource, (iii) data relating to a quantity of words in the first term, (iv) data relating an order of the third word within the second term, and (v) data referencing the resource; and storing, as a fourth entry in a search index, (i) data referencing the fourth word included in a second term that is indicated as a substitute term of the first term, (ii) data indicating that the fourth word included in the second term is a part of a substitute term and does not actually occur in the resource, (iii) data relating to a quantity of words in the first term, (iv) data relating an order of the fourth word within the second term, and (v) data referencing the resource. | 8. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining a resource that includes a first term that includes at least a first word and a second word; identifying a second term that (i) includes at least a third word and a fourth word, and (ii) that is indicated as a substitute term for the first term; storing, as a first entry in a search index, (i) data referencing the first word included in the first term, and (ii) data referencing the resource; storing, as a second entry in the search index, (i) data referencing the second word included in the first term, and (ii) data referencing the resource; storing, as a third entry in the search index, (i) data referencing the third word included in a second term that is indicated as a substitute term of the first term, (ii) data indicating that the third word included in the second term is a part of a substitute term and does not actually occur in the resource, (iii) data relating to a quantity of words in the first term, (iv) data relating an order of the third word within the second term, and (v) data referencing the resource; and storing, as a fourth entry in a search index, (i) data referencing the fourth word included in a second term that is indicated as a substitute term of the first term, (ii) data indicating that the fourth word included in the second term is a part of a substitute term and does not actually occur in the resource, (iii) data relating to a quantity of words in the first term, (iv) data relating an order of the fourth word within the second term, and (v) data referencing the resource. 11. The system of claim 8 , wherein the first through fourth words are all different words. | 0.730769 |
8,266,068 | 12 | 20 | 12. A non-transitory computer readable medium storing instructions for interviewing a candidate, the instructions when executed by a processor comprising functionality to: provide a virtual interview assistant comprising an interview plan, a recording module, an analysis module, and candidate screening criteria, wherein the interview plan comprises one or more interview sessions, wherein the recording module is configured to record at least one recording selected from a group consisting of video recording, audio recording, and physiological parameter recording, wherein the analysis module is configured for analyzing the at least one recording, and wherein the candidate screening criteria comprise an acceptance criterion for each of the one or more interview sessions; obtain a pre-determined qualification score representing a level of a current employee fitting a target requirement, wherein the pre-determined qualification score is assigned to the current employee based on a performance track record of the current employee in a position held by the current employee, and wherein the current employee is identified as a qualified candidate by a recruiter based on the target requirement; interviewing, in a mock interview subsequent to identifying the current employee, the current employee using the virtual interview assistant to generate a qualified candidate profile; adjust the interview plan to generate an adjusted interview plan based on the mock interview score qualified candidate profile and the pre-determined qualification score; collect a candidate interview response by interviewing the candidate using the virtual interview assistant based on the adjusted interview plan, wherein at least a portion of the candidate interview response is collected using the recording module; analyze the candidate interview response using the analysis module to generate candidate profile information comprising a score for each of the one or more interview sessions; and selectively present the candidate profile to the recruiter in response to the candidate profile information meeting the candidate screening criteria, wherein each score in the candidate profile information confirms to the acceptance criterion in the candidate screening criteria for a corresponding one of the one or more interview sessions, and wherein the recruiter makes a recruiting decision regarding the candidate based on the candidate profile information. | 12. A non-transitory computer readable medium storing instructions for interviewing a candidate, the instructions when executed by a processor comprising functionality to: provide a virtual interview assistant comprising an interview plan, a recording module, an analysis module, and candidate screening criteria, wherein the interview plan comprises one or more interview sessions, wherein the recording module is configured to record at least one recording selected from a group consisting of video recording, audio recording, and physiological parameter recording, wherein the analysis module is configured for analyzing the at least one recording, and wherein the candidate screening criteria comprise an acceptance criterion for each of the one or more interview sessions; obtain a pre-determined qualification score representing a level of a current employee fitting a target requirement, wherein the pre-determined qualification score is assigned to the current employee based on a performance track record of the current employee in a position held by the current employee, and wherein the current employee is identified as a qualified candidate by a recruiter based on the target requirement; interviewing, in a mock interview subsequent to identifying the current employee, the current employee using the virtual interview assistant to generate a qualified candidate profile; adjust the interview plan to generate an adjusted interview plan based on the mock interview score qualified candidate profile and the pre-determined qualification score; collect a candidate interview response by interviewing the candidate using the virtual interview assistant based on the adjusted interview plan, wherein at least a portion of the candidate interview response is collected using the recording module; analyze the candidate interview response using the analysis module to generate candidate profile information comprising a score for each of the one or more interview sessions; and selectively present the candidate profile to the recruiter in response to the candidate profile information meeting the candidate screening criteria, wherein each score in the candidate profile information confirms to the acceptance criterion in the candidate screening criteria for a corresponding one of the one or more interview sessions, and wherein the recruiter makes a recruiting decision regarding the candidate based on the candidate profile information. 20. The computer readable medium of claim 12 , the instructions further comprising functionality to: store the candidate profile information for at least one selected from a group consisting of a different position, a future position, a different recruiter, and a different employer, wherein the candidate is interviewed by the virtual interview assistant for the recruiter based on a current position of an employer. | 0.771131 |
8,146,156 | 20 | 28 | 20. A computer-implemented method, comprising: receiving, at a capture device, text capture indications corresponding to text capture operations from a rendered document, each text capture operation capturing less than a whole page of text; the capture device identifying at least one of goods and services using text from at least one of the text capture operations; and the capture device facilitating a transaction related to said at least one of goods and services. | 20. A computer-implemented method, comprising: receiving, at a capture device, text capture indications corresponding to text capture operations from a rendered document, each text capture operation capturing less than a whole page of text; the capture device identifying at least one of goods and services using text from at least one of the text capture operations; and the capture device facilitating a transaction related to said at least one of goods and services. 28. The method of claim 20 , wherein said rendered document comprises an e-book. | 0.766082 |
7,603,269 | 1 | 5 | 1. A speech recognition grammar creating apparatus that describes a speech-recognizing object as a speech recognition grammar, comprising: a grouping unit adapted to create a component group of n component elements, wherein n is an integer not less than 2; a first determination unit adapted to determine if the component group of n component elements is a group including at least one component element that cannot be omitted; a second determination unit adapted to determine if the n component elements are order designated when it is determined by said first determination unit that the component group is the group including the at least one component element that cannot be omitted; and a creating unit adapted to create the speech recognition grammar by creating sequences of the n component elements and combinations thereof according to the designated order when it is determined by said second determination unit that the n component elements are order designated, and by creating respective permutations of the n component elements and combinations thereof when it is determined by said second determination unit that the n component elements are not order designated. | 1. A speech recognition grammar creating apparatus that describes a speech-recognizing object as a speech recognition grammar, comprising: a grouping unit adapted to create a component group of n component elements, wherein n is an integer not less than 2; a first determination unit adapted to determine if the component group of n component elements is a group including at least one component element that cannot be omitted; a second determination unit adapted to determine if the n component elements are order designated when it is determined by said first determination unit that the component group is the group including the at least one component element that cannot be omitted; and a creating unit adapted to create the speech recognition grammar by creating sequences of the n component elements and combinations thereof according to the designated order when it is determined by said second determination unit that the n component elements are order designated, and by creating respective permutations of the n component elements and combinations thereof when it is determined by said second determination unit that the n component elements are not order designated. 5. A speech recognition grammar creating apparatus as claimed in claim 1 , wherein said creating device creates the speech recognition grammar in a metalanguage format. | 0.721854 |
9,305,090 | 15 | 19 | 15. A system, comprising: at least one computing device comprising a processor and a memory; and an application executable in the at least one computing device, the application causing the at least one computing device to at least: request a plurality of suggested keywords from a server in response to user input submitted through a query form, wherein at least one of the plurality of suggested keywords is based at least in part on a shopping history associated with a user account corresponding to an electronic commerce application or a popularity of an item offered for sale through the electronic commerce application and at least one of the plurality of suggested keywords comprises at least one enhanced suggested keyword, the at least one enhanced suggested keyword including at least one spelling correction to the user input; determine a number of a plurality of speculative search queries, the number of the plurality of speculative search queries being determined based at least in part on a length of time that the user account has been associated with the electronic commerce application; provide the plurality of speculative search queries to the server, wherein individual ones of the plurality of speculative search queries comprise at least one of the plurality of suggested keywords, and wherein individual ones of the plurality of speculative search queries that include the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword are weighted higher than individual ones of the plurality of speculative search queries that fail to include any of the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword, wherein the weights of the suggested keywords are used to prefer the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword over individual ones of the plurality of speculative search queries that fail to include the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword when determining suggested keywords to include in the speculative search queries; render, in a hidden portion of a browser window, at least a portion of at least two of a plurality of speculative search results, the at least two of the plurality of speculative search results correspond to at least one of the plurality of speculative search queries; move the rendered portion of the at least two of the plurality of speculative search results from the hidden portion of the browser window to a visible portion of the browser window; render the portion of the at least two of the plurality of speculative search results in the visible portion of the browser window in response to receiving a user instruction to execute a committed search query that includes a suggested keyword from the at least one of the plurality of speculative queries; and render, in the visible portion of the browser window, a remaining portion of the plurality of speculative search results from at least one of the plurality of speculative search queries, in response to receiving the remaining portion of results from the server. | 15. A system, comprising: at least one computing device comprising a processor and a memory; and an application executable in the at least one computing device, the application causing the at least one computing device to at least: request a plurality of suggested keywords from a server in response to user input submitted through a query form, wherein at least one of the plurality of suggested keywords is based at least in part on a shopping history associated with a user account corresponding to an electronic commerce application or a popularity of an item offered for sale through the electronic commerce application and at least one of the plurality of suggested keywords comprises at least one enhanced suggested keyword, the at least one enhanced suggested keyword including at least one spelling correction to the user input; determine a number of a plurality of speculative search queries, the number of the plurality of speculative search queries being determined based at least in part on a length of time that the user account has been associated with the electronic commerce application; provide the plurality of speculative search queries to the server, wherein individual ones of the plurality of speculative search queries comprise at least one of the plurality of suggested keywords, and wherein individual ones of the plurality of speculative search queries that include the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword are weighted higher than individual ones of the plurality of speculative search queries that fail to include any of the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword, wherein the weights of the suggested keywords are used to prefer the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword over individual ones of the plurality of speculative search queries that fail to include the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword when determining suggested keywords to include in the speculative search queries; render, in a hidden portion of a browser window, at least a portion of at least two of a plurality of speculative search results, the at least two of the plurality of speculative search results correspond to at least one of the plurality of speculative search queries; move the rendered portion of the at least two of the plurality of speculative search results from the hidden portion of the browser window to a visible portion of the browser window; render the portion of the at least two of the plurality of speculative search results in the visible portion of the browser window in response to receiving a user instruction to execute a committed search query that includes a suggested keyword from the at least one of the plurality of speculative queries; and render, in the visible portion of the browser window, a remaining portion of the plurality of speculative search results from at least one of the plurality of speculative search queries, in response to receiving the remaining portion of results from the server. 19. The system of claim 15 , wherein the number of the plurality of speculative search queries also varies in accordance with a number of characters in the user input provided to the server. | 0.628906 |
7,971,195 | 26 | 31 | 26. A computer readable storage medium encoded with a computer program code for directing a computer processor to transform instructions in an asynchronous transactional messaging language to instructions compatible with web services, said program code comprising: a translate proxy class code segment for causing said computer processor to iteratively translate, a predetermined number of times, proxy class instructions of said asynchronous transactional messaging language into corresponding port type instructions compatible with said web services, wherein said predetermined number is determined in accordance with a level of dependency of variables within said asynchronous transactional messaging language; a translate method code segment for causing said computer processor to translate methods of said proxy class instructions into corresponding operations of said port types; a translate input parameter code segment for causing said computer processor to translate input parameters of said methods into corresponding request message types of said operations; a translate output parameter code segment for causing said computer processor to translate output parameters of said methods into corresponding response message types of said operations; and a store code segment for causing said computer processor to store the translated output parameters. | 26. A computer readable storage medium encoded with a computer program code for directing a computer processor to transform instructions in an asynchronous transactional messaging language to instructions compatible with web services, said program code comprising: a translate proxy class code segment for causing said computer processor to iteratively translate, a predetermined number of times, proxy class instructions of said asynchronous transactional messaging language into corresponding port type instructions compatible with said web services, wherein said predetermined number is determined in accordance with a level of dependency of variables within said asynchronous transactional messaging language; a translate method code segment for causing said computer processor to translate methods of said proxy class instructions into corresponding operations of said port types; a translate input parameter code segment for causing said computer processor to translate input parameters of said methods into corresponding request message types of said operations; a translate output parameter code segment for causing said computer processor to translate output parameters of said methods into corresponding response message types of said operations; and a store code segment for causing said computer processor to store the translated output parameters. 31. A computer readable storage medium in accordance with claim 26 , wherein said asynchronous transactional messaging is XLANG/s. | 0.935 |
5,500,931 | 11 | 16 | 11. A method for applying a first font style to a text string comprised of a plurality of characters, each of the plurality of characters having an associated font style and the text string containing at least one predetermined special character, the apparatus being operable on a computer with a storage for storing the text string, the method comprising the steps of: (a) sequentially examining each of the plurality of characters to detect predetermined special characters; (b) applying the first font style to a each examined character which is not a special character; (c) determining a current font style associated with an examined special character; (d) obtaining a previous font style associated with a character preceding the examined special character and obtaining a next font style associated with a character following the examined special character; and (e) applying the first font style to the examined special character, based on the previous font style, the next font style and the current font style. | 11. A method for applying a first font style to a text string comprised of a plurality of characters, each of the plurality of characters having an associated font style and the text string containing at least one predetermined special character, the apparatus being operable on a computer with a storage for storing the text string, the method comprising the steps of: (a) sequentially examining each of the plurality of characters to detect predetermined special characters; (b) applying the first font style to a each examined character which is not a special character; (c) determining a current font style associated with an examined special character; (d) obtaining a previous font style associated with a character preceding the examined special character and obtaining a next font style associated with a character following the examined special character; and (e) applying the first font style to the examined special character, based on the previous font style, the next font style and the current font style. 16. The method as recited in claim 11, wherein step (a) comprises the step of: (a1) examining the plurality of characters to detect special characters including spaces and punctuation characters. | 0.865887 |
9,485,207 | 1 | 3 | 1. A computing system for message processing, comprising: at least one processor coupled with at least one storage device, wherein the at least one processor is to operate: receiver logic to receive a message addressed to a user; analysis logic, operatively coupled with the receiver logic, to determine whether the received message has a theme that is similar to a theme of a message collection, comprising one or more previously detected messages including an index message, wherein the message collection and the received message have a similar theme when the messages in the message collection have a common sender or have common content as the received message, and wherein the analysis logic is to define the theme of the message collection according to a sender and a modality of the index message, wherein the index message is a first message received by the receiver logic at a beginning of a predetermined window of time; modality logic, operatively coupled with the receiver logic, to identify a messaging modality associated with each of the messages in the message collection, wherein the messaging modality comprises a mode in which each of the messages in the message collection was sent including one of e-mail, social media, phone call, calendar invitation, text message, Internet service message, microblog message, chat message, or voicemail; criteria logic, operatively coupled with the modality logic, to determine whether the message collection satisfies modality criteria, wherein the modality criteria specify that at least two different messaging modalities be associated with messages in the message collection, wherein the at least two different messaging modalities comprise two or more of e-mail, social media messaging, phone, calendar invitations, text messaging Internet service messaging, microblog messaging, chat messaging, or voicemail; and notification logic, operatively coupled with the criteria logic, to provide a notification of the message collection in response to a determination that the message collection has a similar theme and a determination that the message collection satisfies the modality criteria. | 1. A computing system for message processing, comprising: at least one processor coupled with at least one storage device, wherein the at least one processor is to operate: receiver logic to receive a message addressed to a user; analysis logic, operatively coupled with the receiver logic, to determine whether the received message has a theme that is similar to a theme of a message collection, comprising one or more previously detected messages including an index message, wherein the message collection and the received message have a similar theme when the messages in the message collection have a common sender or have common content as the received message, and wherein the analysis logic is to define the theme of the message collection according to a sender and a modality of the index message, wherein the index message is a first message received by the receiver logic at a beginning of a predetermined window of time; modality logic, operatively coupled with the receiver logic, to identify a messaging modality associated with each of the messages in the message collection, wherein the messaging modality comprises a mode in which each of the messages in the message collection was sent including one of e-mail, social media, phone call, calendar invitation, text message, Internet service message, microblog message, chat message, or voicemail; criteria logic, operatively coupled with the modality logic, to determine whether the message collection satisfies modality criteria, wherein the modality criteria specify that at least two different messaging modalities be associated with messages in the message collection, wherein the at least two different messaging modalities comprise two or more of e-mail, social media messaging, phone, calendar invitations, text messaging Internet service messaging, microblog messaging, chat messaging, or voicemail; and notification logic, operatively coupled with the criteria logic, to provide a notification of the message collection in response to a determination that the message collection has a similar theme and a determination that the message collection satisfies the modality criteria. 3. The computing system of claim 1 , wherein the receiver logic is located in a personal computing device associated with the user. | 0.85636 |
5,455,951 | 5 | 7 | 5. A method for providing an object-oriented application including object-oriented statements an interface to a procedural operating system residing on a host computer with a memory component in the computer and a code library stored in the memory component, comprising the steps of: (a) implementing an object-oriented class library, the object-oriented class library comprising classes for requesting services provided by the procedural operating system; (b) providing said classes to said object-oriented application at application run-time; and (c) executing methods in said classes called by said application program by invoking procedural function calls corresponding to said methods called by said object-oriented application to provide an interface to said procedural operating system. | 5. A method for providing an object-oriented application including object-oriented statements an interface to a procedural operating system residing on a host computer with a memory component in the computer and a code library stored in the memory component, comprising the steps of: (a) implementing an object-oriented class library, the object-oriented class library comprising classes for requesting services provided by the procedural operating system; (b) providing said classes to said object-oriented application at application run-time; and (c) executing methods in said classes called by said application program by invoking procedural function calls corresponding to said methods called by said object-oriented application to provide an interface to said procedural operating system. 7. The method of claim 5, wherein said code library comprises an object-oriented class which includes as data a name port object which contains methods for obtaining information relating to said host computer, and for obtaining a list of processors assigned to said host computer. | 0.692982 |
9,563,646 | 15 | 16 | 15. A computer-implemented system, comprising: an input device enabled to generate an idea-image association that associates an image with an idea based on data that indicates user interaction with the image in a presentation of search results that correspond to a first search query, wherein the idea is determined to be related to the first search query; a database enabled to store the idea-image association and other idea-image associations; and a processor enabled to provide the image for display in a presentation of search results that correspond to a different, second search query, wherein the processor is enabled to select the image for display in the presentation of search results that correspond to the second search query based on (i) determining that the second search query relates to the idea and (ii) identifying from the stored idea-image association that a match exists between the idea that the second search query relates to and the idea to which the image is associated. | 15. A computer-implemented system, comprising: an input device enabled to generate an idea-image association that associates an image with an idea based on data that indicates user interaction with the image in a presentation of search results that correspond to a first search query, wherein the idea is determined to be related to the first search query; a database enabled to store the idea-image association and other idea-image associations; and a processor enabled to provide the image for display in a presentation of search results that correspond to a different, second search query, wherein the processor is enabled to select the image for display in the presentation of search results that correspond to the second search query based on (i) determining that the second search query relates to the idea and (ii) identifying from the stored idea-image association that a match exists between the idea that the second search query relates to and the idea to which the image is associated. 16. The system of claim 15 , wherein the processor is further enabled to determine that the second search query relates to the idea by correlating the idea with a concept described by the search query. | 0.728378 |
9,135,248 | 6 | 7 | 6. The method of claim 5 , further comprising: generating, by the computer system, a plurality of recommendations based on the first demographic profile for the first context, and sending, by the computer system, the plurality of recommendations to a portion of the plurality of mobile electronic devices, wherein the plurality of recommendations are based on the demographic profile for the first context. | 6. The method of claim 5 , further comprising: generating, by the computer system, a plurality of recommendations based on the first demographic profile for the first context, and sending, by the computer system, the plurality of recommendations to a portion of the plurality of mobile electronic devices, wherein the plurality of recommendations are based on the demographic profile for the first context. 7. The method of claim 6 , further comprising: determining, by the computer system, a second context in the plurality of contexts; determining, by the computer system, a second portion of the demographic data determined to include context data that matches the second context; analyzing, by the computer system, the implicit demographic data in the second portion of the demographic data to generate a plurality of demographic characteristics for the second context; and generating, by the computer system, a second demographic profile for the second context based on the plurality of demographic characteristics for the second context. | 0.5 |
8,156,117 | 1 | 19 | 1. A system for storing, searching and retrieval of a plurality of information objects of an arbitrary application domain, comprising: a distributed computer system comprising one or a plurality of computing devices connected with each other by communication lines, a connected logical storage network, wherein each node is an active unit of storage (AUS) and connections between nodes of said network are formed by links of one active units of storage to others, wherein every active unit of storage resides on one of the computing devices of said distributed computer system and comprises: at least one of said plurality of information objects (IOs), each of which is represented in a tree-like structure, a list of links to a certain plurality of other active units of storage by means of which said AUS participates in the operation of the logical storage network, and an associated program agent that allows performing operations on said AUS in connection with searching, storing and retrieving information by user requests using said list of links, wherein a program agent of each active unit of storage compares the IO incorporated into it with the IO of any other AUS and based on the comparison results computes the value of metric distance between the compared IOs and the IOs are electronic documents in the form of XML documents. | 1. A system for storing, searching and retrieval of a plurality of information objects of an arbitrary application domain, comprising: a distributed computer system comprising one or a plurality of computing devices connected with each other by communication lines, a connected logical storage network, wherein each node is an active unit of storage (AUS) and connections between nodes of said network are formed by links of one active units of storage to others, wherein every active unit of storage resides on one of the computing devices of said distributed computer system and comprises: at least one of said plurality of information objects (IOs), each of which is represented in a tree-like structure, a list of links to a certain plurality of other active units of storage by means of which said AUS participates in the operation of the logical storage network, and an associated program agent that allows performing operations on said AUS in connection with searching, storing and retrieving information by user requests using said list of links, wherein a program agent of each active unit of storage compares the IO incorporated into it with the IO of any other AUS and based on the comparison results computes the value of metric distance between the compared IOs and the IOs are electronic documents in the form of XML documents. 19. The system according to claim 1 , wherein the metric distance between two IOs is defined as a matrix of size n 1 ×n 2 : {ρ(T 1 ,r 1 ,T 2 ,r 2 )} n 1× n 2 ,where T 1 , T 2 are rooted trees modeling the intrinsic structure of compared IOs, r 1 , r 2 are two nodes (from T 1 and T 2 respectively), designated as temporary roots, n 1 and n 2 are the number of nodes in the structure of the first and second IO respectively; therewith ρ(T 1 ,r 1 ,T 2 ,r 2 )=(c(T 1 ,r 1 ,T 2 ,r 2 )) α , where c(T 1 ,r 1 ,T 2 ,r 2 ) is the similarity measure equal to the power (number of nodes) of the largest subtree common for two compared IO trees isomorphically transformed relative to designated temporary roots r 1 and r 2 , respectively, and α is a numeric parameter assuming values α<−1. | 0.692003 |
8,682,907 | 25 | 34 | 25. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: selecting a first term and a second term; determining, for each of one or more first co-occurring terms that occur in past search queries that include the first term, a first co-occurrence frequency of the co-occurring term in search queries that include the first term; generating a first vector for the first term using the first co-occurrence frequencies; determining, for each of one or more second co-occurring terms that occur in past search queries that include the first term adjacent to the second term, a second co-occurrence frequency of the co-occurring term in the search queries that include the first term adjacent to the second term; generating a second vector for the second term using the second co-occurrence frequencies; comparing the first vector and the second vector; and computing a score for the second term as a context for a substitution rule based on the first term, wherein the score is based on a comparison between the first vector and the second vector. | 25. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: selecting a first term and a second term; determining, for each of one or more first co-occurring terms that occur in past search queries that include the first term, a first co-occurrence frequency of the co-occurring term in search queries that include the first term; generating a first vector for the first term using the first co-occurrence frequencies; determining, for each of one or more second co-occurring terms that occur in past search queries that include the first term adjacent to the second term, a second co-occurrence frequency of the co-occurring term in the search queries that include the first term adjacent to the second term; generating a second vector for the second term using the second co-occurrence frequencies; comparing the first vector and the second vector; and computing a score for the second term as a context for a substitution rule based on the first term, wherein the score is based on a comparison between the first vector and the second vector. 34. The computer-readable medium of claim 25 , wherein the operations further comprise: determining that the score satisfies a threshold; and designating the second term as a bad context for the first term in response to determining that the score satisfies a threshold. | 0.693878 |
7,772,478 | 10 | 12 | 10. The method for understanding music of claim 6 , wherein extracting a plurality of salient terms further comprises downloading a predetermined number of text pages relating to each music sample extracting terms from each downloaded text page computing the salience of each extracted term selecting the plurality of salient terms, where each salient term has a salience greater than a predetermined threshold constructing a truth vector for each term of the plurality of salient terms. | 10. The method for understanding music of claim 6 , wherein extracting a plurality of salient terms further comprises downloading a predetermined number of text pages relating to each music sample extracting terms from each downloaded text page computing the salience of each extracted term selecting the plurality of salient terms, where each salient term has a salience greater than a predetermined threshold constructing a truth vector for each term of the plurality of salient terms. 12. The method for understanding music of claim 10 , wherein computing the salience of each extracted term further comprises computing a Gaussian-weighted term frequency for each extracted term. | 0.738544 |
8,270,733 | 1 | 4 | 1. A computer-implemented method for identifying anomaly object types during classification of image data captured by a video camera, the method comprising: receiving a micro-feature vector including multiple micro-feature values, each micro-feature value based on at least one pixel-level characteristic of a foreground patch that depicts a foreground object within the image data; classifying the foreground object as depicting a first object type corresponding to a first object type cluster of the object type clusters based on the micro-feature vector; computing a probability density function for the object type clusters; computing a probability density value for the micro-feature vector; evaluating a rareness measure of the micro-feature vector, wherein the rareness measure estimates a likelihood of observing the micro-feature vector, based on the probability density function and the probability density value; and identifying the foreground object as an anomaly object type when the rareness measure is below a specified threshold. | 1. A computer-implemented method for identifying anomaly object types during classification of image data captured by a video camera, the method comprising: receiving a micro-feature vector including multiple micro-feature values, each micro-feature value based on at least one pixel-level characteristic of a foreground patch that depicts a foreground object within the image data; classifying the foreground object as depicting a first object type corresponding to a first object type cluster of the object type clusters based on the micro-feature vector; computing a probability density function for the object type clusters; computing a probability density value for the micro-feature vector; evaluating a rareness measure of the micro-feature vector, wherein the rareness measure estimates a likelihood of observing the micro-feature vector, based on the probability density function and the probability density value; and identifying the foreground object as an anomaly object type when the rareness measure is below a specified threshold. 4. The computer-implemented method of claim 1 , further comprising processing the micro-feature vector by a self-organizing map adaptive resonance theory (SOM-ART) network to discover the object type clusters for the image data. | 0.597173 |
4,773,099 | 1 | 8 | 1. A method for processing reference feature vectors comprising the steps of: obtaining reference feature vectors defining a plurality of references; assigning said references to a plurality of classes, each of said classes containing a plurality of references; and forming a plurality of sets of clusters, each said set of clusters being uniquely associated with an associated class, such that each said set has associated therewith all of said reference feature vectors for its associated class, wherein the number of said clusters is significantly less than the number of said reference feature vectors, and wherein each cluster of said set of clusters has associated therewith any number of regions selected from the group of regions consisting of: a possibility region, such that all said reference feature vectors of said associated class of a selected set of clusters are contained in at least one of said possibility region contains relatively few reference feature vectors not belonging to said associated class; and a certainty region in which is contained a plurality of said reference feature vectors which all belong to said associated class of said cluster and which do not contain reference feature vectors which are not of said selected class. | 1. A method for processing reference feature vectors comprising the steps of: obtaining reference feature vectors defining a plurality of references; assigning said references to a plurality of classes, each of said classes containing a plurality of references; and forming a plurality of sets of clusters, each said set of clusters being uniquely associated with an associated class, such that each said set has associated therewith all of said reference feature vectors for its associated class, wherein the number of said clusters is significantly less than the number of said reference feature vectors, and wherein each cluster of said set of clusters has associated therewith any number of regions selected from the group of regions consisting of: a possibility region, such that all said reference feature vectors of said associated class of a selected set of clusters are contained in at least one of said possibility region contains relatively few reference feature vectors not belonging to said associated class; and a certainty region in which is contained a plurality of said reference feature vectors which all belong to said associated class of said cluster and which do not contain reference feature vectors which are not of said selected class. 8. The method of claim 1 wherein said step of forming a plurality of sets of clusters includes the step of forming a plurality of sets of certainty regions which comprises the steps of: selecting one of said classes; and selecting a number of said reference feature vectors belonging to said selected class such that each reference feature vector of said number of reference feature vectors forms the center of one certainty region of a set of certainty regions associated with said selected class and such that substantially all reference feature vectors of said selected class are contained in a certainty region for said selected class. | 0.5 |
9,219,746 | 11 | 12 | 11. The apparatus of claim 8 , further including instructions that, when executed, cause the apparatus to identify an additional action to implement based on the identified risk rating. | 11. The apparatus of claim 8 , further including instructions that, when executed, cause the apparatus to identify an additional action to implement based on the identified risk rating. 12. The apparatus of claim 11 , wherein the additional action includes altering access to information available to a user associated with the string of terms. | 0.5 |
8,218,859 | 5 | 6 | 5. The method of claim 1 , wherein the grouping the labels into several parts to speed up a labeling inference comprises using a label chunklet analysis to categorize the labels into several subsets. | 5. The method of claim 1 , wherein the grouping the labels into several parts to speed up a labeling inference comprises using a label chunklet analysis to categorize the labels into several subsets. 6. The method of claim 5 , wherein the label chunklet analysis further comprises: measuring a relationship between each pair of labels; pursuing common concepts that have large relationship degrees with other concepts; and dividing remaining concepts into several chunklets, wherein a relationship between chunklets that are different is smaller and a relationship within a chunklet is larger. | 0.5 |
7,627,558 | 8 | 9 | 8. A computer-readable storage medium carrying computer-executable instructions configured to cause a data processing system to perform a method of searching a database having a plurality of information objects, the computer-executable instructions comprising: code for receiving from a client computer connected to the data processing system a first query with one or more keywords; code for determining that the one or more keywords are members of a predetermined master keyword list, wherein each member of the master keyword list has a relevance rating, wherein the relevance rating represents a degree of relevance between a keyword and an information object, wherein each of the one or more keywords is associated with at least a friend keyword in the master keyword list, wherein each keyword-friend pair in the master keyword list has an association score, wherein the association score represents a degree of association between a keyword and a friend keyword; code for retrieving friend keywords associated with the one or more keywords from a keyword-friend table stored in the database; code for automatically expanding the first query to a second query to include the one or more keywords and their friend keywords having association scores that meet or exceed a set value, wherein the second query includes at least one keyword that is not in the first query; code for searching the database using the second query; code for identifying from the plurality of information objects in the database a set of information objects that correspond to the one or more keywords and their friend keywords in the second query; and code for sending the set of information objects or a derivative thereof to the client computer. | 8. A computer-readable storage medium carrying computer-executable instructions configured to cause a data processing system to perform a method of searching a database having a plurality of information objects, the computer-executable instructions comprising: code for receiving from a client computer connected to the data processing system a first query with one or more keywords; code for determining that the one or more keywords are members of a predetermined master keyword list, wherein each member of the master keyword list has a relevance rating, wherein the relevance rating represents a degree of relevance between a keyword and an information object, wherein each of the one or more keywords is associated with at least a friend keyword in the master keyword list, wherein each keyword-friend pair in the master keyword list has an association score, wherein the association score represents a degree of association between a keyword and a friend keyword; code for retrieving friend keywords associated with the one or more keywords from a keyword-friend table stored in the database; code for automatically expanding the first query to a second query to include the one or more keywords and their friend keywords having association scores that meet or exceed a set value, wherein the second query includes at least one keyword that is not in the first query; code for searching the database using the second query; code for identifying from the plurality of information objects in the database a set of information objects that correspond to the one or more keywords and their friend keywords in the second query; and code for sending the set of information objects or a derivative thereof to the client computer. 9. The computer-readable storage medium of claim 8 , wherein the computer-executable instructions further comprise: code for determining a relevance score for each information object in the set of information objects that correspond to the one or more keywords and their friend keywords in the second query; code for sorting the set of information objects based on their relevance scores; and code for sending the sorted information objects or a derivative thereof to the client computer. | 0.512974 |
9,317,589 | 19 | 20 | 19. The system of claim 18 , wherein selecting the first word usage sense from the plurality of word usage senses associated with the first search term, comprises: for each of the plurality of word usage senses: determining a plurality of lexical component scores by applying a plurality of lexical analysis techniques using a respective word usage sense and a context window of words surrounding the first search term, applying a weighting factor to each lexical component score, and adding the lexical component scores to determine a total score for a respective word usage sense; and selecting the word usage sense with a highest total score as the first word usage sense. | 19. The system of claim 18 , wherein selecting the first word usage sense from the plurality of word usage senses associated with the first search term, comprises: for each of the plurality of word usage senses: determining a plurality of lexical component scores by applying a plurality of lexical analysis techniques using a respective word usage sense and a context window of words surrounding the first search term, applying a weighting factor to each lexical component score, and adding the lexical component scores to determine a total score for a respective word usage sense; and selecting the word usage sense with a highest total score as the first word usage sense. 20. The system of claim 19 , wherein one of the lexical analysis techniques comprises: identifying words in a definition of one of the respective word usage senses; and calculating a value based upon the number of words in the definition that match words in the context window of words. | 0.670507 |
9,672,618 | 8 | 10 | 8. A process for Dyslexia management, comprising: a user to login to a hardware that is connected with a network, database and a Dyslexia management system loaded to the processor of the hardware or the network to take a test for evaluating a condition for diagnosing symptoms for Dyslexia; wherein the test consists of several modules for reading, writing, drawing, spelling and listening skills, family drawing, and letter writing; a Dyslexia analytics system housed on a backend server or a processor to auto grade a test result using specific equation for a reading, writing, drawing, spelling and listening skills, family drawing, and letter writing test wherein the specific formula for interpretation and presentation of the test for module for reading, writing, drawing is done using Equations 1-4 in sequence, wherein Equation 1 is: x=a+by+cy 2 , where a, b, and c are as follows: a = Σ x Σ y Σ y 2 Σ xy Σ y 2 Σ y 3 Σ xy 2 Σ y 3 Σ y 4 N Σ y Σ y 2 Σ y Σ y 2 Σ y 3 Σ y 2 Σ y 3 Σ y 4 b = N Σ x Σ y 2 Σ y Σ xy Σ y 3 Σ y 2 Σ xy 2 Σ y 4 N Σ y Σ y 2 Σ y Σ y 2 Σ y 3 Σ y 2 Σ y 3 Σ y 4 c = N Σ y Σ x Σ y Σ y 2 Σ xy Σ y 2 Σ y 3 Σ xy 2 N Σ y Σ y 2 Σ y Σ y 2 Σ y 3 Σ y 2 Σ y 3 Σ y 4 Equation 2 is: κ=x 2 /(1+x 1 2 ) 3/2 where x 1 =dx/dy & x 2 =d 2 x/dy 2 Wherein equation 3: x=a+by y=mx+c form, we pet y=(x/b)−(a/b), so the slope of the line=1/b, where a, b are defined as follows: a = Σ x Σ y Σ xy Σ y 2 N Σ y Σ y Σ y 2 b = N Σ x Σ y Σ xy N Σ y Σ y Σ y 2 And, Equation 4
Sl=M (i,j) +max(( M (i+1,j) +M (i+2,j) ),( M (i+1,j) +M (i+2,j+1) ))
Sr=M (i,j) +max(( M (i,j+1) +M (i,j+2) ),( M (i,j+1) +M (i+1,j+2) ))
Sd=M (i,j) +( M (i+1,j+1) +max( M (i+1,j+2) ,( M (i+2,j+2) ,M (i+2,j+1) ) Where, Sl denotes a shift down, Sr denotes a Shift right, Sd denotes a Shift diagonally; and a doctor to review the test result using a doctor analyzer screen and rendering their opinion to the user by filtering and flagging each test module that shows symptoms of dyslexia and a treatment plan for the user. | 8. A process for Dyslexia management, comprising: a user to login to a hardware that is connected with a network, database and a Dyslexia management system loaded to the processor of the hardware or the network to take a test for evaluating a condition for diagnosing symptoms for Dyslexia; wherein the test consists of several modules for reading, writing, drawing, spelling and listening skills, family drawing, and letter writing; a Dyslexia analytics system housed on a backend server or a processor to auto grade a test result using specific equation for a reading, writing, drawing, spelling and listening skills, family drawing, and letter writing test wherein the specific formula for interpretation and presentation of the test for module for reading, writing, drawing is done using Equations 1-4 in sequence, wherein Equation 1 is: x=a+by+cy 2 , where a, b, and c are as follows: a = Σ x Σ y Σ y 2 Σ xy Σ y 2 Σ y 3 Σ xy 2 Σ y 3 Σ y 4 N Σ y Σ y 2 Σ y Σ y 2 Σ y 3 Σ y 2 Σ y 3 Σ y 4 b = N Σ x Σ y 2 Σ y Σ xy Σ y 3 Σ y 2 Σ xy 2 Σ y 4 N Σ y Σ y 2 Σ y Σ y 2 Σ y 3 Σ y 2 Σ y 3 Σ y 4 c = N Σ y Σ x Σ y Σ y 2 Σ xy Σ y 2 Σ y 3 Σ xy 2 N Σ y Σ y 2 Σ y Σ y 2 Σ y 3 Σ y 2 Σ y 3 Σ y 4 Equation 2 is: κ=x 2 /(1+x 1 2 ) 3/2 where x 1 =dx/dy & x 2 =d 2 x/dy 2 Wherein equation 3: x=a+by y=mx+c form, we pet y=(x/b)−(a/b), so the slope of the line=1/b, where a, b are defined as follows: a = Σ x Σ y Σ xy Σ y 2 N Σ y Σ y Σ y 2 b = N Σ x Σ y Σ xy N Σ y Σ y Σ y 2 And, Equation 4
Sl=M (i,j) +max(( M (i+1,j) +M (i+2,j) ),( M (i+1,j) +M (i+2,j+1) ))
Sr=M (i,j) +max(( M (i,j+1) +M (i,j+2) ),( M (i,j+1) +M (i+1,j+2) ))
Sd=M (i,j) +( M (i+1,j+1) +max( M (i+1,j+2) ,( M (i+2,j+2) ,M (i+2,j+1) ) Where, Sl denotes a shift down, Sr denotes a Shift right, Sd denotes a Shift diagonally; and a doctor to review the test result using a doctor analyzer screen and rendering their opinion to the user by filtering and flagging each test module that shows symptoms of dyslexia and a treatment plan for the user. 10. The process of claim 8 , wherein the test module is 20-minute long and has 4 different tests: reading test, writing test, clock drawing test, and cognitive test through drawing family members, all with an eye tracking and audio capturing capabilities. | 0.538043 |
8,229,730 | 1 | 2 | 1. One or more computer-readable media having computer-executable instructions embodied thereon for performing a method of expanding and indexing relationships between words within a sentence, the method comprising: receiving a first electronic document having content that includes text; breaking the text into one or more sentences; determining a first grammatical role for a word in the sentence; determining that the word has more than one potential grammatical role; assigning a second grammatical role to the word, wherein the second grammatical role is a subservient grammatical role to the first grammatical role, which is a dominant grammatical role, wherein the subservient grammatical role fits within a definition of the dominant grammatical role and has a more specific definition; and storing the word with the first grammatical role and the second grammatical role in an index that associates the word and the sentence with the first electronic document, thereby allowing a search engine to match the first electronic document with a search query that includes similar words having similar roles. | 1. One or more computer-readable media having computer-executable instructions embodied thereon for performing a method of expanding and indexing relationships between words within a sentence, the method comprising: receiving a first electronic document having content that includes text; breaking the text into one or more sentences; determining a first grammatical role for a word in the sentence; determining that the word has more than one potential grammatical role; assigning a second grammatical role to the word, wherein the second grammatical role is a subservient grammatical role to the first grammatical role, which is a dominant grammatical role, wherein the subservient grammatical role fits within a definition of the dominant grammatical role and has a more specific definition; and storing the word with the first grammatical role and the second grammatical role in an index that associates the word and the sentence with the first electronic document, thereby allowing a search engine to match the first electronic document with a search query that includes similar words having similar roles. 2. The media of claim 1 , wherein the method further comprises: receiving the search query containing the word; determining that the word is used in the first grammatical role within the search query; determining that the word has more than one potential grammatical role within the search query; and assigning a third grammatical role to the word. | 0.5 |
7,574,742 | 1 | 7 | 1. A computer data system, comprising: a database storing a plurality of signature strings; a memory storing computer instructions; a processor configured to execute the computer instructions to perform the operations of: assigning values to characters in the signature strings; calculating differences between the assigned values of the characters in the signature strings; identifying common features of the signature strings using the calculated differences; grouping the signature strings into signature groups according to the common features; receiving an input string into the memory; detecting predetermined features of the input string; comparing the predetermined features of the input string with the common features of one or more of the signature groups; and comparing the input string with one or more individual signature strings in one of the signature groups if the predetermined features of the input string match the common features of the one of the signature groups. | 1. A computer data system, comprising: a database storing a plurality of signature strings; a memory storing computer instructions; a processor configured to execute the computer instructions to perform the operations of: assigning values to characters in the signature strings; calculating differences between the assigned values of the characters in the signature strings; identifying common features of the signature strings using the calculated differences; grouping the signature strings into signature groups according to the common features; receiving an input string into the memory; detecting predetermined features of the input string; comparing the predetermined features of the input string with the common features of one or more of the signature groups; and comparing the input string with one or more individual signature strings in one of the signature groups if the predetermined features of the input string match the common features of the one of the signature groups. 7. The computer system of claim 1 , wherein the processor is further configured to: select a sample space for the predetermined features of the input string and the common features of the signature strings. | 0.596078 |
9,286,273 | 1 | 7 | 1. A computer-implemented method for automated generation of web sites, the method comprising: (a) generating a plurality of web page templates and storing them in a template library on a content server; (b) establishing a network connection between the content server and a client; launching a site builder application on a client, the site builder application comprising a plurality of site builder wizards configured to receive and process site content data; (c) acquiring the web page templates from the template library and rendering them to a user via a first site builder wizard; (d) rendering to the user a web page design choices via a second site builder wizard; providing a third site builder wizard to a user for selecting a web page structure; presenting a user with a wizard for filling in a web page text and graphics; generating a preview of the web page and rendering it to the user; (e) sending the web page to a specialist for a usability assessment; and (f) publishing the web page upon completion of the usability assessment, wherein: the templates are generated based on keywords and weight coefficients of the keywords, and each set of the keywords provides a basic web page color scheme using a color scheme shift vector; and wherein the shift vector adjusts the web page color scheme on an element by element basis and adjusts a positioning of the elements on the web page based on the keywords and the weight coefficients. | 1. A computer-implemented method for automated generation of web sites, the method comprising: (a) generating a plurality of web page templates and storing them in a template library on a content server; (b) establishing a network connection between the content server and a client; launching a site builder application on a client, the site builder application comprising a plurality of site builder wizards configured to receive and process site content data; (c) acquiring the web page templates from the template library and rendering them to a user via a first site builder wizard; (d) rendering to the user a web page design choices via a second site builder wizard; providing a third site builder wizard to a user for selecting a web page structure; presenting a user with a wizard for filling in a web page text and graphics; generating a preview of the web page and rendering it to the user; (e) sending the web page to a specialist for a usability assessment; and (f) publishing the web page upon completion of the usability assessment, wherein: the templates are generated based on keywords and weight coefficients of the keywords, and each set of the keywords provides a basic web page color scheme using a color scheme shift vector; and wherein the shift vector adjusts the web page color scheme on an element by element basis and adjusts a positioning of the elements on the web page based on the keywords and the weight coefficients. 7. The method of claim 1 , wherein the user can insert video into the web page. | 0.760606 |
9,098,599 | 8 | 11 | 8. The system of claim 7 , wherein the first set of search query suggestions are based, in part, on search history data that includes data from and related to previous search requests associated with the search query. | 8. The system of claim 7 , wherein the first set of search query suggestions are based, in part, on search history data that includes data from and related to previous search requests associated with the search query. 11. The system of claim 8 , wherein: receiving a first set of search query suggestions for a search query for display on a user device with a first resource determined to be responsive to the search query comprises receiving the first set of search query suggestions for the search query with first resource at the user device; and the search history data is search history data stored at the user device. | 0.5 |
8,046,387 | 11 | 12 | 11. The system of claim 9 , wherein the search engine includes at least one table-based wizard configured to ask a number of questions, to provide a list of potential answers to the questions for selection, and to use the selected answers from the list to search for electronic content within the content repository. | 11. The system of claim 9 , wherein the search engine includes at least one table-based wizard configured to ask a number of questions, to provide a list of potential answers to the questions for selection, and to use the selected answers from the list to search for electronic content within the content repository. 12. The system of claim 11 , wherein the portal content interface of the communication portal developer is configured to use the at least one table-based wizard to provide the list of electronic content associated with the selected audience for potential publication to the portal. | 0.5 |
9,177,018 | 13 | 14 | 13. The system of claim 10 , wherein obtaining one or more selected translations for the first image search query comprises: receiving a plurality of candidate translations of the first image search query; determining a score for each candidate translation; and selecting the translations from the candidate translations according to the scores. | 13. The system of claim 10 , wherein obtaining one or more selected translations for the first image search query comprises: receiving a plurality of candidate translations of the first image search query; determining a score for each candidate translation; and selecting the translations from the candidate translations according to the scores. 14. The system of claim 13 , wherein determining a score for a candidate translation comprises determining the score for the candidate translation from a frequency of submission measurement that measures how often the candidate translation is received from users as an image search query. | 0.625 |
8,578,346 | 10 | 11 | 10. A system, as in claim 1 , wherein: one or more of the diagram elements corresponds to one or more of a: node, edge, and label; further including identifying unlinked labels and dangling edges as the errors in the filtered flow graph; and for each unlinked label and dangling edge providing, respectively, an unlinked label record containing an error description relating to the unlinked labels, a fix description relating to the unlinked labels, and a confidence level and a connector errors and fixes record containing dangling edge errors, fix descriptions relating to the dangling edges, and confidence levels relating to the fix descriptions. | 10. A system, as in claim 1 , wherein: one or more of the diagram elements corresponds to one or more of a: node, edge, and label; further including identifying unlinked labels and dangling edges as the errors in the filtered flow graph; and for each unlinked label and dangling edge providing, respectively, an unlinked label record containing an error description relating to the unlinked labels, a fix description relating to the unlinked labels, and a confidence level and a connector errors and fixes record containing dangling edge errors, fix descriptions relating to the dangling edges, and confidence levels relating to the fix descriptions. 11. A system, as in claim 10 wherein the one or more processors are further operative to perform a process flow repair process that comprises the steps of: a. comparing a confidence threshold to one or more of the confidence levels ; b. if one or more unlinked label records have a confidence level that meet or exceed the confidence threshold, applying a fix described by the respective fix description having a highest confidence level to the respective unlinked label, the fix causing association of the unlinked label with a selected node or edge; c. repeating step b until all errors having an error description have a fix or there is a failed list of unlinked labels with respective confidence levels that do not meet the confidence threshold; d. displaying one or more of the respective error descriptions and one or more fix descriptions to a user; e. receiving a selection of a fix description for the unlinked label from the user and applying a fix described by the selected fix description to the respective unlinked label, the fix causing association of the unlinked label with a selected node or edge; f. repeating steps d and e until the user stops selecting; and g. outputting a corrected flow graph being the flow graph with the fixes. | 0.5 |
8,493,609 | 19 | 21 | 19. A printing device comprising: a control and processing section; an input tray for holding printing sheets; an insert sheet tray for holding insert sheets; and a print engine connected to the control and processing section for forming an image on a recording medium, wherein the control and processing section is programmed to receive data representing a document to be printed in the print job, to receive job information about the print job, the job information including an instruction to print multiple copies of the document, to control the print engine to print the requested multiple copies of the document using the printing sheets from the input tray, to determine whether insert sheets are available in the insert sheet tray, to control the printing device to insert insert sheets from the insert sheet tray between printed copies of the document if insert sheets are available in the insert sheet tray, and to control the print engine to print one or more simulated insert sheets using the printing sheets from the input tray as a substitute and insert them between printed copies of the document if insert sheets are unavailable in the insert sheet tray. | 19. A printing device comprising: a control and processing section; an input tray for holding printing sheets; an insert sheet tray for holding insert sheets; and a print engine connected to the control and processing section for forming an image on a recording medium, wherein the control and processing section is programmed to receive data representing a document to be printed in the print job, to receive job information about the print job, the job information including an instruction to print multiple copies of the document, to control the print engine to print the requested multiple copies of the document using the printing sheets from the input tray, to determine whether insert sheets are available in the insert sheet tray, to control the printing device to insert insert sheets from the insert sheet tray between printed copies of the document if insert sheets are available in the insert sheet tray, and to control the print engine to print one or more simulated insert sheets using the printing sheets from the input tray as a substitute and insert them between printed copies of the document if insert sheets are unavailable in the insert sheet tray. 21. The printing device of claim 19 , wherein the simulated insert sheets are printed in accordance with default layout and content previously stored in the printing device. | 0.703767 |
8,161,043 | 2 | 4 | 2. The interactive program search apparatus according to claim 1 , wherein said obtaining unit is configured to further obtain an instruction to provisionally select one of the program search results displayed on said display unit, said interactive program search apparatus further comprises a provisional selection search unit configured to search out one of the programs from the program information using program information of a provisionally selected program and the obtainment history information, and determine the searched-out program to be the provisionally selected program, said association-source word extracting unit is configured to extract the association-source word, based on the obtainment history information and the program information of the provisionally selected program, and said associated word extracting unit is configured to extract the associated word associated with the association-source word in the association dictionary, from among words included in the program information of the provisionally selected program. | 2. The interactive program search apparatus according to claim 1 , wherein said obtaining unit is configured to further obtain an instruction to provisionally select one of the program search results displayed on said display unit, said interactive program search apparatus further comprises a provisional selection search unit configured to search out one of the programs from the program information using program information of a provisionally selected program and the obtainment history information, and determine the searched-out program to be the provisionally selected program, said association-source word extracting unit is configured to extract the association-source word, based on the obtainment history information and the program information of the provisionally selected program, and said associated word extracting unit is configured to extract the associated word associated with the association-source word in the association dictionary, from among words included in the program information of the provisionally selected program. 4. The interactive program search apparatus according to claim 2 , wherein said associated word extracting unit is configured to extract words associated with the association-source word in the association dictionary from among the words included in the program information of the provisionally selected program, and extract, as the associated word, a word included in the obtainment history information from among the extracted words. | 0.5 |
8,832,126 | 1 | 5 | 1. A method of suggesting custodians subject to a litigation hold, comprising: receiving a set of keywords or queries; identifying, by one or more processing devices, a set of documents relevant to the set of keywords or queries; identifying, by one or more processing devices, one or more custodians associated with one or more documents in the set of documents; and determining a set of one or more candidates for the litigation hold from the identified one or more custodians based upon a comparison of the identified one or more custodians to a known set of one or more custodians relevant to the litigation hold, wherein each of the identified one or more custodians that is external to the known set of one or more custodians is added to the set of one or more candidates, providing, by the one or more processing devices, the determined set of one or more candidates for the litigation hold to a user. | 1. A method of suggesting custodians subject to a litigation hold, comprising: receiving a set of keywords or queries; identifying, by one or more processing devices, a set of documents relevant to the set of keywords or queries; identifying, by one or more processing devices, one or more custodians associated with one or more documents in the set of documents; and determining a set of one or more candidates for the litigation hold from the identified one or more custodians based upon a comparison of the identified one or more custodians to a known set of one or more custodians relevant to the litigation hold, wherein each of the identified one or more custodians that is external to the known set of one or more custodians is added to the set of one or more candidates, providing, by the one or more processing devices, the determined set of one or more candidates for the litigation hold to a user. 5. The method of claim 1 , wherein the at least one of the identified one or more custodians is identified in the name of a document. | 0.851563 |
9,053,392 | 3 | 5 | 3. The method of claim 2 , wherein the computing of the affinity matrix includes: calculating a feature vector of an image that depicts the visual pattern; calculating vector distances between the visual pattern and other visual patterns in the reference set based on the feature vector; and including representations of the vector distances in the affinity matrix as quantifiers of similarity between the visual pattern and the other visual patterns. | 3. The method of claim 2 , wherein the computing of the affinity matrix includes: calculating a feature vector of an image that depicts the visual pattern; calculating vector distances between the visual pattern and other visual patterns in the reference set based on the feature vector; and including representations of the vector distances in the affinity matrix as quantifiers of similarity between the visual pattern and the other visual patterns. 5. The method of claim 3 , wherein the computing of the affinity matrix includes: increasing sparseness of the affinity matrix by setting a representation of a vector distance to zero based on the representation falling below a minimum threshold value. | 0.577181 |
9,288,039 | 1 | 2 | 1. A method for text language identification comprising: at a server, receiving an encrypted score for each of a plurality of languages from a client, the encrypted scores having been generated by homomorphic addition of encrypted frequencies of n-grams in a list of n-grams extracted from text at the client, wherein the list is not provided to the server, the encrypted frequencies of the n-grams in the list having been extracted based on encrypted resources which, for each of the plurality of languages, include an encrypted frequency for each of a set of n-grams; at the server, decrypting the encrypted scores to generate unencrypted scores; and providing information to the client based on the unencrypted scores from which the client is able to identify a language for the text, wherein at least one of the decrypting of the encrypted scores and the providing information is performed by a processor. | 1. A method for text language identification comprising: at a server, receiving an encrypted score for each of a plurality of languages from a client, the encrypted scores having been generated by homomorphic addition of encrypted frequencies of n-grams in a list of n-grams extracted from text at the client, wherein the list is not provided to the server, the encrypted frequencies of the n-grams in the list having been extracted based on encrypted resources which, for each of the plurality of languages, include an encrypted frequency for each of a set of n-grams; at the server, decrypting the encrypted scores to generate unencrypted scores; and providing information to the client based on the unencrypted scores from which the client is able to identify a language for the text, wherein at least one of the decrypting of the encrypted scores and the providing information is performed by a processor. 2. The method of claim 1 , wherein the encrypted resources are provided to the client. | 0.833333 |
8,600,954 | 1 | 4 | 1. A non-transitory computer-readable medium comprising: one or more instructions which, when executed by at least one processor, cause the at least one processor to retrieve a model, the model being received from a user device; one or more instructions which, when executed by the at least one processor, cause the at least one processor to execute the model using a program to determine whether an issue exists with the model or with the program; one or more instructions which, when executed by the at least one processor, cause the at least one processor to cause the model to be made available to one or more users when no issue exists with the model or with the program; one or more instructions which, when executed by the at least one processor, cause the at least one processor to cause information to be presented at the user device when the issue exists with the model, the information indicating that the issue exists with the model; one or more instructions which, when executed by the at least one processor, cause the at least one processor to receive, from the user device, a response to the information indicating that the issue exists with the model, the response indicating that the model, with the issue, is to be made available to the one or more users; and one or more instructions which, when executed by the at least one processor, cause the at least one processor to cause the model, with the issue, to be made available to the one or more users based on receiving the response indicating that the model, with the issue, is to be made available to the one or more users. | 1. A non-transitory computer-readable medium comprising: one or more instructions which, when executed by at least one processor, cause the at least one processor to retrieve a model, the model being received from a user device; one or more instructions which, when executed by the at least one processor, cause the at least one processor to execute the model using a program to determine whether an issue exists with the model or with the program; one or more instructions which, when executed by the at least one processor, cause the at least one processor to cause the model to be made available to one or more users when no issue exists with the model or with the program; one or more instructions which, when executed by the at least one processor, cause the at least one processor to cause information to be presented at the user device when the issue exists with the model, the information indicating that the issue exists with the model; one or more instructions which, when executed by the at least one processor, cause the at least one processor to receive, from the user device, a response to the information indicating that the issue exists with the model, the response indicating that the model, with the issue, is to be made available to the one or more users; and one or more instructions which, when executed by the at least one processor, cause the at least one processor to cause the model, with the issue, to be made available to the one or more users based on receiving the response indicating that the model, with the issue, is to be made available to the one or more users. 4. The non-transitory computer-readable medium of claim 1 , where the model is executed based on at least one of: one or more data types that are associated with the model, or interface timing information that is associated with the model. | 0.829286 |
9,715,879 | 2 | 4 | 2. The method of claim 1 , the method further comprising: determining that the one or more detected voice command text files are associated with a first executable action of the computing device. | 2. The method of claim 1 , the method further comprising: determining that the one or more detected voice command text files are associated with a first executable action of the computing device. 4. The method of claim 2 , wherein one or more executable actions of the computing device are defined by an operating system of the computing device, and wherein the executable actions are executable by one or more applications installed on the computing device. | 0.801515 |
10,032,071 | 12 | 13 | 12. The electronic device of claim 11 , wherein the instructions are executable by the processor to: select, from the plurality of handwriting recognition results, a machine input word; wherein the generating comprises, generating a list comprising at least one candidate word; and wherein the providing comprises, providing the generated list. | 12. The electronic device of claim 11 , wherein the instructions are executable by the processor to: select, from the plurality of handwriting recognition results, a machine input word; wherein the generating comprises, generating a list comprising at least one candidate word; and wherein the providing comprises, providing the generated list. 13. The electronic device of claim 12 , wherein the instructions are executable by the processor to: filter the list comprising at least one candidate word prior to the providing. | 0.58945 |
8,339,357 | 11 | 15 | 11. A character input program for causing a computer integrally or separately provided with an input unit including an n (n is an integer satisfying n=>2) number of selection units to execute: grouping processing of assigning an m-digit n-ary number satisfying X<=nm when the number of input candidate characters which are characters or symbols as an input candidate is set to be X (X is an integer satisfying X=>2) to each input candidate character one-for-one to classify the respective input candidate characters into n groups on a basis of each of m (m is an integer satisfying m=>2) digits, displaying processing of displaying, on a basis of each of the m digit, the n groups of the respective input candidate characters classified, and character specifying processing of specifying a value which each digit of an n-ary number can assume and which corresponds to the selection unit operated by a user and specifying one input candidate character according to an m-digit n-ary number determined by m times of operation of the selection unit. | 11. A character input program for causing a computer integrally or separately provided with an input unit including an n (n is an integer satisfying n=>2) number of selection units to execute: grouping processing of assigning an m-digit n-ary number satisfying X<=nm when the number of input candidate characters which are characters or symbols as an input candidate is set to be X (X is an integer satisfying X=>2) to each input candidate character one-for-one to classify the respective input candidate characters into n groups on a basis of each of m (m is an integer satisfying m=>2) digits, displaying processing of displaying, on a basis of each of the m digit, the n groups of the respective input candidate characters classified, and character specifying processing of specifying a value which each digit of an n-ary number can assume and which corresponds to the selection unit operated by a user and specifying one input candidate character according to an m-digit n-ary number determined by m times of operation of the selection unit. 15. The character input program according to claim 11 , which causes a computer to execute displaying processing of displaying a group of the respective input candidate characters in a different region for each kind of input candidate characters. | 0.632836 |
8,543,589 | 1 | 11 | 1. A method for integrating relational and hierarchical data, schema definitions, and queries in a data processing system, comprising the steps of: converting one or more schema definitions into an intermediate schema language component of an intermediate data language when one or more schema definitions are provided; converting one or more query expressions into an intermediate query language component of the intermediate data language when one or more query expressions are provided; compiling, in an intermediate data language processing engine, at least one of the intermediate schema language component and the intermediate query language component into a run-time representation in accordance with a relational-hierarchical analysis; and determining whether the schema definitions or the query expressions are relational prior to the converting steps; wherein the data processing system comprises a processor and memory for performing the converting, compiling and determining steps. | 1. A method for integrating relational and hierarchical data, schema definitions, and queries in a data processing system, comprising the steps of: converting one or more schema definitions into an intermediate schema language component of an intermediate data language when one or more schema definitions are provided; converting one or more query expressions into an intermediate query language component of the intermediate data language when one or more query expressions are provided; compiling, in an intermediate data language processing engine, at least one of the intermediate schema language component and the intermediate query language component into a run-time representation in accordance with a relational-hierarchical analysis; and determining whether the schema definitions or the query expressions are relational prior to the converting steps; wherein the data processing system comprises a processor and memory for performing the converting, compiling and determining steps. 11. The method of claim 1 , wherein the one or more query expressions comprise continuous queries over streaming data. | 0.825444 |
8,417,511 | 1 | 2 | 1. A method, comprising: issuing a first command, via a reusable dialog component, to a data access service to retrieve data from at least one back-end data source, the format of the first command being independent of the at least one back-end data source; retrieving the data, via the data access service, from the at least one back-end data source by using a second command that is selected based, at least in part, on the first command and the at least one back-end data source; storing the data, via the data access service, in a data structure in a data structure format that is independent of the at least one back-end data source; building a grammar based on the data structure using, at least in part, a dynamic grammar builder; and loading the grammar into a first voice application in a manner enabling its use by the reusable dialog component, the reusable dialog component defining an interaction sequence between the first voice application and a user of the first voice application, the reusable dialog component being adapted for use in at least one voice application other than the first voice application. | 1. A method, comprising: issuing a first command, via a reusable dialog component, to a data access service to retrieve data from at least one back-end data source, the format of the first command being independent of the at least one back-end data source; retrieving the data, via the data access service, from the at least one back-end data source by using a second command that is selected based, at least in part, on the first command and the at least one back-end data source; storing the data, via the data access service, in a data structure in a data structure format that is independent of the at least one back-end data source; building a grammar based on the data structure using, at least in part, a dynamic grammar builder; and loading the grammar into a first voice application in a manner enabling its use by the reusable dialog component, the reusable dialog component defining an interaction sequence between the first voice application and a user of the first voice application, the reusable dialog component being adapted for use in at least one voice application other than the first voice application. 2. The method of claim 1 , wherein storing the data in the data structure comprises the data access service populating a data graph based on the data. | 0.899464 |
9,875,258 | 12 | 14 | 12. A system, comprising: at least one processor; and memory including instructions that, when executed by the at least one processor, cause the system to: analyze an image including a representation of an object using a first classifier to determine a product category associated with the object; analyze the image using a second classifier algorithm to determine a term representing a visual characteristic of the image; analyzing the image using the second classifier algorithm with the term to determine a sequence of words describing visual characteristics associated with the object; determine that the sequence of words satisfies a search condition; generate, in response to the sequence of words satisfying the search condition, a search string query that includes a subset of the sequence of words and search string refinement terms associated with the product category and the sequence of words; determine a set of search results based at least in part on the search string query that includes an item from a catalog of items; and display the set of search results and the search string refinement terms on a computing device, the search string refinement terms being selectable, the search string query being configured to be editable in response to a selection of one of the search string refinement terms. | 12. A system, comprising: at least one processor; and memory including instructions that, when executed by the at least one processor, cause the system to: analyze an image including a representation of an object using a first classifier to determine a product category associated with the object; analyze the image using a second classifier algorithm to determine a term representing a visual characteristic of the image; analyzing the image using the second classifier algorithm with the term to determine a sequence of words describing visual characteristics associated with the object; determine that the sequence of words satisfies a search condition; generate, in response to the sequence of words satisfying the search condition, a search string query that includes a subset of the sequence of words and search string refinement terms associated with the product category and the sequence of words; determine a set of search results based at least in part on the search string query that includes an item from a catalog of items; and display the set of search results and the search string refinement terms on a computing device, the search string refinement terms being selectable, the search string query being configured to be editable in response to a selection of one of the search string refinement terms. 14. The system of claim 12 , wherein the instructions further cause the system to: determine a product category associated with the object; and analyze the image using the second classifier algorithm to determine a sequence of words based at least in part on the term and the product category. | 0.50339 |
9,881,146 | 1 | 5 | 1. An authentication method for verifying password input to an authentication device by a user, comprising the following steps: (a) defining a candidate character set including a plurality of characters, a subset of the candidate character set being a known character set contained in a predefined password; (b) randomly distributing all of the characters of the candidate character set into a plurality of candidate character subsets such that each candidate character subset includes two or more characters, and displaying all of the characters of the plurality of candidate character subsets in a plurality of interactive regions, respectively, all of the characters of each candidate character subset being randomly generated and distributed; and (c) receiving from the user a series of selections of specific ones of the plurality of interactive regions, checking whether each selected interactive region displayed a character of the known character set contained in the predefined password, and confirming successful authentication and outputting a signal indicating successful authentication when each of the interactive regions containing the characters of the known character set contained in the predefined password were directly selected by the user, wherein step (b) is repeated before each user selection of a specific one of the plurality of interactive regions, such that the characters in the plurality of candidate character subsets are randomly generated and distributed before each user selection. | 1. An authentication method for verifying password input to an authentication device by a user, comprising the following steps: (a) defining a candidate character set including a plurality of characters, a subset of the candidate character set being a known character set contained in a predefined password; (b) randomly distributing all of the characters of the candidate character set into a plurality of candidate character subsets such that each candidate character subset includes two or more characters, and displaying all of the characters of the plurality of candidate character subsets in a plurality of interactive regions, respectively, all of the characters of each candidate character subset being randomly generated and distributed; and (c) receiving from the user a series of selections of specific ones of the plurality of interactive regions, checking whether each selected interactive region displayed a character of the known character set contained in the predefined password, and confirming successful authentication and outputting a signal indicating successful authentication when each of the interactive regions containing the characters of the known character set contained in the predefined password were directly selected by the user, wherein step (b) is repeated before each user selection of a specific one of the plurality of interactive regions, such that the characters in the plurality of candidate character subsets are randomly generated and distributed before each user selection. 5. The authentication method as recited in claim 1 , wherein each interactive region is associated with a corresponding input circuit, and switching on of each input circuit is transformed into instructions of selection of a respective one of the interactive regions associated with the corresponding input circuit. | 0.793578 |
8,103,650 | 1 | 7 | 1. A computer implemented method comprising: accessing by one or more computer systems a plurality of keywords, each of the keywords comprising one or more words and describing one or more characteristics or features of particular advertising subject matter; annotating by a processor each of the keywords with one or more labels selected from a plurality of labels, each of the labels comprising one or more words and describing one or more aspects of or one or more categories or concepts represented by the keyword, wherein annotating each of the keywords with one or more labels comprises: for each of the keywords, when the keyword is able to be directly annotated, then directly annotating the keyword; and when the keyword is unable to be directly annotated, then: constructing a keyword document for the keyword; for each of the labels, constructing a label document for the label; and calculating a similarity between the keyword document corresponding to the keyword and the label document corresponding to the label as ∑ k = 1 k = n w wc i , k wc j , k wc i wc j , where: (1) n W denotes a total number of unique words in the keyword document and the label document; (2) wc i,k denotes a number of times a specific word, word k , occurs in the keyword document; (3) wc j,k denotes a number of times the specific word, word k , occurs in the label document; (4) wc i denotes a n W -vector consisting of the wc i,k ; and (5) wc j denotes a n W -vector consisting of the wc j,k ; and annotating the keyword based on the similarity between the keyword document corresponding to the keyword and the label document corresponding to each of the labels; grouping the keywords into one or more keyword groups based on similarities between the labels of the keywords, each of the keyword groups comprising one or more of the keywords; and forming one or more advertising groups from the keyword groups, comprising: from each of the keyword groups, forming one or more of the advertising groups, each of the advertising groups comprising one or more of the keywords in the keyword group. | 1. A computer implemented method comprising: accessing by one or more computer systems a plurality of keywords, each of the keywords comprising one or more words and describing one or more characteristics or features of particular advertising subject matter; annotating by a processor each of the keywords with one or more labels selected from a plurality of labels, each of the labels comprising one or more words and describing one or more aspects of or one or more categories or concepts represented by the keyword, wherein annotating each of the keywords with one or more labels comprises: for each of the keywords, when the keyword is able to be directly annotated, then directly annotating the keyword; and when the keyword is unable to be directly annotated, then: constructing a keyword document for the keyword; for each of the labels, constructing a label document for the label; and calculating a similarity between the keyword document corresponding to the keyword and the label document corresponding to the label as ∑ k = 1 k = n w wc i , k wc j , k wc i wc j , where: (1) n W denotes a total number of unique words in the keyword document and the label document; (2) wc i,k denotes a number of times a specific word, word k , occurs in the keyword document; (3) wc j,k denotes a number of times the specific word, word k , occurs in the label document; (4) wc i denotes a n W -vector consisting of the wc i,k ; and (5) wc j denotes a n W -vector consisting of the wc j,k ; and annotating the keyword based on the similarity between the keyword document corresponding to the keyword and the label document corresponding to each of the labels; grouping the keywords into one or more keyword groups based on similarities between the labels of the keywords, each of the keyword groups comprising one or more of the keywords; and forming one or more advertising groups from the keyword groups, comprising: from each of the keyword groups, forming one or more of the advertising groups, each of the advertising groups comprising one or more of the keywords in the keyword group. 7. The method of claim 1 , further comprising: constructing an annotation model based on a plurality of training keywords and a plurality of training keyword documents, each of the training keywords comprising one or more words and uniquely corresponding to one of the training keyword documents, comprising: annotating each of the training keywords with one or more of the labels based on the training keyword document corresponding to the training keyword; wherein for each corresponding pair of training keyword and label or for each corresponding pair of training keyword document and label, the annotation model produces a score that indicates a level of appropriateness of the label for the training keyword or the training keyword document, wherein annotating each of the keywords with one or more labels further comprises: in alternative to annotating the keyword based on the similarity between the keyword document corresponding to the keyword and the label document corresponding to each of the labels, for each of the labels, computing a score for the keyword document corresponding to the keyword and the label using the annotation model; and annotating the keyword with one of the labels where the keyword document corresponding to the keyword and the label have the highest or the lowest score. | 0.532166 |
7,783,135 | 2 | 3 | 2. The method of claim 1 , wherein performing an action includes displaying a content in response to detecting the selection. | 2. The method of claim 1 , wherein performing an action includes displaying a content in response to detecting the selection. 3. The method of claim 2 , wherein displaying the content includes selectively displaying the information that identifies the one or more objects. | 0.734545 |
9,886,427 | 1 | 4 | 1. A system for suggesting autocompletion terms during text entry of a report, comprising a word processor configured for: enabling a user to enter a text into a current report; determining a plurality of sections of the current report; one or more computer processors configured for: detecting sections of the plurality of sections of the current report which the user is working on, thus obtaining a current section; extracting a term occurring in the current report, thus obtaining an extracted term, identifying sections of the plurality of sections of the current report in which the extracted term occurs, thus obtaining an extracted term section, wherein the extracted term section and the current section are different sections; accessing a plurality of co-occurrence statistics, a co-occurrence statistic being indicative of at least one first term, at least one first section which contains the first term, a second term, a second section which contains the second term, and a frequency in which reports in a knowledge domain contain the at least one first term in the at least one first section in combination with the second term in the second section, wherein the at least one first section is different from the second section; selecting at least one frequently co-occurring term, based on the extracted term, the extracted term section which contains the extracted term, the current section, and the co-occurrence statistics, wherein the at least one frequently co-occurring term is selected for a portion of a term entered in the current section based on at least one of the co-occurrence statistics associated with the extracted term in the extracted term section; the word processor further being configured for providing an indication of the at least one frequently co-occuring term to the user. | 1. A system for suggesting autocompletion terms during text entry of a report, comprising a word processor configured for: enabling a user to enter a text into a current report; determining a plurality of sections of the current report; one or more computer processors configured for: detecting sections of the plurality of sections of the current report which the user is working on, thus obtaining a current section; extracting a term occurring in the current report, thus obtaining an extracted term, identifying sections of the plurality of sections of the current report in which the extracted term occurs, thus obtaining an extracted term section, wherein the extracted term section and the current section are different sections; accessing a plurality of co-occurrence statistics, a co-occurrence statistic being indicative of at least one first term, at least one first section which contains the first term, a second term, a second section which contains the second term, and a frequency in which reports in a knowledge domain contain the at least one first term in the at least one first section in combination with the second term in the second section, wherein the at least one first section is different from the second section; selecting at least one frequently co-occurring term, based on the extracted term, the extracted term section which contains the extracted term, the current section, and the co-occurrence statistics, wherein the at least one frequently co-occurring term is selected for a portion of a term entered in the current section based on at least one of the co-occurrence statistics associated with the extracted term in the extracted term section; the word processor further being configured for providing an indication of the at least one frequently co-occuring term to the user. 4. The system according o claim 1 , wherein the extracted term and/or the first term comprise an expression comprising a plurality of words. | 0.820051 |
9,990,419 | 15 | 18 | 15. An article of manufacture, comprising: at least one tangible computer readable device having computer readable program code logic tangibly embodied therein to generate answers to questions, the computer readable program code logic, when executing, performing the following: receiving an input query; obtaining, from an unstructured data source, a plurality of candidate answers to the input query; performing context independent answer processing to produce first scores for each of the candidate answers; computing specified information about each of the candidate answers during the context independent answer processing; sending the candidate answers to a model selection module; using the model selection module to use said specified information computed about the candidate answers during the context independent answer processing, to select one of a plurality of scoring models; sending each of the candidate answers to the selected one of the scoring models; using the selected one of the scoring models for weighting the first scores for the candidate answers to determine an answer score for each of the candidate answers; and generating at least one answer to the input query based on the answer scores. | 15. An article of manufacture, comprising: at least one tangible computer readable device having computer readable program code logic tangibly embodied therein to generate answers to questions, the computer readable program code logic, when executing, performing the following: receiving an input query; obtaining, from an unstructured data source, a plurality of candidate answers to the input query; performing context independent answer processing to produce first scores for each of the candidate answers; computing specified information about each of the candidate answers during the context independent answer processing; sending the candidate answers to a model selection module; using the model selection module to use said specified information computed about the candidate answers during the context independent answer processing, to select one of a plurality of scoring models; sending each of the candidate answers to the selected one of the scoring models; using the selected one of the scoring models for weighting the first scores for the candidate answers to determine an answer score for each of the candidate answers; and generating at least one answer to the input query based on the answer scores. 18. The article of manufacture according to claim 15 , wherein the computed specified information is intrinsic to the candidate answers. | 0.555556 |
9,570,074 | 6 | 7 | 6. The computer-implemented method of claim 1 , wherein the remediation strategy for inducing the user to speak the particular term using an age-appropriate pronunciation involves outputting audio data corresponding to a pronunciation of the particular term that not age-appropriate. | 6. The computer-implemented method of claim 1 , wherein the remediation strategy for inducing the user to speak the particular term using an age-appropriate pronunciation involves outputting audio data corresponding to a pronunciation of the particular term that not age-appropriate. 7. The computer-implemented method of claim 6 , wherein outputting audio data corresponding to a pronunciation of the particular term that is not age-appropriate comprises outputting the received audio data corresponding to the user speaking the particular term. | 0.554422 |
8,351,708 | 2 | 3 | 2. An information processing apparatus according to claim 1 , wherein the posture estimating means projects, onto a parameter space, an image transformation parameter for determining a positional posture in three dimensions including an image plane and time of the model moving image determined by N sets of the candidate corresponding feature point pairs selected at random, obtains a cluster having a largest number of members among clusters formed by performing clustering on the parameter space, and sets the candidate corresponding feature point pairs, which are members of the cluster having the largest number of members, as the recognition corresponding feature point pair group. | 2. An information processing apparatus according to claim 1 , wherein the posture estimating means projects, onto a parameter space, an image transformation parameter for determining a positional posture in three dimensions including an image plane and time of the model moving image determined by N sets of the candidate corresponding feature point pairs selected at random, obtains a cluster having a largest number of members among clusters formed by performing clustering on the parameter space, and sets the candidate corresponding feature point pairs, which are members of the cluster having the largest number of members, as the recognition corresponding feature point pair group. 3. An information processing apparatus according to claim 2 , wherein the posture estimating means detects a centroid of the cluster having the largest number of members and estimates postures of the models using the centroid as a parameter corresponding to the postures. | 0.671117 |
9,898,531 | 10 | 15 | 10. A mathematical research system comprising: a computer processor operable to: create one or more concept line items (CLIs) from at least one mathematical representation, wherein a CLI is an expression of a mathematical concept that is searchable by the mathematical research system; map defined interrelationships between the CLIs wherein each defined interrelationship is a prerequisite, a dependency, or a lack of relationship; assign at least one unique identification code (IC) to each CLI to create CLI/IC pairs including mapped interrelationships; store the CLI/IC pairs and their mapped interrelationships in at least one database; create an index relating each of a plurality of documents with the CLI/IC pairs; and receive a search request to retrieve documents having an indexed relationship with one or more CLIs, ICs, or CLI/IC pairs through a search interface, wherein the one or more CLIs, ICs, or CLI/IC pairs are derived from the search request, whether the CLIs, ICs, or CLI/IC pairs are expressly or implicitly included in the search request. | 10. A mathematical research system comprising: a computer processor operable to: create one or more concept line items (CLIs) from at least one mathematical representation, wherein a CLI is an expression of a mathematical concept that is searchable by the mathematical research system; map defined interrelationships between the CLIs wherein each defined interrelationship is a prerequisite, a dependency, or a lack of relationship; assign at least one unique identification code (IC) to each CLI to create CLI/IC pairs including mapped interrelationships; store the CLI/IC pairs and their mapped interrelationships in at least one database; create an index relating each of a plurality of documents with the CLI/IC pairs; and receive a search request to retrieve documents having an indexed relationship with one or more CLIs, ICs, or CLI/IC pairs through a search interface, wherein the one or more CLIs, ICs, or CLI/IC pairs are derived from the search request, whether the CLIs, ICs, or CLI/IC pairs are expressly or implicitly included in the search request. 15. The system of claim 10 wherein each CLI is assigned an importance score, wherein said importance score for a given CLI indicates how many other CLIs are prerequisite or dependency CLIs related to the given CLI. | 0.687135 |
8,639,763 | 19 | 21 | 19. A method performed by a first extensible markup language (XML) document management (XDM) server, the method comprising: receiving an XML document command protocol (XDCP) forward request specifying a first uniform resource identifier (URI) corresponding to contact information to be shared with a recipient according to a contact share request from a client, the XDCP forward request further specifying a second URI corresponding to the recipient; providing the contact information to a second XDM server associated with the recipient after receiving a message from the second XDM server requesting the contact information, the message to occur if the recipient has accepted forwarding of the contact information but not if the recipient has rejected forwarding of the contact information. | 19. A method performed by a first extensible markup language (XML) document management (XDM) server, the method comprising: receiving an XML document command protocol (XDCP) forward request specifying a first uniform resource identifier (URI) corresponding to contact information to be shared with a recipient according to a contact share request from a client, the XDCP forward request further specifying a second URI corresponding to the recipient; providing the contact information to a second XDM server associated with the recipient after receiving a message from the second XDM server requesting the contact information, the message to occur if the recipient has accepted forwarding of the contact information but not if the recipient has rejected forwarding of the contact information. 21. A tangible machine readable storage medium storing machine readable instructions which, when executed, cause a machine to implement the method defined in claim 19 . | 0.5 |
8,578,171 | 10 | 11 | 10. The method of claim 1 , wherein the server comprises an associated message server. | 10. The method of claim 1 , wherein the server comprises an associated message server. 11. The method of claim 10 , further comprising: receiving, by the associated message server, the configuration; transmitting, by the associated message server, automatic reply electronic messages in accordance with the configuration. | 0.5 |
7,880,730 | 22 | 23 | 22. A text entry system, comprising: (a) a reduced user input device comprising an auto-correcting keyboard region comprising a plurality of character set members, wherein locations having known coordinates in the auto-correcting keyboard region are associated with corresponding character set members, each location having associated therewith a plurality of said character set members of said alphabet such that contact with one of said locations is ambiguous as to which character set member associated with the location is intended, wherein each time a user contacts the user input device within the auto-correcting keyboard region, a location associated with the user contact is determined and the determined contact location is added to a current input sequence of contact locations; (b) a memory containing a plurality of objects, wherein each object is a string of one or a plurality of character set members; (c) an output device with a text display area; and (d) a processor coupled to the user input device, memory, and output device, said processor comprising: (i) a distance value calculation component which, for each determined contact location in the input sequence of contacts, calculates a set of distance values between the contact locations and the known coordinate locations corresponding to one or a plurality of character set members within the auto-correcting keyboard region; (ii) an object evaluation component which, for each generated input sequence, identifies at least one candidate object in memory, and for each of the at least one identified candidate objects, evaluates each identified candidate object by calculating a matching metric based on the calculated distance values associated with the object, and ranks evaluated candidate objects based on the calculated matching metric values; and (iii) a selection component for identifying at least one candidate object according to an evaluated ranking, presenting the at least one identified object to the user, and enabling the user to select one of the at least one presented objects for output to the text display area on the output device. | 22. A text entry system, comprising: (a) a reduced user input device comprising an auto-correcting keyboard region comprising a plurality of character set members, wherein locations having known coordinates in the auto-correcting keyboard region are associated with corresponding character set members, each location having associated therewith a plurality of said character set members of said alphabet such that contact with one of said locations is ambiguous as to which character set member associated with the location is intended, wherein each time a user contacts the user input device within the auto-correcting keyboard region, a location associated with the user contact is determined and the determined contact location is added to a current input sequence of contact locations; (b) a memory containing a plurality of objects, wherein each object is a string of one or a plurality of character set members; (c) an output device with a text display area; and (d) a processor coupled to the user input device, memory, and output device, said processor comprising: (i) a distance value calculation component which, for each determined contact location in the input sequence of contacts, calculates a set of distance values between the contact locations and the known coordinate locations corresponding to one or a plurality of character set members within the auto-correcting keyboard region; (ii) an object evaluation component which, for each generated input sequence, identifies at least one candidate object in memory, and for each of the at least one identified candidate objects, evaluates each identified candidate object by calculating a matching metric based on the calculated distance values associated with the object, and ranks evaluated candidate objects based on the calculated matching metric values; and (iii) a selection component for identifying at least one candidate object according to an evaluated ranking, presenting the at least one identified object to the user, and enabling the user to select one of the at least one presented objects for output to the text display area on the output device. 23. The system of claim 22 , wherein objects in memory are further associated with at least one module, wherein said module comprises a set of objects having at least one common characteristic or that is generated by a common process/algorithm or alternate method of interpreting said current input sequence. | 0.673729 |
9,130,882 | 16 | 30 | 16. A data processing apparatus comprising: a server computer configured to host a web server; a data storage device coupled to the server computer and storing a plurality of different website resources; in the server computer, a website resource selection unit that is configured to: receive, from a requesting computing device, a request for a resource of a requested website; determine a plurality of context values associated with the request, including a particular context value identifying information associated with a referral website that is different from the requested website; select a plurality of rules, wherein each of the plurality of rules specifies an expected context value, a website resource, and a rank, wherein the plurality of context values contains the expected context value; select a particular website resource from a plurality of website resources, wherein the particular website resource is the website resource of a rule having a highest rank of the plurality of rules; cause the particular website resource to be delivered to the requesting computing device. | 16. A data processing apparatus comprising: a server computer configured to host a web server; a data storage device coupled to the server computer and storing a plurality of different website resources; in the server computer, a website resource selection unit that is configured to: receive, from a requesting computing device, a request for a resource of a requested website; determine a plurality of context values associated with the request, including a particular context value identifying information associated with a referral website that is different from the requested website; select a plurality of rules, wherein each of the plurality of rules specifies an expected context value, a website resource, and a rank, wherein the plurality of context values contains the expected context value; select a particular website resource from a plurality of website resources, wherein the particular website resource is the website resource of a rule having a highest rank of the plurality of rules; cause the particular website resource to be delivered to the requesting computing device. 30. The apparatus of claim 16 , wherein the website resource selection unit is further configured to determine the plurality of context values associated with the request, including the particular context value and a second context value, wherein the second context value indicates a history of a requesting device with the requested website. | 0.72943 |
8,773,389 | 9 | 13 | 9. An electronic device, comprising: one or more processors; a display; a touch sensor to detect user inputs of varying force; a memory coupled to the one or more processors, the memory storing a content item and instructions that are executable by the one or more processors to perform acts comprising: in response to detecting a first user input using the touch sensor, selecting a first entry from supplemental content to output to the display, the first entry selected based at least in part on the first user input; in response to detecting, using the touch sensor, a second user input having an amount of force greater than a predetermined threshold, selecting a second entry from the supplemental content to output to the display by prompting a user to select one of multiple different reference work entries, the second entry selected based at least in part on the amount of force of the second user input. | 9. An electronic device, comprising: one or more processors; a display; a touch sensor to detect user inputs of varying force; a memory coupled to the one or more processors, the memory storing a content item and instructions that are executable by the one or more processors to perform acts comprising: in response to detecting a first user input using the touch sensor, selecting a first entry from supplemental content to output to the display, the first entry selected based at least in part on the first user input; in response to detecting, using the touch sensor, a second user input having an amount of force greater than a predetermined threshold, selecting a second entry from the supplemental content to output to the display by prompting a user to select one of multiple different reference work entries, the second entry selected based at least in part on the amount of force of the second user input. 13. An electronic device as recited in claim 9 , wherein the acts further comprise: in response to detecting, using the touch sensor, a third user input having the amount of force greater than the predetermined threshold, selecting a third entry from third supplemental content to output to the display, the third entry selected based at least in part on the amount of force of the third user input. | 0.5 |
7,644,047 | 3 | 4 | 3. An information retrieval apparatus for use in retrieving information from a set of one or more documents, comprising: an input for receiving a search query; generating means for generating a set of probabilities indicative of the semantic similarity of words selected from said set of one or more documents; query enhancement means for modifying a received search query with reference, in use, to said generated set of probabilities; and information retrieval means for searching said set of one or more documents for relevant information using a received search query modified by said query enhancement means, wherein said generating means are arranged, in use: (i) for each word selected from said set of one or more documents: (a) to identify, in documents of said set of one or more documents, word sequences comprising the word and a predetermined number of other words; (b) to calculate a relative frequency of occurrence for each distinct word sequence among word sequences containing the word; and (c) to generate a fuzzy set comprising, for groups of word sequences containing the word, corresponding fuzzy membership values calculated from the relative frequencies determined at step (b); and (ii) to calculate, for each pair of words of said plurality of words, using respective fuzzy sets generated at step (i), a probability that the first word of the pair is semantically suitable as a replacement for the second word of the pair. | 3. An information retrieval apparatus for use in retrieving information from a set of one or more documents, comprising: an input for receiving a search query; generating means for generating a set of probabilities indicative of the semantic similarity of words selected from said set of one or more documents; query enhancement means for modifying a received search query with reference, in use, to said generated set of probabilities; and information retrieval means for searching said set of one or more documents for relevant information using a received search query modified by said query enhancement means, wherein said generating means are arranged, in use: (i) for each word selected from said set of one or more documents: (a) to identify, in documents of said set of one or more documents, word sequences comprising the word and a predetermined number of other words; (b) to calculate a relative frequency of occurrence for each distinct word sequence among word sequences containing the word; and (c) to generate a fuzzy set comprising, for groups of word sequences containing the word, corresponding fuzzy membership values calculated from the relative frequencies determined at step (b); and (ii) to calculate, for each pair of words of said plurality of words, using respective fuzzy sets generated at step (i), a probability that the first word of the pair is semantically suitable as a replacement for the second word of the pair. 4. An information retrieval apparatus according to claim 3 , wherein said query enhancement means are arranged to identify, with reference to said generated set of probabilities, a word having a similar meaning to a term of said received search query and to modify said search query using said identified word. | 0.593176 |
4,362,152 | 2 | 3 | 2. The erector of claim 1 wherein the elongated rod means comprises two rods each having an axis, the rods encased within a common sleeve, the rods being in substantially side-by-side relation, the rods being capable of rotation relative to each other about their respective axes. | 2. The erector of claim 1 wherein the elongated rod means comprises two rods each having an axis, the rods encased within a common sleeve, the rods being in substantially side-by-side relation, the rods being capable of rotation relative to each other about their respective axes. 3. The erector of claim 2 further comprising a thin filament wrapped around the two rods in a helical fashion for maintaining the rods in side-by-side relation. | 0.5 |
9,348,579 | 1 | 8 | 1. A method of integrating social networks with integrated development environment (IDE), the method comprising: downloading social information; filtering and displaying the downloaded social information; performing software development using the displayed social information, wherein the performing software development comprises creating a topic related to a source file, wherein the topic comprises an identifier that identifies the source file, a location reference of the source file, one or more user comments and a source file snapshot that includes a read-only copy of the source file; and storing updated social information in a database, wherein the updated social information comprises the created topic. | 1. A method of integrating social networks with integrated development environment (IDE), the method comprising: downloading social information; filtering and displaying the downloaded social information; performing software development using the displayed social information, wherein the performing software development comprises creating a topic related to a source file, wherein the topic comprises an identifier that identifies the source file, a location reference of the source file, one or more user comments and a source file snapshot that includes a read-only copy of the source file; and storing updated social information in a database, wherein the updated social information comprises the created topic. 8. The method according to claim 1 , wherein the performing the software development comprises marking, with an icon, the source file in a project tree of source files to indicate it has been a subject of discussion. | 0.544304 |
8,972,391 | 5 | 6 | 5. The non-transitory computer-readable storage medium of claim 1 , wherein adjusting the respective score for a particular selected search result comprises combining the category relevance for the particular selected search result with an information retrieval score of the particular selected search result. | 5. The non-transitory computer-readable storage medium of claim 1 , wherein adjusting the respective score for a particular selected search result comprises combining the category relevance for the particular selected search result with an information retrieval score of the particular selected search result. 6. The non-transitory computer-readable storage medium of claim 5 , wherein combining the category relevance for the selected search result with the information retrieval score of the particular selected search result comprises: multiplying the category relevance for the selected search result by the information retrieval score of the particular selected search result, or adding the category relevance for the particular selected search result by the information retrieval score of the particular selected search result. | 0.5 |
9,116,979 | 6 | 8 | 6. The method of claim 5 , wherein comparing the content of each document-of-interest to one of the topics comprises: obtaining a measure of similarity between each document-of-interest and the topic. | 6. The method of claim 5 , wherein comparing the content of each document-of-interest to one of the topics comprises: obtaining a measure of similarity between each document-of-interest and the topic. 8. The method of claim 6 , wherein the measure of similarity is a cosine similarity between the document-of-interest and the topic. | 0.670854 |
9,639,449 | 5 | 6 | 5. The error detection method of claim 4 , further comprising: determining that a relevant sequence is same logic when each calculated hash code for each minimum unit is same; and determining that a relevant sequence is similar logic when the calculated LCS is greater than the set similarity threshold. | 5. The error detection method of claim 4 , further comprising: determining that a relevant sequence is same logic when each calculated hash code for each minimum unit is same; and determining that a relevant sequence is similar logic when the calculated LCS is greater than the set similarity threshold. 6. The error detection method of claim 5 , further comprising reporting same logic detection, similar logic detection and determination results relative to the sequence. | 0.5 |
8,150,862 | 2 | 17 | 2. A computer-implemented method for collecting event information, comprising: on a server system having one or more processors for executing one or more programs stored in memory of the server system so as to perform the method: loading a plurality of XML documents, each XML document specifying event parsing logic for a respective group of related events; storing in one or more parsing trees a representation of the event parsing logic in the plurality of XML documents, the one or more parsing trees including event parsing logic for parsing events in a plurality of groups of events; receiving events, including a first event and a second event; processing the second event in accordance the event parsing logic for a first group of events that includes both the first event and second event, the processing of the second event including: extracting information from the first event in accordance with the event parsing logic for the first group of events; extracting information from the second event in accordance with the event parsing logic for the first group of events; supplementing at least a portion of the information extracted from the second event with at least a portion of the information extracted from the first event, in accordance with the event parsing logic for the first group of events, to produce enhanced information for the second event; and storing the enhanced information for the second event in computer readable memory. | 2. A computer-implemented method for collecting event information, comprising: on a server system having one or more processors for executing one or more programs stored in memory of the server system so as to perform the method: loading a plurality of XML documents, each XML document specifying event parsing logic for a respective group of related events; storing in one or more parsing trees a representation of the event parsing logic in the plurality of XML documents, the one or more parsing trees including event parsing logic for parsing events in a plurality of groups of events; receiving events, including a first event and a second event; processing the second event in accordance the event parsing logic for a first group of events that includes both the first event and second event, the processing of the second event including: extracting information from the first event in accordance with the event parsing logic for the first group of events; extracting information from the second event in accordance with the event parsing logic for the first group of events; supplementing at least a portion of the information extracted from the second event with at least a portion of the information extracted from the first event, in accordance with the event parsing logic for the first group of events, to produce enhanced information for the second event; and storing the enhanced information for the second event in computer readable memory. 17. The method of claim 2 , wherein each XML document specifies one or more event attributes to be included in the enhanced information for the second event when a predefined precondition is met. | 0.788043 |
7,630,974 | 20 | 22 | 20. One or more processor readable storage devices having processor readable code embodied on said one or more processor readable storage devices, said processor readable code for programming one or more processors, said processor readable code comprising: code for maintaining, at a data store, an access management system configured to receive a request to view and modify at least one of a plurality of identity profiles, wherein the request is associated with one or more multi-valued attributes, said request is associated with a preferred language; code for determining said preferred language from at least one of a Uniform Resource Locator (URL) associated with said request, an HTTP a hypertext transfer protocol (HTTP) header variable associated with said request, an individual identity profile associated with said request, and a cookie associated with said request, wherein each individual identity profile comprises a single data structure, wherein said individual identity profile contains all available language components and value components for said multi-valued attribute; code for determining, at the access management system, whether the preferred language of the request matches an installed language at the access management system; in response to the preferred language not matching the installed language, code for performing an approximate language match based at least in part on a language code associated with the preferred language; code for retrieving from the single data structure said one or more multi-valued attributes, said one or more multi-valued attributes include a plurality of values, each of said values includes a language component and a value component, each value component specifies a value for said one or more multi-valued attributes that is associated with a corresponding language component; and code for generating a response to said request, said response includes at least one first value for said one or more multi-valued attributes that corresponds to said preferred language. | 20. One or more processor readable storage devices having processor readable code embodied on said one or more processor readable storage devices, said processor readable code for programming one or more processors, said processor readable code comprising: code for maintaining, at a data store, an access management system configured to receive a request to view and modify at least one of a plurality of identity profiles, wherein the request is associated with one or more multi-valued attributes, said request is associated with a preferred language; code for determining said preferred language from at least one of a Uniform Resource Locator (URL) associated with said request, an HTTP a hypertext transfer protocol (HTTP) header variable associated with said request, an individual identity profile associated with said request, and a cookie associated with said request, wherein each individual identity profile comprises a single data structure, wherein said individual identity profile contains all available language components and value components for said multi-valued attribute; code for determining, at the access management system, whether the preferred language of the request matches an installed language at the access management system; in response to the preferred language not matching the installed language, code for performing an approximate language match based at least in part on a language code associated with the preferred language; code for retrieving from the single data structure said one or more multi-valued attributes, said one or more multi-valued attributes include a plurality of values, each of said values includes a language component and a value component, each value component specifies a value for said one or more multi-valued attributes that is associated with a corresponding language component; and code for generating a response to said request, said response includes at least one first value for said one or more multi-valued attributes that corresponds to said preferred language. 22. One or more processor readable storage devices according to claim 20 , wherein: said one or more multi-valued attributes are included in configuration information maintained at a data store; and said at least one first value for said one or more multi-valued attributes that corresponds to said preferred language is at least one language specific display name for said one or more multi-valued attributes. | 0.502427 |
9,262,522 | 1 | 18 | 1. A music messaging software-as-a-service platform, comprising: a computer hardware infrastructure accessible at a network domain and comprising: first program code that receives, from a sender, a set of first information, the set of first information including a message personalized for an intended recipient, together with non-audio data identifying a lyric phrase from an audio recording; an audio extraction engine that (i) receives the non-audio data identifying the lyric phrase together with an instance of the audio recording, (ii) identifies a portion of the audio recording where the lyric phrase is likely to be found at least in part by mapping each word in the lyric phrase to one and only vocal interval determined to exist in the audio recording, (iii) extracts the portion of the audio recording into a short snippet; and (iv) writes the short snippet into a database; and a message generator that combines a reference to the short snippet with the message to generate and output a music message note for the intended recipient; and second program code operative to cause delivery of the short snippet in response to receipt of data indicating that the reference is selected by the intended recipient. | 1. A music messaging software-as-a-service platform, comprising: a computer hardware infrastructure accessible at a network domain and comprising: first program code that receives, from a sender, a set of first information, the set of first information including a message personalized for an intended recipient, together with non-audio data identifying a lyric phrase from an audio recording; an audio extraction engine that (i) receives the non-audio data identifying the lyric phrase together with an instance of the audio recording, (ii) identifies a portion of the audio recording where the lyric phrase is likely to be found at least in part by mapping each word in the lyric phrase to one and only vocal interval determined to exist in the audio recording, (iii) extracts the portion of the audio recording into a short snippet; and (iv) writes the short snippet into a database; and a message generator that combines a reference to the short snippet with the message to generate and output a music message note for the intended recipient; and second program code operative to cause delivery of the short snippet in response to receipt of data indicating that the reference is selected by the intended recipient. 18. The messaging software-as-a-service platform as described in claim 1 wherein the delivery is by streaming the short snippet without digital rights management (DRM) associated therewith. | 0.622 |
9,881,052 | 1 | 2 | 1. A method of accessing data within a database object based on a query with a predicate including a plurality of conditional expressions, wherein an element of the database object is stored among a plurality of different storage regions with each storage region being associated with first and second range values indicating a value range for element values within that storage region, the method comprising: applying each conditional expression of the query predicate to at least one of the first and second range values for each of the storage regions to produce evaluation results of that conditional expression for the storage regions, wherein each storage region comprises units of column data, and applying each conditional expression further comprises: inserting mock data into units of column data of a storage region that are determined not to be scanned based on application of that conditional expression; combining the evaluation result of each conditional expression for a corresponding storage region to produce aggregated results for each of the storage regions, wherein the aggregated result for a corresponding storage region indicates at least one of a presence of data satisfying the conditional expressions within that storage region, an absence of data satisfying the conditional expressions within that storage region, and insufficient information to determine the presence of data satisfying the conditional expressions within that storage region, and wherein the aggregated result for at least one storage region indicates insufficient information; providing information to evaluate one or more conditional expressions for a storage region in response to the aggregated result for that storage region indicating insufficient information, wherein the provided information indicates one or more columns within that storage region; and scanning one or more corresponding individual storage regions based on the aggregated results for those storage regions and the provided information. | 1. A method of accessing data within a database object based on a query with a predicate including a plurality of conditional expressions, wherein an element of the database object is stored among a plurality of different storage regions with each storage region being associated with first and second range values indicating a value range for element values within that storage region, the method comprising: applying each conditional expression of the query predicate to at least one of the first and second range values for each of the storage regions to produce evaluation results of that conditional expression for the storage regions, wherein each storage region comprises units of column data, and applying each conditional expression further comprises: inserting mock data into units of column data of a storage region that are determined not to be scanned based on application of that conditional expression; combining the evaluation result of each conditional expression for a corresponding storage region to produce aggregated results for each of the storage regions, wherein the aggregated result for a corresponding storage region indicates at least one of a presence of data satisfying the conditional expressions within that storage region, an absence of data satisfying the conditional expressions within that storage region, and insufficient information to determine the presence of data satisfying the conditional expressions within that storage region, and wherein the aggregated result for at least one storage region indicates insufficient information; providing information to evaluate one or more conditional expressions for a storage region in response to the aggregated result for that storage region indicating insufficient information, wherein the provided information indicates one or more columns within that storage region; and scanning one or more corresponding individual storage regions based on the aggregated results for those storage regions and the provided information. 2. The method of claim 1 , wherein said scanning one or more corresponding individual storage regions includes: omitting one or more corresponding individual storage regions from scanning in response to the aggregated result for those storage regions indicating one of the presence of data satisfying the conditional expressions and the absence of data satisfying the conditional expressions. | 0.546296 |
8,612,212 | 2 | 3 | 2. The method of claim 1 , wherein the morphemes comprise one of verbal speech and non-verbal speech. | 2. The method of claim 1 , wherein the morphemes comprise one of verbal speech and non-verbal speech. 3. The method of claim 2 , wherein the non-verbal speech comprises using one of a gesture, a body movement, a head movement, a non-response, text, a keyboard entry, a keypad entry, a mouse click, a dual-tone machine frequency code, a pointer, a stylus, a graphical user interface, and a touchscreen entry. | 0.5 |
9,966,065 | 40 | 42 | 40. The electronic device of claim 25 , wherein providing to the user the acknowledgment associated with the first intent and the second intent comprises: providing a first task associated with the first intent and a second task associated with the second intent. | 40. The electronic device of claim 25 , wherein providing to the user the acknowledgment associated with the first intent and the second intent comprises: providing a first task associated with the first intent and a second task associated with the second intent. 42. The electronic device of claim 40 , wherein the one or more programs further include instructions for: in response to completing the first process, providing a first indicator associated with the first task; and in response to completing the second process, providing a second indicator associated with the second task. | 0.5 |
9,135,915 | 17 | 18 | 17. The article of manufacture of claim 15 , wherein the functions further comprise: in response to determining that the audio speech data is causally related to the vibration speech data, providing the audio speech data and/or the vibration speech data to a speech recognizer. | 17. The article of manufacture of claim 15 , wherein the functions further comprise: in response to determining that the audio speech data is causally related to the vibration speech data, providing the audio speech data and/or the vibration speech data to a speech recognizer. 18. The article of manufacture of claim 17 , wherein the functions further comprise: recognizing text corresponding to the HMD-wearer speech in the audio speech data and the vibration speech data using the speech recognizer. | 0.5 |
10,061,766 | 13 | 14 | 13. The computer system of claim 12 , the method comprising, prior to the automatically determining parts of speech: measuring domain relevance of the domain-relevant textual segments to the particular domain, wherein the measuring domain relevance yields the domain-relevance values; and verifying a threshold domain relevance of the parsed input text as a precondition of executing the automatically determining parts of speech, wherein the verifying is based at least in part on the domain-relevance values. | 13. The computer system of claim 12 , the method comprising, prior to the automatically determining parts of speech: measuring domain relevance of the domain-relevant textual segments to the particular domain, wherein the measuring domain relevance yields the domain-relevance values; and verifying a threshold domain relevance of the parsed input text as a precondition of executing the automatically determining parts of speech, wherein the verifying is based at least in part on the domain-relevance values. 14. The computer system of claim 13 , the method comprising: prior to the searching, adjusting the segment collection in a rule-based fashion; and wherein the searching is performed using the adjusted segment collection. | 0.5 |
9,430,772 | 11 | 12 | 11. A method comprising: receiving, by a processor over a network, an Short Message Service (SMS) message from a user of the client device, the SMS message being directed to another user of another client device, the user and the other user having a defined social connection; analyzing, by the processor, the SMS message to detect a question from the user to the other user; if a question from the user is detected in the received text message: storing, by the processor, a copy of the detected question comprised in the received text message; monitoring, by the processor, for a response text message to the detected question from the other user for a timeout time period; intercepting, by the processor, a response SMS from the other user of the other client device if the response text message is received within the timeout time period; refining, by the processor, the detected question from the user by combining at least a portion of the response SMS message to the detected question with at least a portion of the detected question from the user, refining the detected question from the user comprising rephrasing the detected question and clarifying the intent of the user; employing, by the processor, the refined detected question to select a contextual advertisement; modifying, by the processor, the response SMS message to include link information to the contextual advertisement; and providing, by the processor, the modified response SMS message to the mobile device. | 11. A method comprising: receiving, by a processor over a network, an Short Message Service (SMS) message from a user of the client device, the SMS message being directed to another user of another client device, the user and the other user having a defined social connection; analyzing, by the processor, the SMS message to detect a question from the user to the other user; if a question from the user is detected in the received text message: storing, by the processor, a copy of the detected question comprised in the received text message; monitoring, by the processor, for a response text message to the detected question from the other user for a timeout time period; intercepting, by the processor, a response SMS from the other user of the other client device if the response text message is received within the timeout time period; refining, by the processor, the detected question from the user by combining at least a portion of the response SMS message to the detected question with at least a portion of the detected question from the user, refining the detected question from the user comprising rephrasing the detected question and clarifying the intent of the user; employing, by the processor, the refined detected question to select a contextual advertisement; modifying, by the processor, the response SMS message to include link information to the contextual advertisement; and providing, by the processor, the modified response SMS message to the mobile device. 12. The method of claim 11 , wherein analyzing the SMS message further comprises: analyzing, by the processor, the SMS message using heuristics to detect at least one of a question-oriented phrase, or question-oriented keyword. | 0.5 |
9,336,207 | 8 | 9 | 8. An information handling system comprising: one or more processors; a memory coupled to at least one of the processors; a set of computer program instructions stored in the memory and executed by at least one of the processors in order to perform actions of: computing a leverage value of a language translation supply chain, wherein the leverage value corresponds to an amount of suggested translations, from a plurality of suggested translations, that are accepted by a user that results in a set of accepted translations; computing a factor value of the language translation supply chain, wherein the factor value indicates a productivity of the user to convert the set of accepted translation into a set of final translations; determining a performance efficiency of the language translation supply chain based upon the leverage value and the factor value; and evaluating the language translation supply chain based upon the performance efficiency. | 8. An information handling system comprising: one or more processors; a memory coupled to at least one of the processors; a set of computer program instructions stored in the memory and executed by at least one of the processors in order to perform actions of: computing a leverage value of a language translation supply chain, wherein the leverage value corresponds to an amount of suggested translations, from a plurality of suggested translations, that are accepted by a user that results in a set of accepted translations; computing a factor value of the language translation supply chain, wherein the factor value indicates a productivity of the user to convert the set of accepted translation into a set of final translations; determining a performance efficiency of the language translation supply chain based upon the leverage value and the factor value; and evaluating the language translation supply chain based upon the performance efficiency. 9. The information handling system of claim 8 wherein the plurality of suggested translations correspond to a plurality of child class sets, and wherein the processors perform additional actions comprising: computing a child class set linguistic noise value for each of the plurality of child class sets using a corresponding child class leverage value and a child class factor value, resulting in a plurality of child class set linguistic noise values; combining the plurality of child class set linguistic noise values, resulting in a translation supply chain linguistic noise value; and utilizing the translation supply chain linguistic noise value during the performance efficiency determination of the language translation supply chain. | 0.5 |
7,735,026 | 7 | 9 | 7. The method of claim 1 , further comprising: generating by the computer the author analysis model, with generating comprising: analyzing at least one composition to generate linked data structures; and, the method further comprising: generating the poem from the data structures by using the data structures to locate the seed word in the linked data structures and determine words that follow it in the linked data structures. | 7. The method of claim 1 , further comprising: generating by the computer the author analysis model, with generating comprising: analyzing at least one composition to generate linked data structures; and, the method further comprising: generating the poem from the data structures by using the data structures to locate the seed word in the linked data structures and determine words that follow it in the linked data structures. 9. The method of claim 7 further comprising: automatically composing words of text while examining weights represented in the data structures to avoid counts of words in the data structures that would tend to repeat same words from the pre-existing compositions given a start word in the analyzed composition to avoid plagiarism. | 0.5 |
9,633,063 | 16 | 17 | 16. The computer system of claim 15 , wherein producing the redacted version comprises: presenting the phrase in an interface indicating that the word is included in the other of the redaction data and the non-redaction data based on the conflict resolution rule being applicable with respect to the phrase; receiving an input via the interface to apply the conflict resolution rule; and applying the conflict resolution rule. | 16. The computer system of claim 15 , wherein producing the redacted version comprises: presenting the phrase in an interface indicating that the word is included in the other of the redaction data and the non-redaction data based on the conflict resolution rule being applicable with respect to the phrase; receiving an input via the interface to apply the conflict resolution rule; and applying the conflict resolution rule. 17. The computer system of claim 16 , wherein presenting the phrase in the interface comprises: presenting the phrase in one of a redaction list generated based on applying the redaction data to the document and a non-redaction list generated based on applying the non-redaction data to the document; and presenting the word in another of the redaction list and the non-redaction list. | 0.53163 |
8,564,721 | 1 | 2 | 1. A method for synchronizing text with audio in a preexisting multimedia file, comprising the steps of: receiving the multimedia file and parsing the audio from the multimedia file while maintaining the timeline synchronization between the video portions and audio portions of the multimedia file; receiving closed-captioned data associated with the multimedia file, where the closed-captioned data contains closed-captioned text, each word of which is associated with a corresponding word spoken in the audio portion; generating text representations of parsed audio of the input multimedia file where each word of the text representation is associated approximately with the corresponding words spoken in the video portion; generating a probabilistic model predicting a next item in a sequence to compare each word of the closed-captioned text with a plurality of words of the text representation until a match is found; synchronizing each closed-captioned word with a respective point on the timeline in which each matched word is spoken in the audio and occurs within the video, where each matched word is associated with the accurate point on the timeline; providing the accurate, time-based text output to a database and associating said output with the original multimedia file. | 1. A method for synchronizing text with audio in a preexisting multimedia file, comprising the steps of: receiving the multimedia file and parsing the audio from the multimedia file while maintaining the timeline synchronization between the video portions and audio portions of the multimedia file; receiving closed-captioned data associated with the multimedia file, where the closed-captioned data contains closed-captioned text, each word of which is associated with a corresponding word spoken in the audio portion; generating text representations of parsed audio of the input multimedia file where each word of the text representation is associated approximately with the corresponding words spoken in the video portion; generating a probabilistic model predicting a next item in a sequence to compare each word of the closed-captioned text with a plurality of words of the text representation until a match is found; synchronizing each closed-captioned word with a respective point on the timeline in which each matched word is spoken in the audio and occurs within the video, where each matched word is associated with the accurate point on the timeline; providing the accurate, time-based text output to a database and associating said output with the original multimedia file. 2. The method of claim 1 , where the closed-captioned text and the text representation from the audio represent a portion of the audio of the multimedia file. | 0.796915 |
8,271,451 | 24 | 26 | 24. The system of claim 22 , wherein the certificate of destruction includes a summarization in a human-readable format. | 24. The system of claim 22 , wherein the certificate of destruction includes a summarization in a human-readable format. 26. The system of claim 24 , wherein the summarization includes links that retrieve an associated record archive when accessed. | 0.522556 |
8,954,845 | 1 | 4 | 1. An image processing device comprising: at least one processor and memory, cooperating to function as: an input unit configured to input document image data; a region division unit configured to divide the document image data into a plurality of regions according to attributes, the divided regions including a text region, a caption region and an object region which is accompanied by the caption region; a character recognition unit configured to obtain character information by executing a character recognition process for each character within each of the text region and the caption region divided by said region division unit; an anchor expression extraction unit configured to extract, from the character information in the caption region, an anchor expression which includes a predetermined character string identifying the object region; a text search unit configured to search for the anchor expression extracted by said anchor expression extraction unit from the character information in the text region; a link information generation unit configured to generate two-way link information associating an anchor expression peripheral region and an image peripheral region with each other, the anchor expression peripheral region being a region including the anchor expression found by said text search unit, and the image peripheral region being a region including the object region, wherein, in a case where said text search unit finds one anchor expression from the character information in the text region, said link information generation unit generates the two-way link information associating the image peripheral region with one anchor expression peripheral region which is a region including the one anchor expression found by said text search unit, wherein, in a case where said text search unit finds a plurality of anchor expressions from the character information in the text region, said link information generation unit generates the two-way link information associating the image peripheral region with a plurality of anchor expression peripheral regions which are regions including the plurality of the anchor expressions found by said text search unit; and a format conversion unit configured to generate electronic document data including document image data and the two-way link information, wherein, in the case where said text search unit finds the one anchor expression from the character information in the text region, the two-way link information includes a first link and a second link, the first link including information for displaying the associated one anchor expression peripheral region when a reader of the electronic document takes a predetermined action on the image peripheral region, and the second link including information for displaying the associated image peripheral region when a reader of the electronic document takes a predetermined action on the one anchor expression peripheral region, and wherein, in the case where said text search unit finds the plurality of anchor expressions from the character information in the text region, the two-way link information includes a third link and a fourth link, the third link including information for displaying information about the plurality of the anchor expression peripheral regions as a plurality of candidates of link destinations from the image peripheral region when a reader of the electronic document takes a predetermined action on the image peripheral region, and the fourth link including information for displaying the associated image peripheral region when a reader of the electronic document takes a predetermined action on any one of the plurality of the anchor expression peripheral regions. | 1. An image processing device comprising: at least one processor and memory, cooperating to function as: an input unit configured to input document image data; a region division unit configured to divide the document image data into a plurality of regions according to attributes, the divided regions including a text region, a caption region and an object region which is accompanied by the caption region; a character recognition unit configured to obtain character information by executing a character recognition process for each character within each of the text region and the caption region divided by said region division unit; an anchor expression extraction unit configured to extract, from the character information in the caption region, an anchor expression which includes a predetermined character string identifying the object region; a text search unit configured to search for the anchor expression extracted by said anchor expression extraction unit from the character information in the text region; a link information generation unit configured to generate two-way link information associating an anchor expression peripheral region and an image peripheral region with each other, the anchor expression peripheral region being a region including the anchor expression found by said text search unit, and the image peripheral region being a region including the object region, wherein, in a case where said text search unit finds one anchor expression from the character information in the text region, said link information generation unit generates the two-way link information associating the image peripheral region with one anchor expression peripheral region which is a region including the one anchor expression found by said text search unit, wherein, in a case where said text search unit finds a plurality of anchor expressions from the character information in the text region, said link information generation unit generates the two-way link information associating the image peripheral region with a plurality of anchor expression peripheral regions which are regions including the plurality of the anchor expressions found by said text search unit; and a format conversion unit configured to generate electronic document data including document image data and the two-way link information, wherein, in the case where said text search unit finds the one anchor expression from the character information in the text region, the two-way link information includes a first link and a second link, the first link including information for displaying the associated one anchor expression peripheral region when a reader of the electronic document takes a predetermined action on the image peripheral region, and the second link including information for displaying the associated image peripheral region when a reader of the electronic document takes a predetermined action on the one anchor expression peripheral region, and wherein, in the case where said text search unit finds the plurality of anchor expressions from the character information in the text region, the two-way link information includes a third link and a fourth link, the third link including information for displaying information about the plurality of the anchor expression peripheral regions as a plurality of candidates of link destinations from the image peripheral region when a reader of the electronic document takes a predetermined action on the image peripheral region, and the fourth link including information for displaying the associated image peripheral region when a reader of the electronic document takes a predetermined action on any one of the plurality of the anchor expression peripheral regions. 4. The image processing device of claim 1 , wherein said anchor expression extraction unit extracts a character string of a figure number as the anchor expression. | 0.822052 |
9,737,759 | 2 | 3 | 2. The method of claim 1 , wherein said parsing further comprises removing all quantity values and quantity units from said parsed text segments, and wherein said ranking said found exercise text matches comprises searching a past history of said user for previous matches, and selecting from said past history a most recent exercise tracked as said exercise to be tracked. | 2. The method of claim 1 , wherein said parsing further comprises removing all quantity values and quantity units from said parsed text segments, and wherein said ranking said found exercise text matches comprises searching a past history of said user for previous matches, and selecting from said past history a most recent exercise tracked as said exercise to be tracked. 3. The method of claim 2 , wherein upon an exercise match not being found in said searching, then searching a user population history for previous matches, and selecting an exercise that has been most often tracked as said exercise to be tracked. | 0.5 |
9,595,171 | 8 | 9 | 8. The method of claim 1 , further comprising: receiving a second plurality of candidate inputs from the sensor; classifying the second plurality of candidate inputs as one or more second intentional inputs; and determining a command for controlling the target device based on the one or more second intentional inputs, wherein providing the signal to the selected target device comprises providing a signal indicative of the command to the selected target device in response to the intentional input. | 8. The method of claim 1 , further comprising: receiving a second plurality of candidate inputs from the sensor; classifying the second plurality of candidate inputs as one or more second intentional inputs; and determining a command for controlling the target device based on the one or more second intentional inputs, wherein providing the signal to the selected target device comprises providing a signal indicative of the command to the selected target device in response to the intentional input. 9. The method of claim 8 , wherein the command comprises a command for an application on the target device. | 0.654839 |
9,946,813 | 1 | 5 | 1. A non-transitory computer-readable recording medium having stored therein a program that causes a computer to execute a process comprising: receiving a question containing a character string; identifying a question phrase for specifying a question type of the received question by comparing the character string contained in the question and a question phrase that is included in information that is stored in a storage unit, in the stored information a question phrase, a display mode and an extraction rule being associated one another, and identifying, based on the extraction rule that is associated with the identified question phrase, a search query used for searching in a database for a response to the received question, the database storing information published on Web sites; determining a display mode of an output of the response to the received question in accordance with the identified question phrase for specifying the question type by referring to the stored information; and outputting a search result of searching in the database using the identified search query, in the display mode of the output, wherein the process further comprises specifying, when the identified question phrase indicates that selection from objects that are included in the question is requested, the objects for selection and information related thereto from the search result; outputting each of the specified objects and information, in a display mode that enables comparison therebetween; extracting, when the identified question phrase indicates that objects of an action that is specified in the question are requested to be searched, the objects from the search result; and outputting the extracted objects in a display mode in which images of the extracted objects are listed. | 1. A non-transitory computer-readable recording medium having stored therein a program that causes a computer to execute a process comprising: receiving a question containing a character string; identifying a question phrase for specifying a question type of the received question by comparing the character string contained in the question and a question phrase that is included in information that is stored in a storage unit, in the stored information a question phrase, a display mode and an extraction rule being associated one another, and identifying, based on the extraction rule that is associated with the identified question phrase, a search query used for searching in a database for a response to the received question, the database storing information published on Web sites; determining a display mode of an output of the response to the received question in accordance with the identified question phrase for specifying the question type by referring to the stored information; and outputting a search result of searching in the database using the identified search query, in the display mode of the output, wherein the process further comprises specifying, when the identified question phrase indicates that selection from objects that are included in the question is requested, the objects for selection and information related thereto from the search result; outputting each of the specified objects and information, in a display mode that enables comparison therebetween; extracting, when the identified question phrase indicates that objects of an action that is specified in the question are requested to be searched, the objects from the search result; and outputting the extracted objects in a display mode in which images of the extracted objects are listed. 5. The non-transitory computer-readable recording medium according to claim 1 , wherein the outputting includes outputting the extracted objects in a display mode in which images and nouns that respectively correspond to the images are listed. | 0.689258 |
8,190,985 | 3 | 6 | 3. A method as set forth in claim 1 , wherein said step of identifying comprises parsing a data stream to obtain an attribute phrase including information potentially defining a semantic object, an attribute of said object and an attribute value of said attribute. | 3. A method as set forth in claim 1 , wherein said step of identifying comprises parsing a data stream to obtain an attribute phrase including information potentially defining a semantic object, an attribute of said object and an attribute value of said attribute. 6. A method as set forth in claim 3 , wherein said step of using comprises performing a comparison of said object, attribute or attribute value to a corresponding set of objects, attributes, or attribute values defined by said first schema. | 0.5 |
9,558,467 | 3 | 6 | 3. The system of claim 1 , wherein the first modeling language is defined so as to specify semantics of model objects based on coloring and shape; semantics of a model as a function of shapes, colors, positioning, and interconnectedness of its model objects; and implicit information about model objects based on grid location. | 3. The system of claim 1 , wherein the first modeling language is defined so as to specify semantics of model objects based on coloring and shape; semantics of a model as a function of shapes, colors, positioning, and interconnectedness of its model objects; and implicit information about model objects based on grid location. 6. The system of claim 3 , wherein model objects located in the first column of the grid logically imposed on the physical substrate are defined as additional semantic objects, provided that such model objects are below a lowest lane including a process step. | 0.534173 |
7,644,356 | 23 | 24 | 23. The method of claim 1 , wherein the determining comprises solving each set of constraints to obtain estimates of attributes and positions of the graphic elements in the determinate layouts. | 23. The method of claim 1 , wherein the determining comprises solving each set of constraints to obtain estimates of attributes and positions of the graphic elements in the determinate layouts. 24. The method of claim 23 , wherein the determining additionally comprises: correcting a set of attributes estimated for a given one of the graphic elements in a given candidate layout; modifying the set of constraints corresponding to the given candidate layout; and solving the modified set of constraints to obtain revised estimates of attributes and positions of the graphic elements in the determinate layout corresponding to the given candidate layout. | 0.5 |
7,657,515 | 7 | 8 | 7. The method of claim 1 , wherein the first list includes more than a thousand terms. | 7. The method of claim 1 , wherein the first list includes more than a thousand terms. 8. The method of claim 7 , wherein the second list includes more than a thousand terms. | 0.5 |
8,792,917 | 15 | 18 | 15. A non-transitory storage device storing computer instructions operable to cause one or more processors to perform operations comprising: receiving a current location of a mobile device and a context of the current location, the context comprising a pattern of movement of the mobile device and a horizontal accuracy of the current location; identifying, from a plurality of geofences, two or more geofences intersecting the current location; selecting a geofence from the two or more geofences using the context, wherein selecting the geofence comprises: determining a fence size for each of the two or more geofences; calculating match scores measuring matches between the fence sizes and the pattern of movement of the mobile device; and selecting the geofence based on the match scores; and determining that the mobile device is located in a geofenced area enclosed by the selected geofence. | 15. A non-transitory storage device storing computer instructions operable to cause one or more processors to perform operations comprising: receiving a current location of a mobile device and a context of the current location, the context comprising a pattern of movement of the mobile device and a horizontal accuracy of the current location; identifying, from a plurality of geofences, two or more geofences intersecting the current location; selecting a geofence from the two or more geofences using the context, wherein selecting the geofence comprises: determining a fence size for each of the two or more geofences; calculating match scores measuring matches between the fence sizes and the pattern of movement of the mobile device; and selecting the geofence based on the match scores; and determining that the mobile device is located in a geofenced area enclosed by the selected geofence. 18. The non-transitory storage device of claim 15 , wherein the horizontal accuracy is determined using one of a global positioning system (GPS), triangulation using locations of wireless access points of a wireless local area network (WLAN), and triangulation using locations of cell towers of a cellular communications network. | 0.5 |
9,237,211 | 1 | 27 | 1. An energy harvesting communication device configured with signal booster apparatus, comprising: at least a communication apparatus; at least an antenna apparatus communicatively coupled to the communication apparatus and in association with at least an input output (IO) device; at least a microprocessor configured with a software for controlling communications via the communication apparatus and for processing data associated with said IO device; said at least an antenna apparatus in communication with said at least a microprocessor; and at least a sensor apparatus embedded in silicon substrate and embedded in a microfiber material to provide at least one of a communication medium, communication clarity, a detection platform, detection selectivity, and detection sensitivity. | 1. An energy harvesting communication device configured with signal booster apparatus, comprising: at least a communication apparatus; at least an antenna apparatus communicatively coupled to the communication apparatus and in association with at least an input output (IO) device; at least a microprocessor configured with a software for controlling communications via the communication apparatus and for processing data associated with said IO device; said at least an antenna apparatus in communication with said at least a microprocessor; and at least a sensor apparatus embedded in silicon substrate and embedded in a microfiber material to provide at least one of a communication medium, communication clarity, a detection platform, detection selectivity, and detection sensitivity. 27. The energy harvesting communication device of claim 1 , wherein said at least an antenna apparatus in association with said at least a microprocessor for determining signal strength, further operable for determining at least one of: a plurality of wavelet coefficients corresponding to at least a received wireless signal; an average energy from the determined plurality of wavelet coefficients; energy harvesting platform; computing platform; gaming platform; downloadable platform; a social media platform; professional media platform; varying frequency platform; multiple network platform; a mirror platform; an averaging energy comprising a squared modulus for each of the determined plurality of wavelet coefficients. | 0.75137 |
8,744,861 | 13 | 18 | 13. A system for invoking a tapered prompt comprising a plurality of prompt elements, each prompt element comprising a voice component and a non-voice component, the system comprising at least one processor programmed to: select a first voice style for the voice component of a first prompt element in the plurality of prompt elements of the tapered prompt, wherein the voice component of the first prompt element solicits requested information from a user; select, in conjunction with selecting the first voice style, a first non-voice style for the non-voice component of the first prompt element, wherein the non-voice component of the first prompt element solicits the same requested information as the voice component of the first prompt element; receive voice input provided by the user in response to the first prompt element; process the voice input to determine whether the user provided the requested information; and in response to determining that at least some of the requested information was not provided by the user, select a second voice style for the voice component of a second prompt element of the tapered prompt, and select, in conjunction with selecting the second voice style, a second non-voice style for the non-voice component of the second prompt element, wherein: both the voice component and non-voice component of the second prompt element further solicit the at least some of the requested information from the user, the second voice style is different from the first voice style, and the second non-voice style is different from the first non-voice style. | 13. A system for invoking a tapered prompt comprising a plurality of prompt elements, each prompt element comprising a voice component and a non-voice component, the system comprising at least one processor programmed to: select a first voice style for the voice component of a first prompt element in the plurality of prompt elements of the tapered prompt, wherein the voice component of the first prompt element solicits requested information from a user; select, in conjunction with selecting the first voice style, a first non-voice style for the non-voice component of the first prompt element, wherein the non-voice component of the first prompt element solicits the same requested information as the voice component of the first prompt element; receive voice input provided by the user in response to the first prompt element; process the voice input to determine whether the user provided the requested information; and in response to determining that at least some of the requested information was not provided by the user, select a second voice style for the voice component of a second prompt element of the tapered prompt, and select, in conjunction with selecting the second voice style, a second non-voice style for the non-voice component of the second prompt element, wherein: both the voice component and non-voice component of the second prompt element further solicit the at least some of the requested information from the user, the second voice style is different from the first voice style, and the second non-voice style is different from the first non-voice style. 18. The system of claim 13 , wherein the at least one processor is further programmed to: audibly render the voice component of the first prompt element in the first voice style. | 0.646825 |
9,344,562 | 2 | 4 | 2. The method of claim 1 , wherein the feature of the graphical image comprises a transparency value associated a degree to which the graphical image of the textual interpretation blocks visibility of the media content that is being presented. | 2. The method of claim 1 , wherein the feature of the graphical image comprises a transparency value associated a degree to which the graphical image of the textual interpretation blocks visibility of the media content that is being presented. 4. The method of claim 2 , further comprising receiving, by the system, the user preference associated with the feature of the graphical image. | 0.64604 |
8,972,460 | 1 | 3 | 1. A computer implemented method for data model optimization using multilevel entity dependency analytics, the method comprising: accessing a multilevel schema data structure; determining, using a computer, a dependency relationship lineage between schema entities present in the multilevel schema data structure; generating a dependency table using the dependency relationship lineage, the dependency table comprising at least one multilevel dependency relationship between schema entities having a depth of two or more; using the dependency table to perform at least one analysis comprising at least one of, a high impact analysis, a referential integrity analysis, or a conformance analysis; and storing a result from the analysis in a stored metadata format. | 1. A computer implemented method for data model optimization using multilevel entity dependency analytics, the method comprising: accessing a multilevel schema data structure; determining, using a computer, a dependency relationship lineage between schema entities present in the multilevel schema data structure; generating a dependency table using the dependency relationship lineage, the dependency table comprising at least one multilevel dependency relationship between schema entities having a depth of two or more; using the dependency table to perform at least one analysis comprising at least one of, a high impact analysis, a referential integrity analysis, or a conformance analysis; and storing a result from the analysis in a stored metadata format. 3. The method of claim 1 , wherein the stored metadata format is at least one of, an XML format, a binary format, a message format, or a relational database table. | 0.5 |
7,644,069 | 1 | 8 | 1. A computer-implemented search ranking method suitable for a file system, comprising: receiving a query via a computer; calculating final relevance scores of individual file items via said computer with respect to said query at least partially in accordance with energy scores of individual nodes on a current file system energy tree, and outputting a list of search results based on said final relevance scores; and updating said energy scores of said individual nodes on said file system energy tree via said computer in response to an operation on said file system performed by a user, wherein said file system energy tree has a tree structure corresponding to that of said file system, and said individual nodes thereof respectively correspond to the individual file items in said file system. | 1. A computer-implemented search ranking method suitable for a file system, comprising: receiving a query via a computer; calculating final relevance scores of individual file items via said computer with respect to said query at least partially in accordance with energy scores of individual nodes on a current file system energy tree, and outputting a list of search results based on said final relevance scores; and updating said energy scores of said individual nodes on said file system energy tree via said computer in response to an operation on said file system performed by a user, wherein said file system energy tree has a tree structure corresponding to that of said file system, and said individual nodes thereof respectively correspond to the individual file items in said file system. 8. The method according to claim 1 , wherein said file item includes file and file folder. | 0.896552 |
8,321,398 | 1 | 7 | 1. A computer implemented method comprising: receiving a list comprising an entity, the entity having been identified as being associated with an electronic document; based solely upon a set of characteristics of the document, determining a relevancy score associated with the entity with respect to the document, wherein the set of characteristics includes at least one characteristic from the group consisting of: a first number representing a number of sentences occurring in the document prior to a first sentence in which the entity is named; a second number representing a number of sentences between first and last occurrences of the entity within the document; and a third number representing a uniformity with which the entity occurs within the document; and storing the relevancy score. | 1. A computer implemented method comprising: receiving a list comprising an entity, the entity having been identified as being associated with an electronic document; based solely upon a set of characteristics of the document, determining a relevancy score associated with the entity with respect to the document, wherein the set of characteristics includes at least one characteristic from the group consisting of: a first number representing a number of sentences occurring in the document prior to a first sentence in which the entity is named; a second number representing a number of sentences between first and last occurrences of the entity within the document; and a third number representing a uniformity with which the entity occurs within the document; and storing the relevancy score. 7. The method of claim 1 , wherein the document is unstructured. | 0.934021 |
7,765,178 | 8 | 9 | 8. The method of claim 4 , further comprising repeatedly generating the updated probabilities that the leaf categories of the taxonomy contain relevant documents based on the previous updated probabilities that the leaf categories of the taxonomy contain relevant documents and re-determining the updated relevance of documents to the query. | 8. The method of claim 4 , further comprising repeatedly generating the updated probabilities that the leaf categories of the taxonomy contain relevant documents based on the previous updated probabilities that the leaf categories of the taxonomy contain relevant documents and re-determining the updated relevance of documents to the query. 9. The method of claim 8 , wherein generating the updated probabilities that the leaf categories of the taxonomy contain relevant documents ceases when a change in the updated probabilities is less than a predetermined convergence threshold. | 0.5 |
8,484,557 | 8 | 9 | 8. A non-transitory machine-readable medium having instructions that, when executed by processor, cause a machine to perform operations including: creating and storing a first set of attribute information associated with a first preflight rule in an attribute table uniquely associated with the first preflight rule, the first set comprising a summary of at least a first parameter, a second parameter, and a data type of the first parameter and a data type of the second parameter, the data type of the first parameter and data type of the second parameter representing a format of the first parameter and a format of the second parameter; defining relationship information between the first parameter and the second parameter in the preflight rule, the relationship information placing constraints on parameter values for the first parameter and the second parameter in the preflight rule to maintain consistency between the first parameter and second parameter in the preflight rule, the relationship information stored to a relationship table that is suitable for use by at least one handler to check for consistency between the parameter values for the first parameter and the second parameter in the preflight rule; and responsive to receiving a request to modify the first preflight rule: creating a control interface based on at least one of the defined data types representing the format of the first or the second parameter; presenting the first parameter or the second parameter using the control interface; receiving updated information related to at least one of the first parameter or the second parameter; storing the updated information in the attribute table uniquely associated with the first preflight rule, the updated information including at least one of a parameter or a parameter value; and generating an updated first set of attribute information using the received updated information. | 8. A non-transitory machine-readable medium having instructions that, when executed by processor, cause a machine to perform operations including: creating and storing a first set of attribute information associated with a first preflight rule in an attribute table uniquely associated with the first preflight rule, the first set comprising a summary of at least a first parameter, a second parameter, and a data type of the first parameter and a data type of the second parameter, the data type of the first parameter and data type of the second parameter representing a format of the first parameter and a format of the second parameter; defining relationship information between the first parameter and the second parameter in the preflight rule, the relationship information placing constraints on parameter values for the first parameter and the second parameter in the preflight rule to maintain consistency between the first parameter and second parameter in the preflight rule, the relationship information stored to a relationship table that is suitable for use by at least one handler to check for consistency between the parameter values for the first parameter and the second parameter in the preflight rule; and responsive to receiving a request to modify the first preflight rule: creating a control interface based on at least one of the defined data types representing the format of the first or the second parameter; presenting the first parameter or the second parameter using the control interface; receiving updated information related to at least one of the first parameter or the second parameter; storing the updated information in the attribute table uniquely associated with the first preflight rule, the updated information including at least one of a parameter or a parameter value; and generating an updated first set of attribute information using the received updated information. 9. The non-transitory machine-readable medium of claim 8 , wherein each of the first parameter or the second parameter is defined based on a data type and a control interface. | 0.5 |
10,140,971 | 1 | 3 | 1. A method of on-site speech broadcasting, comprising: receiving a text signal, wherein the text signal is automatically generated by an on-site text-generating device in response to a parameter in an industrial environment sensed by an on-site sensor of the on-site text-generating device reaching a predetermined value; converting the text signal to a speech signal by an on-site speech converting module disposed within an on-site speaker device separated from the on-site text-generating device; and playing the converted speech signal by using a speaker of the on-site speaker device to broadcast an alarm in the industrial environment, wherein the text signal is generated by automatically selecting the text signal from a plurality of text signals preset by an on-site user to correspond to the parameter reaching the predetermined value, wherein the on-site text-generating device further includes a human machine interface for automatically selecting a text from a plurality of texts without input of the on-site user, and a transmitting interface for transmitting the text signal, wherein the human machine interface comprises a processor for determining an event indicating a certain device in the industrial environment is abnormal based on the parameter sensed by the on-site sensor, and wherein the text of the plurality of texts corresponds to the event. | 1. A method of on-site speech broadcasting, comprising: receiving a text signal, wherein the text signal is automatically generated by an on-site text-generating device in response to a parameter in an industrial environment sensed by an on-site sensor of the on-site text-generating device reaching a predetermined value; converting the text signal to a speech signal by an on-site speech converting module disposed within an on-site speaker device separated from the on-site text-generating device; and playing the converted speech signal by using a speaker of the on-site speaker device to broadcast an alarm in the industrial environment, wherein the text signal is generated by automatically selecting the text signal from a plurality of text signals preset by an on-site user to correspond to the parameter reaching the predetermined value, wherein the on-site text-generating device further includes a human machine interface for automatically selecting a text from a plurality of texts without input of the on-site user, and a transmitting interface for transmitting the text signal, wherein the human machine interface comprises a processor for determining an event indicating a certain device in the industrial environment is abnormal based on the parameter sensed by the on-site sensor, and wherein the text of the plurality of texts corresponds to the event. 3. The method according to claim 1 , wherein the text signal comprises at least two languages. | 0.835088 |
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