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7,536,641 | 12 | 16 | 12. A computer readable storage medium storing one or more programs for execution by a computer, the one or more programs, including a web browser-based web page authoring tool, comprising: a web page editor embedded in an authoring web page, the authoring web page suitable for display by a web browser; and the web page editor including a web server communication interface for communication with a remote server; wherein the web page editor includes instructions for: displaying a graphical user interface of the web page editor; updating a user defined web page displayed in a first web browser window of the web browser in accordance with user inputs received using the graphical user interface; defining multiple user-specified fields in the first web browser window of the web browser each of a plurality of the user-specified fields having a visible and adjustable boundary; saving the user inputs to the remote server through the web server communication interface; and displaying a preview of the user defined web page in a second web browser window of the web browser in a manner consistent with the user defined web page displayed in the first web browser window of the web browser in response to a user instruction. | 12. A computer readable storage medium storing one or more programs for execution by a computer, the one or more programs, including a web browser-based web page authoring tool, comprising: a web page editor embedded in an authoring web page, the authoring web page suitable for display by a web browser; and the web page editor including a web server communication interface for communication with a remote server; wherein the web page editor includes instructions for: displaying a graphical user interface of the web page editor; updating a user defined web page displayed in a first web browser window of the web browser in accordance with user inputs received using the graphical user interface; defining multiple user-specified fields in the first web browser window of the web browser each of a plurality of the user-specified fields having a visible and adjustable boundary; saving the user inputs to the remote server through the web server communication interface; and displaying a preview of the user defined web page in a second web browser window of the web browser in a manner consistent with the user defined web page displayed in the first web browser window of the web browser in response to a user instruction. 16. The computer readable storage medium of claim 12 , wherein the web page editor includes instructions for: allowing the user to move a content object from a source location to a destination location in the web page; and adjusting other content near the source and destination locations to accommodate the movement of the content object. | 0.691818 |
9,230,214 | 10 | 11 | 10. The method of claim 1 , further comprising displaying one or more text strings from the set of potential replacement text strings as suggestions for selection by the user to replace the input text string. | 10. The method of claim 1 , further comprising displaying one or more text strings from the set of potential replacement text strings as suggestions for selection by the user to replace the input text string. 11. The method of claim 10 , further comprising: receiving the selection from the user; and replacing the input text string with the selection. | 0.964286 |
7,603,276 | 1 | 3 | 1. A standard model creating apparatus for creating a standard model which shows an acoustic characteristic having a specific attribute and is used for speech recognition in an electronic apparatus used by a user, the standard model creating apparatus using a probability model that expresses a frequency parameter showing an acoustic characteristic as an output probability, the standard model creating apparatus comprising: a reference model storing unit configured to store a plurality of reference models which are probability models showing an acoustic characteristic having a specific attribute; and a standard model creating unit configured to create the standard model by calculating statistics of the standard model using statistics of the plurality of reference models stored in said reference model storing unit, wherein said standard model creating unit includes: a standard model structure determining unit configured to determine a structure of the standard model which is to be created, based on specification information regarding specifications of the electronic apparatus; an initial standard model creating unit configured to determine initial values of the statistics specifying the standard model whose structure has been determined; and a statistics estimating unit configured to estimate and calculate the statistics of the standard model so as to maximize or locally maximize a probability or a likelihood of the standard model, whose initial values have been determined, with respect to the plurality of reference models, wherein the plurality of reference models and the standard model are expressed using at least one Gaussian distribution, said standard model structure determining unit is configured to determine a number of statistics of the standard model including at least a number of Gaussian mixture distributions as the structure of the standard model, said standard model structure determining unit is configured to determine a Gaussian mixture distribution having an Mf (Mf≧1) number of mixture distributions as the structure of the standard model, and said statistics estimating unit is configured to calculate at least one of a mixture weighting coefficient ω f(m) (m=1,2, . . . , M f ), a mean value μ f(m) (m=1,2, . . . , M f ), and a variance σ f(m) 2 (m=1,2, . . . , M f ) which are the statistics of the standard model ∑ m = 1 M f ω f ( m ) f ( x ; μ f ( m ) , σ f ( m ) 2 ) (where f(x;μ f(m) ,σ f(m) 2 ) (m=1,2, . . . , M f ) represents a Gaussian distribution, and χ represents input data) represented by the Gaussian mixture distribution so as to maximize or locally maximize a likelihood log P = ∑ i = 1 N g ∫ - ∞ ∞ log [ ∑ m = 1 M f ω f ( m ) f ( x ; μ f ( m ) , σ f ( m ) 2 ) ] { ∑ i = 1 L g ( i ) υ g ( i , l ) g ( x ; μ g ( i , l ) , σ g ( i , l ) 2 ) } ⅆ x of the standard model, with respect to Ng (Ng≧2) reference models ∑ l = i L g ( i ) υ g ( i , l ) g ( x ; μ g ( i , l ) , σ g ( i , l ) 2 ) ( i = 1 , 2 , … , N g ) (where g(x;μ g(i,l) ,σ g(i,l) 2 ) (i=1,2, . . . , N g , l=1,2, . . . , L (i) ) represents a Gaussian distribution, L g(i) (i=1,2, . . . , N g ) represents a mixture distribution of each of reference models, ν g(i,l) (l=1,2, . . . , L g(i) ) represents a mixture weighting coefficient, μ 2 g(i,l) (l=1,2, . . . , L g(i) ) represents a mean value, and σ g(i,l) 2 (l=1,2, . . . , L g(i) ) represents a variance). | 1. A standard model creating apparatus for creating a standard model which shows an acoustic characteristic having a specific attribute and is used for speech recognition in an electronic apparatus used by a user, the standard model creating apparatus using a probability model that expresses a frequency parameter showing an acoustic characteristic as an output probability, the standard model creating apparatus comprising: a reference model storing unit configured to store a plurality of reference models which are probability models showing an acoustic characteristic having a specific attribute; and a standard model creating unit configured to create the standard model by calculating statistics of the standard model using statistics of the plurality of reference models stored in said reference model storing unit, wherein said standard model creating unit includes: a standard model structure determining unit configured to determine a structure of the standard model which is to be created, based on specification information regarding specifications of the electronic apparatus; an initial standard model creating unit configured to determine initial values of the statistics specifying the standard model whose structure has been determined; and a statistics estimating unit configured to estimate and calculate the statistics of the standard model so as to maximize or locally maximize a probability or a likelihood of the standard model, whose initial values have been determined, with respect to the plurality of reference models, wherein the plurality of reference models and the standard model are expressed using at least one Gaussian distribution, said standard model structure determining unit is configured to determine a number of statistics of the standard model including at least a number of Gaussian mixture distributions as the structure of the standard model, said standard model structure determining unit is configured to determine a Gaussian mixture distribution having an Mf (Mf≧1) number of mixture distributions as the structure of the standard model, and said statistics estimating unit is configured to calculate at least one of a mixture weighting coefficient ω f(m) (m=1,2, . . . , M f ), a mean value μ f(m) (m=1,2, . . . , M f ), and a variance σ f(m) 2 (m=1,2, . . . , M f ) which are the statistics of the standard model ∑ m = 1 M f ω f ( m ) f ( x ; μ f ( m ) , σ f ( m ) 2 ) (where f(x;μ f(m) ,σ f(m) 2 ) (m=1,2, . . . , M f ) represents a Gaussian distribution, and χ represents input data) represented by the Gaussian mixture distribution so as to maximize or locally maximize a likelihood log P = ∑ i = 1 N g ∫ - ∞ ∞ log [ ∑ m = 1 M f ω f ( m ) f ( x ; μ f ( m ) , σ f ( m ) 2 ) ] { ∑ i = 1 L g ( i ) υ g ( i , l ) g ( x ; μ g ( i , l ) , σ g ( i , l ) 2 ) } ⅆ x of the standard model, with respect to Ng (Ng≧2) reference models ∑ l = i L g ( i ) υ g ( i , l ) g ( x ; μ g ( i , l ) , σ g ( i , l ) 2 ) ( i = 1 , 2 , … , N g ) (where g(x;μ g(i,l) ,σ g(i,l) 2 ) (i=1,2, . . . , N g , l=1,2, . . . , L (i) ) represents a Gaussian distribution, L g(i) (i=1,2, . . . , N g ) represents a mixture distribution of each of reference models, ν g(i,l) (l=1,2, . . . , L g(i) ) represents a mixture weighting coefficient, μ 2 g(i,l) (l=1,2, . . . , L g(i) ) represents a mean value, and σ g(i,l) 2 (l=1,2, . . . , L g(i) ) represents a variance). 3. The standard model creating apparatus according to claim 1 , further comprising: a specification information holding unit configured to store an application/specifications correspondence database showing a correspondence between an application program which uses the standard model and specifications of the standard model, wherein said standard model structure determining unit is configured to read specifications corresponding to an application program to be activated from the application/specifications correspondence database held by said specification information holding unit, and to determine the structure of the standard model based on the read specifications. | 0.500741 |
8,768,910 | 16 | 18 | 16. A system comprising: a memory to store a keyword list associated with a category of media items; and one or more processors to: obtain a search query, identify candidate queries for the search query, determine whether the candidate queries match words in the keyword list, determine a first ratio based on a first quantity of times that the search query is submitted to a web search engine interface, determine a second ratio based on a second quantity of times that the search query is submitted to a specialized search engine interface that is used to search for information associated with the category or to search for information associated with news, identify, based on the first ratio and the second ratio, the search query as a media query associated with the category when the candidate queries match one or more of the words in the keyword list, and provide, based on identifying the search query as the media query, a result document based on the media query. | 16. A system comprising: a memory to store a keyword list associated with a category of media items; and one or more processors to: obtain a search query, identify candidate queries for the search query, determine whether the candidate queries match words in the keyword list, determine a first ratio based on a first quantity of times that the search query is submitted to a web search engine interface, determine a second ratio based on a second quantity of times that the search query is submitted to a specialized search engine interface that is used to search for information associated with the category or to search for information associated with news, identify, based on the first ratio and the second ratio, the search query as a media query associated with the category when the candidate queries match one or more of the words in the keyword list, and provide, based on identifying the search query as the media query, a result document based on the media query. 18. The system of claim 16 , where, when determining whether the candidate queries match the words in the keyword list, the one or more processors are further to: determine a first quantity based on at least one of a second quantity of the candidate queries or a third quantity of the words in the keyword list, determine a fourth quantity of matching words that are included as both part of the candidate queries and the words in the keyword list, and determine that the candidate queries match one or more of the words in the keyword list when the fourth quantity is greater than or equal to the first quantity. | 0.744583 |
8,762,934 | 1 | 10 | 1. A method of defining a business object model comprising: defining a plurality of named logical types, field-sets, business objects and sub-objects, structures and enumerations that are referenced in the model by their names, wherein defining the business objects further comprises listing the plurality of their fields, each field having a type attribute referencing a logical type defined in the model, and field-sets, each field-set referencing a corresponding field-set defined in the model and the plurality of business object operations and sub-objects; wherein defining business objects and sub-objects further comprises marking a single field or a field-set with a key attribute, which indicates that the key is serial (for fields only), or is user-supplied, or is a reference to another object's key attribute; and wherein no two objects can both have their key fields marked as serial or marked as user-supplied with the same logical types, and wherein no two objects can both have their key field-sets marked as user-supplied and as referencing the same field-set defined in the business object model. | 1. A method of defining a business object model comprising: defining a plurality of named logical types, field-sets, business objects and sub-objects, structures and enumerations that are referenced in the model by their names, wherein defining the business objects further comprises listing the plurality of their fields, each field having a type attribute referencing a logical type defined in the model, and field-sets, each field-set referencing a corresponding field-set defined in the model and the plurality of business object operations and sub-objects; wherein defining business objects and sub-objects further comprises marking a single field or a field-set with a key attribute, which indicates that the key is serial (for fields only), or is user-supplied, or is a reference to another object's key attribute; and wherein no two objects can both have their key fields marked as serial or marked as user-supplied with the same logical types, and wherein no two objects can both have their key field-sets marked as user-supplied and as referencing the same field-set defined in the business object model. 10. The method of claim 1 , wherein defining business objects and sub-objects further comprises specifying additional extensible configuration for the objects including, but not limited to, mappings to corresponding database tables and custom service attributes where applicable. | 0.78991 |
9,053,091 | 12 | 13 | 12. The non-transitory machine-readable storage medium of claim 11 , wherein the operations further comprise: the assigned value represents a relevance probability of the first token; and the computing of the relevance value of the group of tokens is based on the relevance probability of the first token and further based on an irrelevance probability of the first token. | 12. The non-transitory machine-readable storage medium of claim 11 , wherein the operations further comprise: the assigned value represents a relevance probability of the first token; and the computing of the relevance value of the group of tokens is based on the relevance probability of the first token and further based on an irrelevance probability of the first token. 13. The non-transitory machine-readable storage medium of claim 12 , wherein the operations further comprise: determining the irrelevance probability based on a proportion of descriptions that contain the first token within a set of descriptions. | 0.901757 |
7,809,719 | 14 | 17 | 14. A system to assist a user comprising a computing device comprising a memory and a processor that is communicatively coupled to the memory; an input component to receive user input to the computing device; a store component that stores the input in chronological order; a prediction component coupled to the memory that functions to predict a textual candidate selected from at least one of a next word or a phrase that is associated with the user input, wherein the predicting comprises: determining a textual candidate probability using one or more preceding words in the store component and an n-gram probability model, wherein each textual candidate probability is based in part on a first quantity that corresponds with a number of times the textual candidate follows the number of preceding textual words in the store component and the number of times that the number of preceding textual words occur in the store component and a second quantity that corresponds with a number of times the textual candidate is observed in the store component and the total number of words in the store component; a suggestion component to suggest the textual candidate as a suggested candidate, wherein the suggestion is produced by: selecting a number of top textual candidates based on the textual candidate probabilities; determining adjusted probabilities of the selected top textual candidates, wherein each adjusted candidate probability is based in part on a candidate rank function multiplied by a first variable and an associated textual candidate probability multiplied by a second variable, wherein the candidate rank function is based in part on a third quantity that corresponds with the selected top textual candidate rank values; and the store component of the computing device storing the textual candidate. | 14. A system to assist a user comprising a computing device comprising a memory and a processor that is communicatively coupled to the memory; an input component to receive user input to the computing device; a store component that stores the input in chronological order; a prediction component coupled to the memory that functions to predict a textual candidate selected from at least one of a next word or a phrase that is associated with the user input, wherein the predicting comprises: determining a textual candidate probability using one or more preceding words in the store component and an n-gram probability model, wherein each textual candidate probability is based in part on a first quantity that corresponds with a number of times the textual candidate follows the number of preceding textual words in the store component and the number of times that the number of preceding textual words occur in the store component and a second quantity that corresponds with a number of times the textual candidate is observed in the store component and the total number of words in the store component; a suggestion component to suggest the textual candidate as a suggested candidate, wherein the suggestion is produced by: selecting a number of top textual candidates based on the textual candidate probabilities; determining adjusted probabilities of the selected top textual candidates, wherein each adjusted candidate probability is based in part on a candidate rank function multiplied by a first variable and an associated textual candidate probability multiplied by a second variable, wherein the candidate rank function is based in part on a third quantity that corresponds with the selected top textual candidate rank values; and the store component of the computing device storing the textual candidate. 17. The system of claim 14 , further comprising a collection component to collect user input including a selected textual candidate and to store the collected user input and selected textual candidate as a text stream in chronological order to the store component. | 0.870079 |
10,042,549 | 14 | 15 | 14. The device of claim 11 , wherein the subsequent portion of the gesture comprises the contact being maintained at a same location as the initial portion of the gesture. | 14. The device of claim 11 , wherein the subsequent portion of the gesture comprises the contact being maintained at a same location as the initial portion of the gesture. 15. The device of claim 14 , wherein the first dynamic disambiguation threshold is a first speed threshold. | 0.971693 |
9,495,345 | 9 | 10 | 9. The method of claim 1 , further comprising: receiving an input to identify which documents in the plurality of documents are to be classified into the first node; in response to said input, analyzing the plurality of documents by the natural language model, using the at least one rule, to determine which documents are to be classified into the first node; and causing display of the documents that are determined to be classified into the first node. | 9. The method of claim 1 , further comprising: receiving an input to identify which documents in the plurality of documents are to be classified into the first node; in response to said input, analyzing the plurality of documents by the natural language model, using the at least one rule, to determine which documents are to be classified into the first node; and causing display of the documents that are determined to be classified into the first node. 10. The method of claim 9 , further comprising causing display of documents that are determined to be classified into the first node, wherein the determination is made at least in part by the document triggering the at least one rule. | 0.925667 |
7,831,869 | 4 | 5 | 4. The method as claimed in claim 1 , wherein each of said rows comprises 128 bytes, and each of the code words comprises 32 bytes. | 4. The method as claimed in claim 1 , wherein each of said rows comprises 128 bytes, and each of the code words comprises 32 bytes. 5. The method as claimed in claim 4 , wherein each of said columns comprises 124 bytes. | 0.970942 |
8,832,103 | 8 | 15 | 8. In a computing system environment, a method of filtering to users relevancy data available from one or more computing devices, comprising: from a plurality of original files on the one or more computing devices, each file representing an underlying original bits of data and representative of a relevancy topic, creating a key in a multi-dimensional mapping space for the relevancy topic wherein the multi-dimensional mapping space is defined by an N-dimensional space according to a number of symbols N corresponding to the underlying original bits of data, said key being created by defining a digital spectrum of each of said plurality of files from an entirety of said original bits of data of said plurality of files, aggregating each said digital spectrum of each of said plurality of files, and plotting said aggregated digital spectrum as defining a single point in the multi-dimensional mapping space representing the relevancy topic for said plurality of original files; defining a measure of closeness to the key in the multi-dimensional mapping space; and presenting to users new data from the one or more computing devices sufficiently related to the relevancy topic that is within the measure of closeness. | 8. In a computing system environment, a method of filtering to users relevancy data available from one or more computing devices, comprising: from a plurality of original files on the one or more computing devices, each file representing an underlying original bits of data and representative of a relevancy topic, creating a key in a multi-dimensional mapping space for the relevancy topic wherein the multi-dimensional mapping space is defined by an N-dimensional space according to a number of symbols N corresponding to the underlying original bits of data, said key being created by defining a digital spectrum of each of said plurality of files from an entirety of said original bits of data of said plurality of files, aggregating each said digital spectrum of each of said plurality of files, and plotting said aggregated digital spectrum as defining a single point in the multi-dimensional mapping space representing the relevancy topic for said plurality of original files; defining a measure of closeness to the key in the multi-dimensional mapping space; and presenting to users new data from the one or more computing devices sufficiently related to the relevancy topic that is within the measure of closeness. 15. The method of claim 8 , further including creating a second key for a second relevancy topic. | 0.873037 |
7,836,148 | 1 | 14 | 1. A method of dynamically generating a display page, comprising: using a processor to obtain an object tree comprising a plurality of hierarchically organized objects, each object containing data and methods for processing a corresponding definitional element of said display page; using the processor to modify said object tree at runtime; and using the processor to invoke said methods of the objects comprising the object tree as modified to generate, dynamically at runtime, a plurality of definitional statements, each definitional statement being associated with one or more definitional elements of said display page; wherein said methods for processing a corresponding definitional element of said display page comprise computer instructions which when executed generate said plurality of definitional statements; wherein said definitional statements comprise hypertext markup language (HTML) or other statements usable by a browser or other software to render the display page; and wherein the display page generated using the objects comprising the object tree as modified reflects the modification made to said object tree at runtime. | 1. A method of dynamically generating a display page, comprising: using a processor to obtain an object tree comprising a plurality of hierarchically organized objects, each object containing data and methods for processing a corresponding definitional element of said display page; using the processor to modify said object tree at runtime; and using the processor to invoke said methods of the objects comprising the object tree as modified to generate, dynamically at runtime, a plurality of definitional statements, each definitional statement being associated with one or more definitional elements of said display page; wherein said methods for processing a corresponding definitional element of said display page comprise computer instructions which when executed generate said plurality of definitional statements; wherein said definitional statements comprise hypertext markup language (HTML) or other statements usable by a browser or other software to render the display page; and wherein the display page generated using the objects comprising the object tree as modified reflects the modification made to said object tree at runtime. 14. The method of claim 1 , wherein obtaining the object tree comprises generating the object tree based at least in part on a template. | 0.824742 |
8,341,610 | 3 | 10 | 3. A method as in claim 2 , wherein the questions have associated costs expressed in some unit of measure, and wherein the flowchart presents the questions in an optimally informative order. | 3. A method as in claim 2 , wherein the questions have associated costs expressed in some unit of measure, and wherein the flowchart presents the questions in an optimally informative order. 10. A method as in claim 3 , wherein the optimally informative order of questions is determined automatically from probabilities contained in cell values in the dependency matrix. | 0.929416 |
7,792,832 | 37 | 39 | 37. An article of manufacture comprising a machine-readable storage medium with instruction code stored in the medium, said instruction code, when executed by a data processing system comprising a processor, causes the processor to perform the following steps to identify products potentially infringing a patent: receiving an identifier of the patent; retrieving text of the patent; parsing the text of the patent to identify claims section of the text of the patent; parsing the claims section to identify one or more individual claims of the patent; parsing the individual claims of the patent to identify one or more independent claims of the patent, the one or more independent claims comprising a first independent claim; identifying a preamble of the first independent claim; identifying one or more limitations of the first independent claim; identifying one or more key terms for each limitation of the one or more limitations; formulating at least one query to search for data items that include the key terms of the one or more limitations of the first independent claim; launching the at least one query; receiving search results responsive to the at least one query; and reviewing the search results of the query; wherein the code causes the processor, in the course of performing the step of identifying one or more key terms, to perform steps comprising: for each word of a plurality of words in the one or more limitations, calculating a ratio of (1) frequency of occurrence within the text of the patent of said each word to (2) frequency of occurrence of said each word in a neutral text not related to the patent or to technology of the patent, thereby obtaining a plurality of ratios, each ratio of the plurality of ratios corresponding to a different said each word; comparing each ratio of the plurality of ratios to a first predetermined parameter to obtain a plurality of key terms, a key term being a word of the plurality of words corresponding to a ratio of the plurality of ratios that exceeds the first predetermined parameter. | 37. An article of manufacture comprising a machine-readable storage medium with instruction code stored in the medium, said instruction code, when executed by a data processing system comprising a processor, causes the processor to perform the following steps to identify products potentially infringing a patent: receiving an identifier of the patent; retrieving text of the patent; parsing the text of the patent to identify claims section of the text of the patent; parsing the claims section to identify one or more individual claims of the patent; parsing the individual claims of the patent to identify one or more independent claims of the patent, the one or more independent claims comprising a first independent claim; identifying a preamble of the first independent claim; identifying one or more limitations of the first independent claim; identifying one or more key terms for each limitation of the one or more limitations; formulating at least one query to search for data items that include the key terms of the one or more limitations of the first independent claim; launching the at least one query; receiving search results responsive to the at least one query; and reviewing the search results of the query; wherein the code causes the processor, in the course of performing the step of identifying one or more key terms, to perform steps comprising: for each word of a plurality of words in the one or more limitations, calculating a ratio of (1) frequency of occurrence within the text of the patent of said each word to (2) frequency of occurrence of said each word in a neutral text not related to the patent or to technology of the patent, thereby obtaining a plurality of ratios, each ratio of the plurality of ratios corresponding to a different said each word; comparing each ratio of the plurality of ratios to a first predetermined parameter to obtain a plurality of key terms, a key term being a word of the plurality of words corresponding to a ratio of the plurality of ratios that exceeds the first predetermined parameter. 39. The article of manufacture of claim 37 , wherein the code further causes the processor to perform the step of generating a claim chart after the step of identifying one or more key terms. | 0.90185 |
9,087,204 | 1 | 10 | 1. A decryption system for decrypting user information encrypted on a storage device associated with an identity document of a user, the system comprising: a server configured to collect user identity document data from the user and to construct a token comprising the user identity document data, wherein the server is further configured to send the token to a mobile device associated with the user for storing the token at the mobile device and wherein the mobile device is physically separate from said storage device; a key construction unit communicatively coupled to a machine reader configured to read the data from the token by radio frequency identification communication with the mobile device, wherein the token further comprises user identification information and in particular in which the reader is further configured to read the user identification information from the token and wherein the key construction unit uses the user identity document data read from the token, stored on the mobile device, to construct a key for decrypting the user information stored on said storage device; a comparator for comparing the user identification information read from the token stored on the mobile device and the user information decrypted from said storage device associated with the user identity document; and authentication means for authenticating the user depending upon the result of the comparison. | 1. A decryption system for decrypting user information encrypted on a storage device associated with an identity document of a user, the system comprising: a server configured to collect user identity document data from the user and to construct a token comprising the user identity document data, wherein the server is further configured to send the token to a mobile device associated with the user for storing the token at the mobile device and wherein the mobile device is physically separate from said storage device; a key construction unit communicatively coupled to a machine reader configured to read the data from the token by radio frequency identification communication with the mobile device, wherein the token further comprises user identification information and in particular in which the reader is further configured to read the user identification information from the token and wherein the key construction unit uses the user identity document data read from the token, stored on the mobile device, to construct a key for decrypting the user information stored on said storage device; a comparator for comparing the user identification information read from the token stored on the mobile device and the user information decrypted from said storage device associated with the user identity document; and authentication means for authenticating the user depending upon the result of the comparison. 10. A decryption system according to claim 1 in which the reader is a wireless reading means. | 0.896437 |
8,706,739 | 6 | 7 | 6. A system for matching multiple user profiles from separate online social networks (OSNs), comprising: a processor; a profile tokenizer executing on the processor and configured to: extract target OSN user profile tokens from a target OSN user profile of a target user, wherein the target OSN user profile belongs to the target user in a first OSN of the plurality of OSNs, wherein extracting the target OSN user profile tokens from the target OSN user profile comprises: retrieving a target OSN user profile entry from the target OSN user profile; generating a target OSN user profile key token from the target OSN user profile entry based on a first sequence of alphanumeric characters in the target OSN user profile entry; and generating a target OSN user profile derived token from the target OSN user profile key token based on a first segment of the first sequence wherein the first segment is delimited within the target OSN user profile entry using a set of pre-determined special characters, wherein the target OSN user profile tokens comprise the target OSN user profile key token and target OSN user profile derived token; extract candidate OSN user profile tokens from a candidate OSN user profile of a candidate user, wherein the candidate OSN user profile belongs to the candidate user in a second OSN of the plurality of OSNs, wherein extracting the candidate OSN user profile tokens from the candidate OSN user profile comprises: retrieving a candidate OSN user profile entry from the candidate OSN user profile; generating a candidate OSN user profile key token from the candidate OSN user profile entry based on a second sequence of alphanumeric characters in the candidate OSN user profile entry; and generating a candidate OSN user profile derived token from the candidate OSN user profile key token based on a second segment of the second sequence, wherein the second segment is delimited within the candidate OSN user profile entry using the set of pre-determined special characters, wherein the candidate OSN user profile tokens comprise the candidate OSN user profile key token and candidate OSN user profile derived token; and a profiler matcher executing on the processor and configured to: calculate a first similarity measure between the candidate OSN user profile and the target OSN user profile based on a first tally of a plurality of key tokens shared by the candidate OSN user profile tokens and the target OSN user profile tokens; calculate a second similarity measure between the candidate OSN user profile and the target OSN user profile based on a second tally of a plurality of derived tokens shared by the candidate OSN user profile tokens and the target OSN user profile tokens; aggregate, based on a pre-determined formula, the first similarity measure and the second similarity measure to generate a score; determine, in response to the score exceeding a pre-determined threshold, the target user and the candidate user as a single person; and combine, in response to at least the score exceeding the pre-determined threshold, the multiple user profiles from the separate OSNs for storing as an expanded profile of the single person, wherein the multiple user profiles comprise the target OSN user profile and the candidate OSN user profile, wherein the separate OSNs comprise the first OSN and the second OSN. | 6. A system for matching multiple user profiles from separate online social networks (OSNs), comprising: a processor; a profile tokenizer executing on the processor and configured to: extract target OSN user profile tokens from a target OSN user profile of a target user, wherein the target OSN user profile belongs to the target user in a first OSN of the plurality of OSNs, wherein extracting the target OSN user profile tokens from the target OSN user profile comprises: retrieving a target OSN user profile entry from the target OSN user profile; generating a target OSN user profile key token from the target OSN user profile entry based on a first sequence of alphanumeric characters in the target OSN user profile entry; and generating a target OSN user profile derived token from the target OSN user profile key token based on a first segment of the first sequence wherein the first segment is delimited within the target OSN user profile entry using a set of pre-determined special characters, wherein the target OSN user profile tokens comprise the target OSN user profile key token and target OSN user profile derived token; extract candidate OSN user profile tokens from a candidate OSN user profile of a candidate user, wherein the candidate OSN user profile belongs to the candidate user in a second OSN of the plurality of OSNs, wherein extracting the candidate OSN user profile tokens from the candidate OSN user profile comprises: retrieving a candidate OSN user profile entry from the candidate OSN user profile; generating a candidate OSN user profile key token from the candidate OSN user profile entry based on a second sequence of alphanumeric characters in the candidate OSN user profile entry; and generating a candidate OSN user profile derived token from the candidate OSN user profile key token based on a second segment of the second sequence, wherein the second segment is delimited within the candidate OSN user profile entry using the set of pre-determined special characters, wherein the candidate OSN user profile tokens comprise the candidate OSN user profile key token and candidate OSN user profile derived token; and a profiler matcher executing on the processor and configured to: calculate a first similarity measure between the candidate OSN user profile and the target OSN user profile based on a first tally of a plurality of key tokens shared by the candidate OSN user profile tokens and the target OSN user profile tokens; calculate a second similarity measure between the candidate OSN user profile and the target OSN user profile based on a second tally of a plurality of derived tokens shared by the candidate OSN user profile tokens and the target OSN user profile tokens; aggregate, based on a pre-determined formula, the first similarity measure and the second similarity measure to generate a score; determine, in response to the score exceeding a pre-determined threshold, the target user and the candidate user as a single person; and combine, in response to at least the score exceeding the pre-determined threshold, the multiple user profiles from the separate OSNs for storing as an expanded profile of the single person, wherein the multiple user profiles comprise the target OSN user profile and the candidate OSN user profile, wherein the separate OSNs comprise the first OSN and the second OSN. 7. The system of claim 6 , wherein the system further comprises a personal information analyzer configured to: analyze the expanded profile to generate a personal information report of the target user. | 0.747487 |
7,529,737 | 28 | 29 | 28. A computer containing a processor configured to create models by retrieving information organized in documents containing information in the form of text, meta-data, citation information and potentially other types of information comprising the steps of: obtaining and labeling a selected set of documents; extracting and selecting features from each document in the selected set; representing the extracted and selected features; dividing the set of documents into a plurality of splits of documents, each split comprising first, second, and third subsets of the documents in the split; constructing models using a parametric learning algorithm, the constructed models being capable of assigning a label to a document, the models being instantiated using the first subset of a first of the plurality of splits of documents, and parameters associated with the model being chosen by validating the model against the second subset of the first of the plurality of splits; repeating the constructing, instantiating, and validating steps for each of the second and subsequent splits in the plurality of splits; testing the validated models by applying them to the third subset of a respective split; and selecting a best validated model, wherein the best validated model is configured to assign labels to documents exclusive of the selected set of documents. | 28. A computer containing a processor configured to create models by retrieving information organized in documents containing information in the form of text, meta-data, citation information and potentially other types of information comprising the steps of: obtaining and labeling a selected set of documents; extracting and selecting features from each document in the selected set; representing the extracted and selected features; dividing the set of documents into a plurality of splits of documents, each split comprising first, second, and third subsets of the documents in the split; constructing models using a parametric learning algorithm, the constructed models being capable of assigning a label to a document, the models being instantiated using the first subset of a first of the plurality of splits of documents, and parameters associated with the model being chosen by validating the model against the second subset of the first of the plurality of splits; repeating the constructing, instantiating, and validating steps for each of the second and subsequent splits in the plurality of splits; testing the validated models by applying them to the third subset of a respective split; and selecting a best validated model, wherein the best validated model is configured to assign labels to documents exclusive of the selected set of documents. 29. A computer containing a processor configured to create models according to claim 28 , wherein the set of documents and the labels are chosen using a plurality of different sources. | 0.646154 |
8,788,480 | 19 | 20 | 19. A system to halt execution of queries containing entity resolution (ER) candidate-building keys unsuitable for generating a restricted set of candidate entities against which to match a received identity record, the system comprising: one or more computer processors; a memory containing a program which, when executed by the one or more computer processors, is configured to perform an operation comprising: receiving an identity record; determining a plurality of ER candidate-building keys for the received identity record; generating a query from one or more of the plurality of ER candidate-building keys to retrieve entities matching any of the one or more ER candidate-building keys, wherein the one or more ER candidate-building keys are derived from at least a field of the received identity record; and upon determining, during execution of the query, that at least a first ER candidate-building key of the one or more ER candidate-building keys is unsuitable for generating a restricted set of candidate entities against which to match the received identity record, aborting executing the query, wherein the restricted set of candidate entities is selected from a plurality of available entities greater in number than the restricted set of candidate entities. | 19. A system to halt execution of queries containing entity resolution (ER) candidate-building keys unsuitable for generating a restricted set of candidate entities against which to match a received identity record, the system comprising: one or more computer processors; a memory containing a program which, when executed by the one or more computer processors, is configured to perform an operation comprising: receiving an identity record; determining a plurality of ER candidate-building keys for the received identity record; generating a query from one or more of the plurality of ER candidate-building keys to retrieve entities matching any of the one or more ER candidate-building keys, wherein the one or more ER candidate-building keys are derived from at least a field of the received identity record; and upon determining, during execution of the query, that at least a first ER candidate-building key of the one or more ER candidate-building keys is unsuitable for generating a restricted set of candidate entities against which to match the received identity record, aborting executing the query, wherein the restricted set of candidate entities is selected from a plurality of available entities greater in number than the restricted set of candidate entities. 20. The system of claim 19 , wherein the operation further comprises: removing the unsuitable ER candidate-building key from the query to produce a modified query. | 0.873053 |
9,928,060 | 6 | 7 | 6. The method of claim 5 , further comprising: receiving, by one or more computer processors, a third set of at least one change to the Javascript object notation structure, wherein the third set, the first set, and the second set include a change to a common component in the code; and adjusting, by one or more computer processors, the tags to the Javascript object notation structure to replace the first set of at least one change and the second set of at least one change that overlap with the third set of at least one change. | 6. The method of claim 5 , further comprising: receiving, by one or more computer processors, a third set of at least one change to the Javascript object notation structure, wherein the third set, the first set, and the second set include a change to a common component in the code; and adjusting, by one or more computer processors, the tags to the Javascript object notation structure to replace the first set of at least one change and the second set of at least one change that overlap with the third set of at least one change. 7. The method of claim 6 , further comprising: changing, by one or more computer processors, the Javascript object notation structure based upon the adjusted tags to the Javascript object notation structure to replace the first set of at least one change and the second set of at least one change that overlap with the third set of at least one change. | 0.849186 |
8,606,803 | 1 | 7 | 1. A method for translating a relational database query into a multidimensional expression language (MDX) database query comprising: parsing a relational database query into one or more relational database query tokens; filtering zero or more of the one or more relational database query tokens based at least in part on business logic to create a set of filtered relational database query tokens, the filtering comprising: removing a relational database query token, from the one or more relational database query tokens, responsive to determining that the relational database query token corresponds to a field not supported by a multidimensional database and is associated with a return of a dataset that exceeds a threshold; identifying relevant metadata, from a metadata store, associated with metadata associated with the set of filtered relational database query tokens, the relevant metadata comprising current multidimensional metadata and trend related multidimensional metadata; translating at least some relational database query tokens of the set of filtered relational database query tokens into one or more work item query language (WIQL) tokens; retrieving a first group of one or more MDX tokens based at least in part on the relevant metadata; retrieving a second group of one or more MDX tokens based at least in part on the one or more WIQL tokens; arranging at least some of the one or more MDX tokens of the first group and at least some of the one or more MDX tokens of the second group based at least in part on the metadata associated with the set of filtered relational database query tokens; and generating one or more MDX database queries for trend related information and current information based at least in part on at least some of the arranged MDX tokens, at least some of the parsing, the filtering, the identifying, the translating, the retrieving a first group, the retrieving a second group, the arranging, and the generating implemented at least in part via a processing unit. | 1. A method for translating a relational database query into a multidimensional expression language (MDX) database query comprising: parsing a relational database query into one or more relational database query tokens; filtering zero or more of the one or more relational database query tokens based at least in part on business logic to create a set of filtered relational database query tokens, the filtering comprising: removing a relational database query token, from the one or more relational database query tokens, responsive to determining that the relational database query token corresponds to a field not supported by a multidimensional database and is associated with a return of a dataset that exceeds a threshold; identifying relevant metadata, from a metadata store, associated with metadata associated with the set of filtered relational database query tokens, the relevant metadata comprising current multidimensional metadata and trend related multidimensional metadata; translating at least some relational database query tokens of the set of filtered relational database query tokens into one or more work item query language (WIQL) tokens; retrieving a first group of one or more MDX tokens based at least in part on the relevant metadata; retrieving a second group of one or more MDX tokens based at least in part on the one or more WIQL tokens; arranging at least some of the one or more MDX tokens of the first group and at least some of the one or more MDX tokens of the second group based at least in part on the metadata associated with the set of filtered relational database query tokens; and generating one or more MDX database queries for trend related information and current information based at least in part on at least some of the arranged MDX tokens, at least some of the parsing, the filtering, the identifying, the translating, the retrieving a first group, the retrieving a second group, the arranging, and the generating implemented at least in part via a processing unit. 7. The method of claim 1 , the metadata store comprising metadata associated with at least one of a filter operator, a filter criteria, a filter field, or a result field. | 0.745509 |
8,176,419 | 1 | 4 | 1. A computer-implemented method comprising: receiving a group of keywords, wherein each keyword includes one or more words; forming a word list from the group of keywords, where the word list includes a list of each word in the group of keywords; determining that a first word in the word list is a misspelling of a second word in the word list by: determining correct spelling candidate words in the word list; computing misspelling confidence scores for correcting the first word to the correct spelling candidate words; and in at least one instance, choosing, as the second word, an individual correct spelling candidate word having a misspelling confidence score that exceeds a misspelling confidence score threshold and that has a highest misspelling confidence score; correcting the first word by spelling the first word like the second word; and outputting corrected keywords that include the corrected first word. | 1. A computer-implemented method comprising: receiving a group of keywords, wherein each keyword includes one or more words; forming a word list from the group of keywords, where the word list includes a list of each word in the group of keywords; determining that a first word in the word list is a misspelling of a second word in the word list by: determining correct spelling candidate words in the word list; computing misspelling confidence scores for correcting the first word to the correct spelling candidate words; and in at least one instance, choosing, as the second word, an individual correct spelling candidate word having a misspelling confidence score that exceeds a misspelling confidence score threshold and that has a highest misspelling confidence score; correcting the first word by spelling the first word like the second word; and outputting corrected keywords that include the corrected first word. 4. One or more computer-readable storage devices storing computer-readable instructions that, when executed by a processing unit, cause the processing unit to perform the method of claim 1 . | 0.861516 |
8,201,095 | 2 | 3 | 2. The method of claim 1 wherein the thread comprises one or more existing posts, wherein the one or more thread keywords are automatically identified from the one or more existing posts. | 2. The method of claim 1 wherein the thread comprises one or more existing posts, wherein the one or more thread keywords are automatically identified from the one or more existing posts. 3. The method of claim 2 wherein the one or more thread keywords and the one or more relevancy scores are automatically identified based upon at least one of a keyword frequency and a keyword proximity to an original post. | 0.924438 |
9,400,786 | 19 | 21 | 19. The method according to claim 1 , wherein stylistic options are in said stored material segments. | 19. The method according to claim 1 , wherein stylistic options are in said stored material segments. 21. The method according to claim 19 , wherein said stylistic options comprise at least one of: clarity and conciseness, length of a sentence, a commonly misused word, unnecessary wording, and a combination of specific characters. | 0.934918 |
8,773,389 | 1 | 5 | 1. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: receiving a first indication that a touch-sensitive display has detected a first user input; selecting a first entry from supplemental works to output to the touch-sensitive display based at least in part on the first user input, the supplemental works comprising at least one of a dictionary, a thesaurus, an almanac, an atlas, an encyclopedia, a gazetteer, or a reference work; receiving a second indication that the touch-sensitive display has detected a second user input having an amount of force greater than a predetermined threshold; and selecting a second entry from the supplemental works to output to the touch-sensitive display based at least in part on the amount of force of the second user input. | 1. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: receiving a first indication that a touch-sensitive display has detected a first user input; selecting a first entry from supplemental works to output to the touch-sensitive display based at least in part on the first user input, the supplemental works comprising at least one of a dictionary, a thesaurus, an almanac, an atlas, an encyclopedia, a gazetteer, or a reference work; receiving a second indication that the touch-sensitive display has detected a second user input having an amount of force greater than a predetermined threshold; and selecting a second entry from the supplemental works to output to the touch-sensitive display based at least in part on the amount of force of the second user input. 5. One or more non-transitory computer-readable media as recited in claim 1 , wherein: the touch-sensitive display forms a portion of an electronic book reader device; and the first user input or the second user input selects a word that is included in an electronic book rendered by the electronic book reader device. | 0.645089 |
8,554,789 | 10 | 12 | 10. A volatile or non-volatile computer-readable medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform a database server registering a XML schema, wherein registering the XML schema includes: traversing a declaration of a first element that comprises a second element; while traversing said declaration of said first element: tracking on a stack a declaration of an element or a type encountered during said traversing; encountering said second element; and determining that said second element belongs to a type within a hierarchy of inheritance of a certain type of said first element by at least determining that said first element is on the stack; and in response to determining that said second element belongs to a type within a hierarchy of inheritance of a certain type of the first element, performing: determining that said XML schema defines a cyclic construct; determining a database representation capable of storing instances of said XML schema that contain said cyclic construct; and generating a mapping between constructs of said XML schema and said database representation. | 10. A volatile or non-volatile computer-readable medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform a database server registering a XML schema, wherein registering the XML schema includes: traversing a declaration of a first element that comprises a second element; while traversing said declaration of said first element: tracking on a stack a declaration of an element or a type encountered during said traversing; encountering said second element; and determining that said second element belongs to a type within a hierarchy of inheritance of a certain type of said first element by at least determining that said first element is on the stack; and in response to determining that said second element belongs to a type within a hierarchy of inheritance of a certain type of the first element, performing: determining that said XML schema defines a cyclic construct; determining a database representation capable of storing instances of said XML schema that contain said cyclic construct; and generating a mapping between constructs of said XML schema and said database representation. 12. The medium of claim 10 , wherein: determining that said XML schema defines a cyclic construct includes detecting that an ascendant element and a descendant element that descends from the ascendant element are involved in said cyclic construct; the database representation includes an out-of-line table for storing said ascendant element; and generating a mapping includes generating a mapping that maps said ascendant element to said out-of-line table. | 0.501094 |
9,697,830 | 14 | 15 | 14. The computer program product according to claim 1 , wherein the index comprises a plurality of indexes that are simultaneously searched. | 14. The computer program product according to claim 1 , wherein the index comprises a plurality of indexes that are simultaneously searched. 15. The computer program product according to claim 14 , wherein the plurality of indexes comprise at least two of a word-based index, a word-based index with no language model scores, and a morph-based index. | 0.928179 |
8,812,320 | 9 | 11 | 9. 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: receiving a request for a verification phrase for verifying an identity of a user; in response to receiving the request for the verification phrase for verifying the identity of the user, identifying subwords to be included in the verification phrase; in response to identifying the subwords to be included in the verification phrase, obtaining a candidate phrase that includes at least some of the identified subwords as the verification phrase; and providing the verification phrase as a response to the request for the verification phrase for verifying the identity of the user. | 9. 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: receiving a request for a verification phrase for verifying an identity of a user; in response to receiving the request for the verification phrase for verifying the identity of the user, identifying subwords to be included in the verification phrase; in response to identifying the subwords to be included in the verification phrase, obtaining a candidate phrase that includes at least some of the identified subwords as the verification phrase; and providing the verification phrase as a response to the request for the verification phrase for verifying the identity of the user. 11. The system of claim 9 , wherein obtaining a candidate phrase that includes at least some of the identified subwords as the verification phrase comprises: determining that a particular identified subword is particularly sound discriminative; and in response to determining that the particular identified subword is particularly sound discriminative, obtaining a candidate phrase that includes the particular identified subword that is determined to be particularly sound discriminative. | 0.615566 |
9,317,500 | 15 | 21 | 15. A computer-implemented method for synchronizing output of translated content corresponding to a translation of a base content during consumption of the base content, the computer-implemented method comprising: causing output of the base content; monitoring a current position of consumption of the base content based at least in part on at least one input device, wherein the current position of consumption of the base content changes during consumption of the base content; determining that content synchronization information associated with the base content and the translated content identifies a position within the base content that corresponds to the current position of consumption of the base content, wherein the content synchronization information identifies one or more positions within the base content and, a position within the translated content that corresponds to each of the one or more positions within the base content; and causing synchronization of output of the base content and output of the translated content from an output position of the translated content that is synchronized to the current position of consumption of the base content based at least in part on the content synchronization information. | 15. A computer-implemented method for synchronizing output of translated content corresponding to a translation of a base content during consumption of the base content, the computer-implemented method comprising: causing output of the base content; monitoring a current position of consumption of the base content based at least in part on at least one input device, wherein the current position of consumption of the base content changes during consumption of the base content; determining that content synchronization information associated with the base content and the translated content identifies a position within the base content that corresponds to the current position of consumption of the base content, wherein the content synchronization information identifies one or more positions within the base content and, a position within the translated content that corresponds to each of the one or more positions within the base content; and causing synchronization of output of the base content and output of the translated content from an output position of the translated content that is synchronized to the current position of consumption of the base content based at least in part on the content synchronization information. 21. The computer-implemented method of claim 15 , wherein output of the base content and output of the translated content are performed by different computing devices. | 0.956076 |
8,515,959 | 1 | 7 | 1. A method for storing a document in a file system, comprising the steps of: determining a term weight for terms appearing in said document, wherein a given term weight is based on a frequency of occurrence of said corresponding term in a reference corpus: and storing said document in said file system with an indication of said term weights, wherein said given term weight is obtained by dividing a fractional frequency of said term in said document by a fractional frequency of said term in said reference corpus, wherein said fractional frequency of said term in said document is the number of occurrences of the term in the document divided by the total number of terms in the document and wherein said fractional frequency of said term in said reference corpus is the number of occurrences of the term in the reference corsus divided by the total number of words in the reference corpus. | 1. A method for storing a document in a file system, comprising the steps of: determining a term weight for terms appearing in said document, wherein a given term weight is based on a frequency of occurrence of said corresponding term in a reference corpus: and storing said document in said file system with an indication of said term weights, wherein said given term weight is obtained by dividing a fractional frequency of said term in said document by a fractional frequency of said term in said reference corpus, wherein said fractional frequency of said term in said document is the number of occurrences of the term in the document divided by the total number of terms in the document and wherein said fractional frequency of said term in said reference corpus is the number of occurrences of the term in the reference corsus divided by the total number of words in the reference corpus. 7. The method of claim 1 , wherein said term weights are stored in an array. | 0.907767 |
7,818,665 | 5 | 6 | 5. The method of claim 3 , further comprising: determining a suitability of the second transform based on the comparison of the second markup language document to the third markup language document. | 5. The method of claim 3 , further comprising: determining a suitability of the second transform based on the comparison of the second markup language document to the third markup language document. 6. The method of claim 5 , wherein determining the suitability of the first transform and determining the suitability of the second transform comprise: determining the first transform and second transform as suitable in response to the comparison identifying no discrepancies between the second markup language document and the third markup language document; and determining the first transform and second transform as unsuitable in response to the comparison identifying at least one discrepancy between the second markup language document and the third markup language document. | 0.821888 |
9,473,637 | 14 | 15 | 14. The call center device of claim 6 wherein the training device is configured to assign to the word lattices τ the conditional probabilities p(τ|DA type) by operations that for each word lattice τ include: sampling the word lattice τ to generate sample utterances; labeling each sample utterance with conditional probabilities p(DA type|utt) where utt is the sample utterance and DA type is a dialog act type; and generating the conditional probabilities p(τ|DA type) for the word lattice τ from the conditional probabilities p(DA type|utt) of the sample utterances. | 14. The call center device of claim 6 wherein the training device is configured to assign to the word lattices τ the conditional probabilities p(τ|DA type) by operations that for each word lattice τ include: sampling the word lattice τ to generate sample utterances; labeling each sample utterance with conditional probabilities p(DA type|utt) where utt is the sample utterance and DA type is a dialog act type; and generating the conditional probabilities p(τ|DA type) for the word lattice τ from the conditional probabilities p(DA type|utt) of the sample utterances. 15. The call center device of claim 14 wherein the conditional probabilities p(τ|DA type) for the word lattice τ are generated from the conditional probabilities p(DA type|utt) of the sample utterances using Baye's rule. | 0.910131 |
9,043,423 | 47 | 48 | 47. The method of claim 42 , comprising receiving the information interactively. | 47. The method of claim 42 , comprising receiving the information interactively. 48. The method of claim 47 , comprising receiving the information by an interrogation avatar. | 0.969528 |
7,634,546 | 47 | 48 | 47. A method according to claim 46 wherein said current database hierarchy comprises: a top-level hierarchy having at least one top-level subject; at least one mid-level hierarchy, each of said at least one mid-level hierarchy having at least one mid-level subject related to at least one of said at least one top-level subject; and a low-level hierarchy having at least one low-level subject related to at least one of said at least one mid-level subject, wherein said response input becomes an item indexed to at least one of said at least one low-level subject. | 47. A method according to claim 46 wherein said current database hierarchy comprises: a top-level hierarchy having at least one top-level subject; at least one mid-level hierarchy, each of said at least one mid-level hierarchy having at least one mid-level subject related to at least one of said at least one top-level subject; and a low-level hierarchy having at least one low-level subject related to at least one of said at least one mid-level subject, wherein said response input becomes an item indexed to at least one of said at least one low-level subject. 48. A method according to claim 47 wherein said current database hierarchy further comprises: at least one top-level leader assigned to each of said at least one top-level subject; at least one mid-level leader assigned to each of said at least one mid-level subject; and at least one low-level leader assigned to each of said at least one low-level subject. | 0.959114 |
6,064,961 | 9 | 14 | 9. The method of claim 1, wherein said initial text and said further text are contextual phrases including a target word and words immediately preceding and following said target word. | 9. The method of claim 1, wherein said initial text and said further text are contextual phrases including a target word and words immediately preceding and following said target word. 14. The method of claim 9, further comprising the step of inversely displaying said target word. | 0.944056 |
9,305,553 | 16 | 18 | 16. The computer system of claim 15 wherein the speech recognition engine generation module is further adapted to: (a) create a first speech recognition engine based on a first one of the speech corpuses; and (b) apply the first speech recognition engine to produce a recognized version of a second one of the speech corpuses, and wherein the comparison module is further adapted to calculate the distance as a first edit distance between the recognized version of the second one of the speech corpuses and the transcription of the second one of the speech corpuses. | 16. The computer system of claim 15 wherein the speech recognition engine generation module is further adapted to: (a) create a first speech recognition engine based on a first one of the speech corpuses; and (b) apply the first speech recognition engine to produce a recognized version of a second one of the speech corpuses, and wherein the comparison module is further adapted to calculate the distance as a first edit distance between the recognized version of the second one of the speech corpuses and the transcription of the second one of the speech corpuses. 18. The computer system of claim 16 wherein the speech recognition engine generation module is further adapted to: (c) create a second speech recognition engine based on the second one of the speech corpuses; and (d) apply the second speech recognition engine to produce a recognized version of the first speech corpus, and wherein the comparison module is further adapted to calculate a second edit distance between the recognized version of the first speech corpus and the transcription of the first one of the speech corpuses. | 0.808333 |
9,092,523 | 22 | 30 | 22. A system comprising: a) a Web server computer configured to present web page search results related to terms of a search query initiated by a user, wherein the web page search results include a results list comprising a list of web pages related to the terms of the search query, the order in which the web pages are presented in response to the search query being influenced by relevance feedback provided by multiple users prior to the search query, and wherein the relevance feedback is different from selection of a link to a web page in the results list; b) a search engine for querying a database and providing the web page search results in response to user queries; c) a content manager for managing the supplemental information in response to user input, wherein the user input comprises the relevance feedback; and d) a first data store coupled to the content manager for storing supplemental information related to the search query, wherein the web page search results include the supplemental information, and multiple users are able to modify the same portions of the supplemental information, wherein after the second user modifies the supplemental information previously provided by a first user, any user, including the first user, is able to at least one of further modify the supplemental information or revert the modification of the second user. | 22. A system comprising: a) a Web server computer configured to present web page search results related to terms of a search query initiated by a user, wherein the web page search results include a results list comprising a list of web pages related to the terms of the search query, the order in which the web pages are presented in response to the search query being influenced by relevance feedback provided by multiple users prior to the search query, and wherein the relevance feedback is different from selection of a link to a web page in the results list; b) a search engine for querying a database and providing the web page search results in response to user queries; c) a content manager for managing the supplemental information in response to user input, wherein the user input comprises the relevance feedback; and d) a first data store coupled to the content manager for storing supplemental information related to the search query, wherein the web page search results include the supplemental information, and multiple users are able to modify the same portions of the supplemental information, wherein after the second user modifies the supplemental information previously provided by a first user, any user, including the first user, is able to at least one of further modify the supplemental information or revert the modification of the second user. 30. The system of claim 22 , wherein the order in which the web pages are to be initially presented in the results list in response to the search query initiated by the user is influenced by relevance feedback received in a context other than a previous search query. | 0.733533 |
9,552,349 | 3 | 4 | 3. The method of claim 2 , wherein said distance one variation comprises a replacement operation to generate a replacement hash table having entries of single character wild card replacements of said entries in said dictionary and said method further comprises the steps of generating single character replacements and insertions of said candidate word and comparing said single character replacements and insertions against said replacement hash table. | 3. The method of claim 2 , wherein said distance one variation comprises a replacement operation to generate a replacement hash table having entries of single character wild card replacements of said entries in said dictionary and said method further comprises the steps of generating single character replacements and insertions of said candidate word and comparing said single character replacements and insertions against said replacement hash table. 4. The method of claim 3 , wherein the replacement hash table is obtained by: generating variants of each word in the dictionary, each variant is comprised of replacing any one character in the word with a wild card character and leaving other characters unchanged, thereby generating W variants for each word of length W; and for each generated variant of a word in the dictionary, storing a key-value pair in a hash table, wherein a key is a generated variant having a value that is the word itself. | 0.882889 |
8,069,137 | 1 | 5 | 1. A method for implementing intelligent agent services, comprising: generating an ontological domain for an individual based upon information elements, wherein a set of information elements represents a behavior of the individual at a point in time, the generating including creating subdomains of contextually organized collections of a plurality of sets of the information elements, the subdomains including any orthogonally related data identified among a plurality of behaviors; determining relevance of relationships among the plurality of sets of the information elements in the ontological domain, the relevance determined based upon measurable aspects, wherein a relationship determined to be relevant is identified as an interest of the individual; identifying sources of information topically related to the interest; searching the sources of information using the plurality of sets of the information elements having the relationship determined to be relevant to identify a solution for satisfying the interest; and detecting the behavior of the individual, gathering the information elements from a portion of the sources in response to the detecting; wherein detectable behaviors represent behavioral indicators that occur within a physical and virtual geography and in relation to time, the detectable behaviors including a transaction, a presence of the individual at a location, a presence of the individual at a function, and a computer query; wherein the presence of the individual at a function is determined by analyzing a combination of activities conducted by the individual at the sources. | 1. A method for implementing intelligent agent services, comprising: generating an ontological domain for an individual based upon information elements, wherein a set of information elements represents a behavior of the individual at a point in time, the generating including creating subdomains of contextually organized collections of a plurality of sets of the information elements, the subdomains including any orthogonally related data identified among a plurality of behaviors; determining relevance of relationships among the plurality of sets of the information elements in the ontological domain, the relevance determined based upon measurable aspects, wherein a relationship determined to be relevant is identified as an interest of the individual; identifying sources of information topically related to the interest; searching the sources of information using the plurality of sets of the information elements having the relationship determined to be relevant to identify a solution for satisfying the interest; and detecting the behavior of the individual, gathering the information elements from a portion of the sources in response to the detecting; wherein detectable behaviors represent behavioral indicators that occur within a physical and virtual geography and in relation to time, the detectable behaviors including a transaction, a presence of the individual at a location, a presence of the individual at a function, and a computer query; wherein the presence of the individual at a function is determined by analyzing a combination of activities conducted by the individual at the sources. 5. The method of claim 1 , further comprising: storing each of the plurality of sets of information elements in a corresponding record using a standard data structure having corresponding data fields, the record including a unique identifier; and storing records produced for each of the plurality of sets of the information elements in a database; wherein creating subdomains that include orthogonally related data includes identifying matching information elements from data fields across multiple records in the database via corresponding unique identifiers. | 0.642219 |
10,025,855 | 12 | 13 | 12. An article comprising: a non-transitory storage medium storing computer instructions, wherein the computer instructions are executable by at least one processor of at least one local computing device to: store in at least one physical memory of the at least one local computing device any results to be generated from the execution of the computer instructions; process one or more digital signals to be received from one or more first remote user computing platforms via a communication network, the one or more digital signals comprise identities of a plurality of federated search sources and one or more user-submitted index keywords to indicate content of the plurality of federated search sources, the plurality of federated search sources comprising at least one search source which is uncrawled and not publically available, the plurality of federated search sources further comprises at least one first federated search source and at least one second federated search source, individual ones of the plurality of federated search sources comprise links to multiple different specified sources of electronic digital signal quantities; index at least one of the plurality of federated search sources to determine index criteria and to determine at least one federated search source of the at least one first federated search source and the at least one second federated search source to be related to individual index keywords that comprise at least the one or more user-submitted index keywords, wherein the index is to be based at least in part on a match of domains of an indexed federated search to domains of a search engine to return results to be based at least in part on a category path, wherein the category path of the indexed federated search results is to be matched against a category path to be associated with a crawler-based search, and wherein the index further comprises: retrieve, by a server computer, one or more digital signals comprising the electronic digital signal quantities from sites associated with a federated search; extract, by the server computer, weighing factors from the one or more digital signals including at least keywords and domains; and create, by the server computer, a table of a plurality of signatures based at least in part on the weighing factors; store the index criteria in a database of the at least one physical memory; process a query received via the communication network from a second remote user computing platform after performing the indexing; execute a web searching protocol to search at least one of the plurality of federated search sources; determine one or more signatures of the plurality of signatures associated with one or more of the plurality of federated search sources to be based, at least in part, on the index criteria; match the query with the determined one or more signatures to be based, at least in part, on the index criteria to determine and rank one or more of the plurality of federated search sources for the query in accordance with a usefulness metric; and at least partially in response to a user selection of one or more of the ranked one or more of the plurality of federated search sources, perform a federated search, and transmit electrical signals via the communication network to the second remote user computing platform, the electrical signals comprising results including respective links to the one or more ranked federated search sources for the query and at least one displayable graphical indicator of the usefulness metric for individual ones of the one or more ranked federated search sources. | 12. An article comprising: a non-transitory storage medium storing computer instructions, wherein the computer instructions are executable by at least one processor of at least one local computing device to: store in at least one physical memory of the at least one local computing device any results to be generated from the execution of the computer instructions; process one or more digital signals to be received from one or more first remote user computing platforms via a communication network, the one or more digital signals comprise identities of a plurality of federated search sources and one or more user-submitted index keywords to indicate content of the plurality of federated search sources, the plurality of federated search sources comprising at least one search source which is uncrawled and not publically available, the plurality of federated search sources further comprises at least one first federated search source and at least one second federated search source, individual ones of the plurality of federated search sources comprise links to multiple different specified sources of electronic digital signal quantities; index at least one of the plurality of federated search sources to determine index criteria and to determine at least one federated search source of the at least one first federated search source and the at least one second federated search source to be related to individual index keywords that comprise at least the one or more user-submitted index keywords, wherein the index is to be based at least in part on a match of domains of an indexed federated search to domains of a search engine to return results to be based at least in part on a category path, wherein the category path of the indexed federated search results is to be matched against a category path to be associated with a crawler-based search, and wherein the index further comprises: retrieve, by a server computer, one or more digital signals comprising the electronic digital signal quantities from sites associated with a federated search; extract, by the server computer, weighing factors from the one or more digital signals including at least keywords and domains; and create, by the server computer, a table of a plurality of signatures based at least in part on the weighing factors; store the index criteria in a database of the at least one physical memory; process a query received via the communication network from a second remote user computing platform after performing the indexing; execute a web searching protocol to search at least one of the plurality of federated search sources; determine one or more signatures of the plurality of signatures associated with one or more of the plurality of federated search sources to be based, at least in part, on the index criteria; match the query with the determined one or more signatures to be based, at least in part, on the index criteria to determine and rank one or more of the plurality of federated search sources for the query in accordance with a usefulness metric; and at least partially in response to a user selection of one or more of the ranked one or more of the plurality of federated search sources, perform a federated search, and transmit electrical signals via the communication network to the second remote user computing platform, the electrical signals comprising results including respective links to the one or more ranked federated search sources for the query and at least one displayable graphical indicator of the usefulness metric for individual ones of the one or more ranked federated search sources. 13. The article of claim 12 , wherein the instructions are further executable by the one or more processors to: determine a signature to be associated with an indexed federated search source, compare a query to the indexed federated search source, and determine a closer match between the query and the indexed federated search source, wherein the determine a closer match comprises a determination of the closer match between the query and the signature to be associated with the indexed federated search source. | 0.603555 |
8,666,757 | 5 | 17 | 5. The computer-implemented method according to claim 2 , wherein the hierarchical coded payment system includes a plurality of classification levels defining a payment determined, the plurality of classification levels comprising: a primary level including a set of driving elements used to encode the service provider activity at a transactional level; an intermediary level including a set of groups, each group mapping one or more driving elements to a particular payment rate; and an aggregate level including a set of categories, each category being mapped to one or more of the groups according to predetermined industry classification schemes. | 5. The computer-implemented method according to claim 2 , wherein the hierarchical coded payment system includes a plurality of classification levels defining a payment determined, the plurality of classification levels comprising: a primary level including a set of driving elements used to encode the service provider activity at a transactional level; an intermediary level including a set of groups, each group mapping one or more driving elements to a particular payment rate; and an aggregate level including a set of categories, each category being mapped to one or more of the groups according to predetermined industry classification schemes. 17. The computer-implemented method according to claim 5 , wherein calculating summary variables from the data comprises: capturing, by at least one data processor, behavioral characteristics within the facility into a profile; and deriving, by at least one data processor, the summary variables from the profile. | 0.930629 |
8,978,140 | 5 | 6 | 5. The computer-implemented method of claim 1 , further comprising: providing the first URL to a data mining module, the data mining module in communication with a plurality of collection sources, the plurality of collection sources implementing the plurality of collection methods, and comprising asynchronous processes. | 5. The computer-implemented method of claim 1 , further comprising: providing the first URL to a data mining module, the data mining module in communication with a plurality of collection sources, the plurality of collection sources implementing the plurality of collection methods, and comprising asynchronous processes. 6. The computer-implemented method of claim 5 , further comprising configuring the data mining module, wherein configuring the data mining module includes defining a characteristic indicative of a targeted attribute, and configuring the data mining module to identify requests having the attribute. | 0.93187 |
7,590,936 | 1 | 11 | 1. A computer-implemented method for displaying one or more tagged data items proximate to a result of a search of an electronic document, comprising the steps of: locating one or more of the search results generated by the search of the electronic document; identifying each of the tagged data items present in the electronic document within a distance from each search result using a proximity rule, wherein identifying each of the tagged data items comprises: calculating the distance between each search result and each tagged data item; and determining if the calculated distance is less than a distance criterion, wherein the distance criterion is a predetermined number of lines of text; identifying applicable tagged data items by determining whether the each of the tagged data items present in the electronic document should be associated with the one or more search results using grammatical semantic intelligence, the grammatical semantic intelligence comprising a rule that tagged data items that satisfy the proximity rule, with respect to the one or more search results, represent facts about search terms used in generating the search of the electronic document only when the search terms are proper nouns; displaying on a user interface the one or more tagged items associated with each search result and identified as within the distance from each search result; and removing a tag from a displayed item associated with the one or more search results by specifying in the user interface that the item should not be categorized, wherein the user interface comprises an on-object-user interface which receives a pointing action from a computer pointing device for pointing at the displayed item, the pointing action causing the generation of a menu for removing the tag in the on-object user interface. | 1. A computer-implemented method for displaying one or more tagged data items proximate to a result of a search of an electronic document, comprising the steps of: locating one or more of the search results generated by the search of the electronic document; identifying each of the tagged data items present in the electronic document within a distance from each search result using a proximity rule, wherein identifying each of the tagged data items comprises: calculating the distance between each search result and each tagged data item; and determining if the calculated distance is less than a distance criterion, wherein the distance criterion is a predetermined number of lines of text; identifying applicable tagged data items by determining whether the each of the tagged data items present in the electronic document should be associated with the one or more search results using grammatical semantic intelligence, the grammatical semantic intelligence comprising a rule that tagged data items that satisfy the proximity rule, with respect to the one or more search results, represent facts about search terms used in generating the search of the electronic document only when the search terms are proper nouns; displaying on a user interface the one or more tagged items associated with each search result and identified as within the distance from each search result; and removing a tag from a displayed item associated with the one or more search results by specifying in the user interface that the item should not be categorized, wherein the user interface comprises an on-object-user interface which receives a pointing action from a computer pointing device for pointing at the displayed item, the pointing action causing the generation of a menu for removing the tag in the on-object user interface. 11. The method of claim 1 wherein the distance from each search result comprises a distance based on grammatical rules of a language comprising the electronic document. | 0.854922 |
8,202,094 | 1 | 12 | 1. A virtual learning system comprising: an image library included in a first database that is communicatively coupled to a computer, wherein the image library includes stored images of objects; an electronic dictionary included in the first database or in another database communicatively coupled to the computer, wherein the electronic dictionary includes information relating to stored phonetic sounds of words that identify the stored images of objects in the image library and information relating to alphanumeric characters of an alphabet that spell words associated with the stored images of objects in the image library; and a voice recognition unit communicatively coupled to the computer, wherein the voice recognition unit is configured to: receive a training command to associate future inputs of an utterance with a word that identifies an object, wherein the utterance is different from a pronunciation of the word that identifies the object, receive a sound pattern input of the utterance from a user, associate the utterance with the word that identifies the object according to the training command, and provide a digital recognition output corresponding to the sound pattern input; wherein the computer is configured to scan the database to find an entry matching the digital recognition output, and, when a matching entry is found, to present on a display alphanumeric characters representing a word or a sound from the electronic dictionary that corresponds to the digital recognition output and an image from the stored images of objects in the image library that is associated with the word or the sound presented on the display, wherein the image presented on the display corresponds to a graphical representation of an object identified by the word or the sound presented on the display. | 1. A virtual learning system comprising: an image library included in a first database that is communicatively coupled to a computer, wherein the image library includes stored images of objects; an electronic dictionary included in the first database or in another database communicatively coupled to the computer, wherein the electronic dictionary includes information relating to stored phonetic sounds of words that identify the stored images of objects in the image library and information relating to alphanumeric characters of an alphabet that spell words associated with the stored images of objects in the image library; and a voice recognition unit communicatively coupled to the computer, wherein the voice recognition unit is configured to: receive a training command to associate future inputs of an utterance with a word that identifies an object, wherein the utterance is different from a pronunciation of the word that identifies the object, receive a sound pattern input of the utterance from a user, associate the utterance with the word that identifies the object according to the training command, and provide a digital recognition output corresponding to the sound pattern input; wherein the computer is configured to scan the database to find an entry matching the digital recognition output, and, when a matching entry is found, to present on a display alphanumeric characters representing a word or a sound from the electronic dictionary that corresponds to the digital recognition output and an image from the stored images of objects in the image library that is associated with the word or the sound presented on the display, wherein the image presented on the display corresponds to a graphical representation of an object identified by the word or the sound presented on the display. 12. The virtual learning system of claim 1 , wherein the computer is further configured to create a profile for a user, wherein the profile is associated with a particular instruction set that corresponds to the user. | 0.774896 |
9,666,180 | 1 | 3 | 1. A method performed by a near end communication device, the method comprising: establishing an audio connection between the near-end communication device and a far-end communication device via a communication network; detecting a noise level in an audio input to the near-end communication device; providing an option to activate text-to-speech conversion on a display screen of the near-end communications device based at least in part on the noise level; activating text-to-speech conversion at the near-end communication device in response to the option to activate text-to-speech conversion being selected; prompting for text input based at least in part on the activating; receiving text input at the near-end communication device based at least in part on the prompting; converting the text input into speech signals at the near-end communication device; and transmitting the speech signals to the far-end communication device using the audio connection, wherein the transmitting is performed while muting the audio input to the communication device, and the muting is based at least in part on the activating. | 1. A method performed by a near end communication device, the method comprising: establishing an audio connection between the near-end communication device and a far-end communication device via a communication network; detecting a noise level in an audio input to the near-end communication device; providing an option to activate text-to-speech conversion on a display screen of the near-end communications device based at least in part on the noise level; activating text-to-speech conversion at the near-end communication device in response to the option to activate text-to-speech conversion being selected; prompting for text input based at least in part on the activating; receiving text input at the near-end communication device based at least in part on the prompting; converting the text input into speech signals at the near-end communication device; and transmitting the speech signals to the far-end communication device using the audio connection, wherein the transmitting is performed while muting the audio input to the communication device, and the muting is based at least in part on the activating. 3. The method of claim 1 , further comprising: detecting the noise level as below a threshold value after the text-to-speech conversion is activated; and deactivating the text-to-speech conversion based at least in part on the noise level being below the threshold value. | 0.657828 |
8,768,910 | 16 | 19 | 16. A system comprising: a memory to store a keyword list associated with a category of media items; and one or more processors to: obtain a search query, identify candidate queries for the search query, determine whether the candidate queries match words in the keyword list, determine a first ratio based on a first quantity of times that the search query is submitted to a web search engine interface, determine a second ratio based on a second quantity of times that the search query is submitted to a specialized search engine interface that is used to search for information associated with the category or to search for information associated with news, identify, based on the first ratio and the second ratio, the search query as a media query associated with the category when the candidate queries match one or more of the words in the keyword list, and provide, based on identifying the search query as the media query, a result document based on the media query. | 16. A system comprising: a memory to store a keyword list associated with a category of media items; and one or more processors to: obtain a search query, identify candidate queries for the search query, determine whether the candidate queries match words in the keyword list, determine a first ratio based on a first quantity of times that the search query is submitted to a web search engine interface, determine a second ratio based on a second quantity of times that the search query is submitted to a specialized search engine interface that is used to search for information associated with the category or to search for information associated with news, identify, based on the first ratio and the second ratio, the search query as a media query associated with the category when the candidate queries match one or more of the words in the keyword list, and provide, based on identifying the search query as the media query, a result document based on the media query. 19. The system of claim 16 , where, when identifying the search query as the media query, the one or more processors are further to: identify product search results based on the search query and a products search index that includes information regarding documents associated with products, determine the category based on a set of results of the search results, determine whether the category matches one of the candidate queries, and identify, based on the first ratio and the second ratio, the search query as the media query when the candidate queries match the words in the keyword list and the category matches the one of the candidate queries. | 0.729167 |
5,583,989 | 5 | 9 | 5. A vehicle control system using an object program for a vehicle automatic transmission based on operating conditions of a vehicle, comprising: a microcomputer mounted in the vehicle; source program generating means for generating a source program, while determining control parameters and a control algorithm through simulation on a mainframe computer; detection means, operably connected to said source program generating means, for detecting expressions containing at least a quantization factor with floating-point arithmetic included in the source program; conversion means, operably connected to said detection means, for converting the expressions detected by the detection means into a microcode, which is loaded into a microcomputer of the vehicle, containing at least a quantization factor without floating-point arithmetic using a prescribed method of notation; arithmetic means, operably connected to said conversion means, for multiplying the variables of the microcode containing at least a quantization factor without floating-point arithmetic converted by the conversion means by prescribed values obtained from the expressions containing at least a quantization factor with floating-point arithmetic to convert into the object program including the microcode; state transformation means, operably connected to said arithmetic means, for reducing the microcode containing at least a quantization factor without floating-point arithmetic containing variables multiplied by the arithmetic means; and loading means for loading the object program including the reduced microcode on the microcomputer, wherein said microcomputer determines a gear shift scheduling by using the object program in response to the operating conditions of the vehicle. | 5. A vehicle control system using an object program for a vehicle automatic transmission based on operating conditions of a vehicle, comprising: a microcomputer mounted in the vehicle; source program generating means for generating a source program, while determining control parameters and a control algorithm through simulation on a mainframe computer; detection means, operably connected to said source program generating means, for detecting expressions containing at least a quantization factor with floating-point arithmetic included in the source program; conversion means, operably connected to said detection means, for converting the expressions detected by the detection means into a microcode, which is loaded into a microcomputer of the vehicle, containing at least a quantization factor without floating-point arithmetic using a prescribed method of notation; arithmetic means, operably connected to said conversion means, for multiplying the variables of the microcode containing at least a quantization factor without floating-point arithmetic converted by the conversion means by prescribed values obtained from the expressions containing at least a quantization factor with floating-point arithmetic to convert into the object program including the microcode; state transformation means, operably connected to said arithmetic means, for reducing the microcode containing at least a quantization factor without floating-point arithmetic containing variables multiplied by the arithmetic means; and loading means for loading the object program including the reduced microcode on the microcomputer, wherein said microcomputer determines a gear shift scheduling by using the object program in response to the operating conditions of the vehicle. 9. The vehicle control system according to claim 5, further comprising memory means for storing said generated source program and control means for controlling a system using said memory means. | 0.502577 |
9,501,459 | 7 | 12 | 7. A system for detecting an influence caused by changing a source code of an application from which a document object model (DOM) tree and cascading style sheets (CSSs) are extracted, the system comprising: a memory; and one or more processors, communicatively coupled to the memory, the one or more processors configured to: save one or more input operations of a user of the application, a DOM tree, and a CSS for each of one or more times that an instruction is received to check a screen state; emulate, after the source code is changed, the one or more input operations in an operation order, for each of the one or more times; acquire a DOM tree and CSS for each of the one or more times; compare the saved DOM tree and CSS with the acquired DOM tree and CSS for each of the one or more times; and output a result of the comparison. | 7. A system for detecting an influence caused by changing a source code of an application from which a document object model (DOM) tree and cascading style sheets (CSSs) are extracted, the system comprising: a memory; and one or more processors, communicatively coupled to the memory, the one or more processors configured to: save one or more input operations of a user of the application, a DOM tree, and a CSS for each of one or more times that an instruction is received to check a screen state; emulate, after the source code is changed, the one or more input operations in an operation order, for each of the one or more times; acquire a DOM tree and CSS for each of the one or more times; compare the saved DOM tree and CSS with the acquired DOM tree and CSS for each of the one or more times; and output a result of the comparison. 12. The system of claim 7 , wherein the output comprises outputting a portion that differs, at a single time, between two or more graphical user interfaces of the application. | 0.905508 |
9,607,612 | 13 | 15 | 13. One or more non-transitory machine readable storage media comprising a plurality of instructions that in response to being executed cause a computing device to: capture audio input using an audio sensor of the computing device; distort a waveform of the audio input to produce a plurality of distorted audio variations, wherein to distort the waveform comprises to adjust a temporal duration of the waveform; perform speech recognition on the audio input and each of the distorted audio variations to produce a plurality of speech recognition results; and select a result from the speech recognition results based on contextual information. | 13. One or more non-transitory machine readable storage media comprising a plurality of instructions that in response to being executed cause a computing device to: capture audio input using an audio sensor of the computing device; distort a waveform of the audio input to produce a plurality of distorted audio variations, wherein to distort the waveform comprises to adjust a temporal duration of the waveform; perform speech recognition on the audio input and each of the distorted audio variations to produce a plurality of speech recognition results; and select a result from the speech recognition results based on contextual information. 15. The non-transitory machine readable media of claim 13 , wherein to adjust the temporal duration of the waveform comprises to insert a pause at a phonetic split point of the audio input identified by performing speech recognition on the audio input. | 0.7375 |
8,266,184 | 4 | 5 | 4. A computer hardware apparatus for generating a context model for generating a Service-Oriented Architecture (SOA) policy, comprising: at least one processor; a collector configured to collect SOA metadata documents compliant with an application scope of the SOA policy; an inter-document reference establishing module configured to establish inter-document references among the collected SOA metadata documents; and an aggregator configured to aggregate the collected SOA metadata documents according to the inter-document references to generate a context model, wherein the inter-document reference establishing module includes a correspondence establishing unit configured to establish a unique correspondence between a Uniform Resource Identifier of each of the collected SOA metadata documents and a role taken by the collected SOA metadata document. | 4. A computer hardware apparatus for generating a context model for generating a Service-Oriented Architecture (SOA) policy, comprising: at least one processor; a collector configured to collect SOA metadata documents compliant with an application scope of the SOA policy; an inter-document reference establishing module configured to establish inter-document references among the collected SOA metadata documents; and an aggregator configured to aggregate the collected SOA metadata documents according to the inter-document references to generate a context model, wherein the inter-document reference establishing module includes a correspondence establishing unit configured to establish a unique correspondence between a Uniform Resource Identifier of each of the collected SOA metadata documents and a role taken by the collected SOA metadata document. 5. The computer hardware apparatus according to claim 4 , further comprising: a checking module configured to check for the existence of at least one OWL document in the Web Ontology Language (OWL) in the SOA metadata documents; an OWL parser configured to parse each of the at least one OWL document to obtain OWL class in the OWL document; an OWL individual creator configured to create an OWL individual based on the OWL class of each of the at least one OWL document obtained by the OWL parser; and an ontology file generator configured to generate an ontology file containing the OWL class and the corresponding OWL individual for each of the at least one OWL document. | 0.500741 |
10,019,507 | 1 | 4 | 1. A method comprising: receiving data, wherein the data is organized as a plurality of named fields, wherein each named field includes a set of values associated with the named field, wherein each named field is assigned to a category from a plurality of categories and wherein each set of values includes two or more entries; determining, for at least one category, whether there is at least one identifier field for that category, wherein each identifier field is a named field that acts as an identifier for that category; and selecting a concept, wherein selecting the concept includes: determining whether one of the categories includes an identifier field that has a unique value for each entry in the identifier field set of values and, if so, selecting the identifier field as the concept; if none of the categories include an identifier field that has a unique value for each entry in the identifier field set of values, determining whether one of the categories includes two or more identifier fields that, when combined, have a unique value for each entry in the combined identifier field set of values and, if so, selecting the combined identifier fields as the concept; and if none of the categories include an identifier field that has a unique value for each entry in the identifier field set of values and if none of the categories include two or more identifier fields that, when combined, have a unique value for each entry in the combined identifier field set of values, adding a new identifier field, wherein adding the new identifier field includes providing a unique value for each entry in set of values included in the new identifier field, associating the new identifier field with one of the categories, and selecting the new identifier field as the concept. | 1. A method comprising: receiving data, wherein the data is organized as a plurality of named fields, wherein each named field includes a set of values associated with the named field, wherein each named field is assigned to a category from a plurality of categories and wherein each set of values includes two or more entries; determining, for at least one category, whether there is at least one identifier field for that category, wherein each identifier field is a named field that acts as an identifier for that category; and selecting a concept, wherein selecting the concept includes: determining whether one of the categories includes an identifier field that has a unique value for each entry in the identifier field set of values and, if so, selecting the identifier field as the concept; if none of the categories include an identifier field that has a unique value for each entry in the identifier field set of values, determining whether one of the categories includes two or more identifier fields that, when combined, have a unique value for each entry in the combined identifier field set of values and, if so, selecting the combined identifier fields as the concept; and if none of the categories include an identifier field that has a unique value for each entry in the identifier field set of values and if none of the categories include two or more identifier fields that, when combined, have a unique value for each entry in the combined identifier field set of values, adding a new identifier field, wherein adding the new identifier field includes providing a unique value for each entry in set of values included in the new identifier field, associating the new identifier field with one of the categories, and selecting the new identifier field as the concept. 4. The method of claim 1 , wherein one of the categories includes an identifier field with a unique value in the identifier field for each entry in the set of values. | 0.788804 |
8,644,458 | 15 | 17 | 15. A server for processing a call, the server comprising: a receiver for receiving a call from a caller over a communication network; a processor for determining a telephone number of the caller, and for determining if the telephone number of the caller is a telephone number assigned to a specific individual, for prompting the caller to select a language preference when the telephone number of the caller is determined to be assigned to a specific individual and the specific individual does not have a stored language preference, and for storing the language preference selected by the caller based on the prompting; an electronic database that is accessed by the processor to determine the stored language preference of the specific individual when the telephone number of the caller is determined to be assigned to a specific individual, the specific individual's stored language preference being associated with the caller's telephone number in the electronic database; and a router for routing the call to a predetermined destination based on the stored language preference of the specific individual in the electronic database when the telephone number of the caller is determined to be assigned to the specific individual, and for routing the call to a first default destination when the telephone number of the caller is determined to not be assigned to a specific individual. | 15. A server for processing a call, the server comprising: a receiver for receiving a call from a caller over a communication network; a processor for determining a telephone number of the caller, and for determining if the telephone number of the caller is a telephone number assigned to a specific individual, for prompting the caller to select a language preference when the telephone number of the caller is determined to be assigned to a specific individual and the specific individual does not have a stored language preference, and for storing the language preference selected by the caller based on the prompting; an electronic database that is accessed by the processor to determine the stored language preference of the specific individual when the telephone number of the caller is determined to be assigned to a specific individual, the specific individual's stored language preference being associated with the caller's telephone number in the electronic database; and a router for routing the call to a predetermined destination based on the stored language preference of the specific individual in the electronic database when the telephone number of the caller is determined to be assigned to the specific individual, and for routing the call to a first default destination when the telephone number of the caller is determined to not be assigned to a specific individual. 17. The server of claim 15 , wherein the first predetermined destination is an automated interactive voice response unit that implements a language associated with the stored language preference of the specific individual. | 0.736967 |
9,311,048 | 7 | 11 | 7. A method for generating electronic templates and using the electronic templates to extract response data from assessment content objects, the method comprising: receiving an electronic structure file that corresponds to an assessment and includes structure-file data, the structure-file data including a region of interest where a response to a question on the assessment is to be provided; rendering an image of the structure-file data or processed version of the structure-file data, the rendered image representing the region of interest; detecting a first input provided during a presentation of the rendered image corresponding to specification of a position of the region of interest; defining a segment-position specification indicative of the position of the region of interest; generating an electronic template that associates an identifier of the question-with the segment-position specification; detecting a second input identifying a target data element corresponding to the question; detecting a content object for processing that includes content-object data; determining that the content object for processing corresponds to the electronic template; extracting, using the segment-position specification of the template, a portion of the content-object data that corresponds to the region of interest, the portion of the content-object data including a response to the question on the assessment; evaluating the portion of the content-object data to identify the response to the question included in portion of the content-object data; determining an evaluation quality metric reflecting a confidence in the identification of the response; and determining whether a quality criterion is satisfied based on the evaluation quality metric; and when it is determined that the quality criterion is not satisfied: facilitating a presentation that includes the portion of the content-object data; and receiving a third input corresponding to an identification of a score corresponding to the response. | 7. A method for generating electronic templates and using the electronic templates to extract response data from assessment content objects, the method comprising: receiving an electronic structure file that corresponds to an assessment and includes structure-file data, the structure-file data including a region of interest where a response to a question on the assessment is to be provided; rendering an image of the structure-file data or processed version of the structure-file data, the rendered image representing the region of interest; detecting a first input provided during a presentation of the rendered image corresponding to specification of a position of the region of interest; defining a segment-position specification indicative of the position of the region of interest; generating an electronic template that associates an identifier of the question-with the segment-position specification; detecting a second input identifying a target data element corresponding to the question; detecting a content object for processing that includes content-object data; determining that the content object for processing corresponds to the electronic template; extracting, using the segment-position specification of the template, a portion of the content-object data that corresponds to the region of interest, the portion of the content-object data including a response to the question on the assessment; evaluating the portion of the content-object data to identify the response to the question included in portion of the content-object data; determining an evaluation quality metric reflecting a confidence in the identification of the response; and determining whether a quality criterion is satisfied based on the evaluation quality metric; and when it is determined that the quality criterion is not satisfied: facilitating a presentation that includes the portion of the content-object data; and receiving a third input corresponding to an identification of a score corresponding to the response. 11. The method for generating electronic templates and using the electronic templates to extract response data from assessment content objects as recited in claim 7 , further comprising: detecting a document type of the structure file; and processing the structure-file data so as to change a file type of the structure-file data from the electronic structure file. | 0.815657 |
7,660,811 | 1 | 5 | 1. A system that facilitates analyzing content of a multi-dimensional structure, the system comprising: an interface component that collects statements in a declarative language and relays the statements; a calculation component that receives relayed statements from the interface component, the statements being in a declarative language relating to modifying data, and executes such statements against the multi-dimensional structure, the calculation component recognizes that the statements relate to a recursive calculation assigned as a value of a cell in the multi-dimensional structure, the recursive calculation including a recursive reference back to the cell, the execution of the relayed statements modifying a portion of the data stored within the multi-dimensional structure; a pass generation component that, in response to the calculation component receiving the relayed statements and prior to the execution of the relayed statements by the calculation component, creates at least one pass, each pass including the portion of the data stored within the multi-dimensional structure as the portion of the data existed prior to the calculation component executed the relayed statements; and a pass analysis component that analyzes a previous pass and selects a value within a previous pass that enables the recursive calculation to complete through utilization of cells at multiple prior passes to complete a calculation or assignment, wherein storage operatively coupled to a processor retains at least a portion of the calculation component or the pass generation component. | 1. A system that facilitates analyzing content of a multi-dimensional structure, the system comprising: an interface component that collects statements in a declarative language and relays the statements; a calculation component that receives relayed statements from the interface component, the statements being in a declarative language relating to modifying data, and executes such statements against the multi-dimensional structure, the calculation component recognizes that the statements relate to a recursive calculation assigned as a value of a cell in the multi-dimensional structure, the recursive calculation including a recursive reference back to the cell, the execution of the relayed statements modifying a portion of the data stored within the multi-dimensional structure; a pass generation component that, in response to the calculation component receiving the relayed statements and prior to the execution of the relayed statements by the calculation component, creates at least one pass, each pass including the portion of the data stored within the multi-dimensional structure as the portion of the data existed prior to the calculation component executed the relayed statements; and a pass analysis component that analyzes a previous pass and selects a value within a previous pass that enables the recursive calculation to complete through utilization of cells at multiple prior passes to complete a calculation or assignment, wherein storage operatively coupled to a processor retains at least a portion of the calculation component or the pass generation component. 5. The system of claim 1 , wherein the pass generation component creates a plurality of passes, each pass accessible by reference to the pass. | 0.777429 |
7,587,318 | 28 | 39 | 28. A system for speech recognition, comprising: a first receiver that receives audio signals from a speech source; a second receiver that receives video signals from the speech source; a processor that detects if the audio signals can be processed and that processes the audio signals if the audio signals can be processed, the processor processing the video signals based on the detection that at least a portion of the audio signals can not be processed; a converter that converts at least one of the audio signals and the video signals to recognizable information; and an implementor that implements a task based on the recognizable information, wherein the processor determines if the video image of a user is detected and, if the user's video image is not detected, indicates to the user that the video image is not detected. | 28. A system for speech recognition, comprising: a first receiver that receives audio signals from a speech source; a second receiver that receives video signals from the speech source; a processor that detects if the audio signals can be processed and that processes the audio signals if the audio signals can be processed, the processor processing the video signals based on the detection that at least a portion of the audio signals can not be processed; a converter that converts at least one of the audio signals and the video signals to recognizable information; and an implementor that implements a task based on the recognizable information, wherein the processor determines if the video image of a user is detected and, if the user's video image is not detected, indicates to the user that the video image is not detected. 39. The system of claim 28 , wherein the system for speech recognition is part of a laptop computer, a home computer, a remote controller and/or a game console. | 0.704797 |
9,448,996 | 15 | 21 | 15. A manufacture comprising: non-transitory computer readable media comprising executable instructions, the executable instructions being executable by one or more processors to perform operations comprising: obtaining a translation of a message in a first language to a second language wherein the translation was submitted by a user; generating a part-of-speech (POS) n-gram representation of the translation comprising a plurality of POS n-grams of two or more different lengths; determining a respective probability for each POS n-gram as a ratio of a count of occurrences of the POS n-grams in a corpus for the second language to a count of all POS n-grams in the corpus having a same length as the POS n-gram and determining an accuracy of the translation based on a combination of the probabilities. | 15. A manufacture comprising: non-transitory computer readable media comprising executable instructions, the executable instructions being executable by one or more processors to perform operations comprising: obtaining a translation of a message in a first language to a second language wherein the translation was submitted by a user; generating a part-of-speech (POS) n-gram representation of the translation comprising a plurality of POS n-grams of two or more different lengths; determining a respective probability for each POS n-gram as a ratio of a count of occurrences of the POS n-grams in a corpus for the second language to a count of all POS n-grams in the corpus having a same length as the POS n-gram and determining an accuracy of the translation based on a combination of the probabilities. 21. The manufacture of claim 15 , wherein the operations further comprise: revoking the user's translation privileges if the accuracy falls below a threshold value. | 0.821351 |
8,156,430 | 8 | 12 | 8. A method for clustering nodes of a tree structure, comprising: maintaining a plurality of messages, each message represented as a node in a tree structure; assigning a word vector to each message; identifying pairs of the nodes based on relationships in the tree structure and combining the nodes of one or more of the pairs into clusters; adjusting boundaries of each cluster, comprising at least one of: placing a root node into one such cluster having a closest related child node; separating children nodes into distinct groups and retaining a relationship between a parent node and one such group comprising a nearest child node; and transferring a parent node to one such cluster having all children of the parent node; and forming a digest of the messages comprising one or more of the clusters. | 8. A method for clustering nodes of a tree structure, comprising: maintaining a plurality of messages, each message represented as a node in a tree structure; assigning a word vector to each message; identifying pairs of the nodes based on relationships in the tree structure and combining the nodes of one or more of the pairs into clusters; adjusting boundaries of each cluster, comprising at least one of: placing a root node into one such cluster having a closest related child node; separating children nodes into distinct groups and retaining a relationship between a parent node and one such group comprising a nearest child node; and transferring a parent node to one such cluster having all children of the parent node; and forming a digest of the messages comprising one or more of the clusters. 12. A method according to claim 8 , further comprising: assigning a primary status to those clusters that are larger than a minimum size; assigning a secondary status to the clusters that are smaller than the minimum size; and presenting the primary and secondary clusters. | 0.754054 |
8,260,790 | 7 | 8 | 7. A computer-readable medium including code stored thereon to allow an application program to access data in a static XML document, the code, when executed, comprising the steps of: for each node in the static XML document, determining a Node Offset value, at least in part, by parsing the static XML document; and storing the Node Offset value as an index offset value into an index file, wherein the index offset value is equal to adding a size, H, of a header of the index file with a product of an identifier value, I, multiplied by a size, Z, of the Node Offset and wherein the index offset value is used by an application program so that the application program can directly retrieve the data contained in the static XML document, wherein the retrieving is performed without parsing the entire static XML document. | 7. A computer-readable medium including code stored thereon to allow an application program to access data in a static XML document, the code, when executed, comprising the steps of: for each node in the static XML document, determining a Node Offset value, at least in part, by parsing the static XML document; and storing the Node Offset value as an index offset value into an index file, wherein the index offset value is equal to adding a size, H, of a header of the index file with a product of an identifier value, I, multiplied by a size, Z, of the Node Offset and wherein the index offset value is used by an application program so that the application program can directly retrieve the data contained in the static XML document, wherein the retrieving is performed without parsing the entire static XML document. 8. The computer-readable medium of claim 7 , wherein the method further comprises the step of the Node Offset values sequentially in the index file. | 0.734767 |
8,584,045 | 3 | 4 | 3. The method of claim 1 , further including, in response to user selection of the first graphical element, presenting a second graphical element corresponding to another set of data objects of a second type, and at least one semantic relationship between presented sets. | 3. The method of claim 1 , further including, in response to user selection of the first graphical element, presenting a second graphical element corresponding to another set of data objects of a second type, and at least one semantic relationship between presented sets. 4. The method of claim 3 , further including presenting information corresponding to the second graphical element in response to user selection of the second graphical element. | 0.969508 |
9,171,326 | 1 | 3 | 1. A computer-implemented method for user profiling comprising: evaluating a plurality of textual actions of a user, the plurality of textual actions comprising online social media activities wherein the user interacts with text or generates textual information; for each textual action of the plurality of textual actions, identifying one or more concepts by: identifying at least one entity corresponding to the each textual action of the plurality of textual actions, by using natural language processing, to identify parts of speech performed by the at least one entity; identifying two or more concept candidates for at least one of the identified at least one entity; and selecting one of the identified two or more concept candidates as one of the identified one or more concepts according to a user profile of the user; and generating an interest profile for the user according to the identified one or more concepts; wherein selecting the one of the identified two or more concept candidates comprises: calculating two or more first concept candidate scores for the identified two or more concept candidates, by, for each concept candidate, determining consistency of related concepts of the each concept candidate to the plurality of textual actions of the user profile; determining that a difference between a highest first concept candidate score of the two or more first concept candidate scores and others of the two or more first concept candidate scores does not exceed a first threshold condition; in response to determining that the difference between the highest first concept candidate score of the two or more first concept candidate scores and the others of the two or more first concept candidate scores does not exceed the first threshold condition, calculating two or more second concept candidate scores for the identified two or more concept candidates, by, for each concept candidate: determining a second consistency of the related concepts of the each concept candidate of the identified two or more concept candidates to one or more profiles of close friends of the user; and determining that a second difference between a highest second concept candidate score of the two or more second concept candidate scores and others of the two or more second concept candidate scores does not exceed a second threshold condition; in response to determining that the second difference between the highest second concept candidate score of the two or more second concept candidate scores and the others of the two or more second concept candidate scores does not exceed the second threshold condition, calculating two or more third concept candidate scores for the identified two or more concept candidates, by, for each concept candidate: determining a third consistency of the related concepts of the each concept candidate to one or more profiles of non-close friends of the user; and determining that a third difference between a highest third concept candidate score of the two or more third concept candidate scores and others of the two or more third concept candidate scores does not exceed a third threshold condition; in response to determining that the third difference between the highest third concept candidate score of the two or more third concept candidate scores and the others of the two or more third concept candidate scores does not exceed the third threshold condition, calculating two or more fourth concept candidate scores for the identified two or more concept candidates, by: determining a global popularity of the identified two or more concept candidates; and determining that a fourth difference between a highest fourth concept candidate score of the two or more fourth concept candidate scores and the others of the two or more fourth concept candidate scores meets a fourth threshold condition; and in response to determining that the fourth difference between the highest fourth concept candidate score of the two or more fourth concept candidate scores and others of the two or more fourth concept candidate scores meets the fourth threshold condition, selecting a concept candidate of the two or more concept candidates corresponding to the highest fourth concept candidate score as the identified one or more concepts. | 1. A computer-implemented method for user profiling comprising: evaluating a plurality of textual actions of a user, the plurality of textual actions comprising online social media activities wherein the user interacts with text or generates textual information; for each textual action of the plurality of textual actions, identifying one or more concepts by: identifying at least one entity corresponding to the each textual action of the plurality of textual actions, by using natural language processing, to identify parts of speech performed by the at least one entity; identifying two or more concept candidates for at least one of the identified at least one entity; and selecting one of the identified two or more concept candidates as one of the identified one or more concepts according to a user profile of the user; and generating an interest profile for the user according to the identified one or more concepts; wherein selecting the one of the identified two or more concept candidates comprises: calculating two or more first concept candidate scores for the identified two or more concept candidates, by, for each concept candidate, determining consistency of related concepts of the each concept candidate to the plurality of textual actions of the user profile; determining that a difference between a highest first concept candidate score of the two or more first concept candidate scores and others of the two or more first concept candidate scores does not exceed a first threshold condition; in response to determining that the difference between the highest first concept candidate score of the two or more first concept candidate scores and the others of the two or more first concept candidate scores does not exceed the first threshold condition, calculating two or more second concept candidate scores for the identified two or more concept candidates, by, for each concept candidate: determining a second consistency of the related concepts of the each concept candidate of the identified two or more concept candidates to one or more profiles of close friends of the user; and determining that a second difference between a highest second concept candidate score of the two or more second concept candidate scores and others of the two or more second concept candidate scores does not exceed a second threshold condition; in response to determining that the second difference between the highest second concept candidate score of the two or more second concept candidate scores and the others of the two or more second concept candidate scores does not exceed the second threshold condition, calculating two or more third concept candidate scores for the identified two or more concept candidates, by, for each concept candidate: determining a third consistency of the related concepts of the each concept candidate to one or more profiles of non-close friends of the user; and determining that a third difference between a highest third concept candidate score of the two or more third concept candidate scores and others of the two or more third concept candidate scores does not exceed a third threshold condition; in response to determining that the third difference between the highest third concept candidate score of the two or more third concept candidate scores and the others of the two or more third concept candidate scores does not exceed the third threshold condition, calculating two or more fourth concept candidate scores for the identified two or more concept candidates, by: determining a global popularity of the identified two or more concept candidates; and determining that a fourth difference between a highest fourth concept candidate score of the two or more fourth concept candidate scores and the others of the two or more fourth concept candidate scores meets a fourth threshold condition; and in response to determining that the fourth difference between the highest fourth concept candidate score of the two or more fourth concept candidate scores and others of the two or more fourth concept candidate scores meets the fourth threshold condition, selecting a concept candidate of the two or more concept candidates corresponding to the highest fourth concept candidate score as the identified one or more concepts. 3. The method of claim 1 , wherein the first, second, third, and fourth threshold conditions are identical. | 0.795019 |
8,346,526 | 2 | 19 | 2. A computer-readable medium comprising software, which when executed by a computer system causes the computer system to perform operations in a computing environment to generate a test in a test environment, the operations comprising: specifying, from within the test environment, a plurality of test elements within an iterations part of the test, the plurality of test elements including: a first test element being a simulation model having a block property, the model executed from within a second environment that is separate from the test environment, and a second test element that is not a simulation model, the second test element being executable; generating, from within the test environment, at least one test condition for the test, the at least one test condition specifying a number of values for the block property of the simulation model; specifying at least one metric setting for the simulation model; defining a test variable within the test environment; mapping, from within the test environment, the at least one metric setting of the simulation model to the test variable; running, by a computer, the test from within the test environment such that the simulation model is executed within the second environment for a plurality of iterations based on the number of block property values specified in the at least one test condition, and the second test element is executed for the plurality of iterations; generating, during each iteration of the simulation model, metric data based on the at least one metric setting for the simulation model, the metric data generated within the second environment; assigning the metric data generated in the second environment to the test variable of the test environment as a result of the mapping of the at least one metric setting of the simulation model to the test variable so that the metric data from the iterations of the simulation model is accumulated; and providing access to the accumulated metric data from within the test environment. | 2. A computer-readable medium comprising software, which when executed by a computer system causes the computer system to perform operations in a computing environment to generate a test in a test environment, the operations comprising: specifying, from within the test environment, a plurality of test elements within an iterations part of the test, the plurality of test elements including: a first test element being a simulation model having a block property, the model executed from within a second environment that is separate from the test environment, and a second test element that is not a simulation model, the second test element being executable; generating, from within the test environment, at least one test condition for the test, the at least one test condition specifying a number of values for the block property of the simulation model; specifying at least one metric setting for the simulation model; defining a test variable within the test environment; mapping, from within the test environment, the at least one metric setting of the simulation model to the test variable; running, by a computer, the test from within the test environment such that the simulation model is executed within the second environment for a plurality of iterations based on the number of block property values specified in the at least one test condition, and the second test element is executed for the plurality of iterations; generating, during each iteration of the simulation model, metric data based on the at least one metric setting for the simulation model, the metric data generated within the second environment; assigning the metric data generated in the second environment to the test variable of the test environment as a result of the mapping of the at least one metric setting of the simulation model to the test variable so that the metric data from the iterations of the simulation model is accumulated; and providing access to the accumulated metric data from within the test environment. 19. The computer-readable medium as in claim 2 , wherein the operations further comprise: designating a coverage path for the simulation model. | 0.803571 |
8,699,677 | 15 | 16 | 15. The method of claim 13 , further comprising transcribing the second segment separately from the first segment. | 15. The method of claim 13 , further comprising transcribing the second segment separately from the first segment. 16. The method of claim 15 , wherein transcribing the second segment separately from the first segment comprises transcribing the second segment in its own thread. | 0.93438 |
9,727,976 | 5 | 7 | 5. The computing device of claim 3 , wherein the minimum distance is a minimum distance between the second object and interpolated locations of the first object, the interpolated locations of the first object based upon the locations of the first object over the window of time. | 5. The computing device of claim 3 , wherein the minimum distance is a minimum distance between the second object and interpolated locations of the first object, the interpolated locations of the first object based upon the locations of the first object over the window of time. 7. The computing device of claim 5 , wherein the data assigned to the first node indicates that the first node corresponds to a first trajectory and a second trajectory, the first trajectory comprising locations of the first object during a first window of time in the window of time, the second trajectory comprising locations of the first object during a second window of time in the window of time, wherein further each of the interpolated locations is based exclusively upon either the locations of the first object during the first window of time or the locations of the first object during the second window of time. | 0.773818 |
8,989,785 | 6 | 7 | 6. The method of claim 1 , further comprising providing options associated with the specific audio voice message to the recipient in response to the recipient linking to the specific audio voice message via the identifier. | 6. The method of claim 1 , further comprising providing options associated with the specific audio voice message to the recipient in response to the recipient linking to the specific audio voice message via the identifier. 7. The method of claim 6 , wherein the options include at least one of listening to the audio voice message, deleting the audio voice message, and forwarding the audio voice message. | 0.824663 |
9,966,073 | 13 | 14 | 13. An apparatus including memory and one or more processors operable to execute instructions stored in the memory, comprising instructions to: receive a voice input with a voice-enabled electronic device, the voice input including an original request that includes first and second portions, the second portion including a first context sensitive entity among a plurality of context sensitive entities that are associated with a context sensitive parameter and that potentially may be spoken in the voice input; and in the voice-enabled electronic device, and responsive to receiving the first portion of the voice input: perform local processing of the first portion of the voice input to dynamically build at least a portion of a voice action prior to completely receiving the voice input with the voice-enabled electronic device; determine during the local processing whether the voice action is associated with the context sensitive parameter; and in response to a determination that the voice action is associated with the context sensitive parameter and prior to performing local processing of the second portion of the voice input including the first context sensitive entity, initiate a dynamic update to a local voice to text model used by the voice-enabled electronic device prior to completing the voice action to facilitate recognition of the first context sensitive entity. | 13. An apparatus including memory and one or more processors operable to execute instructions stored in the memory, comprising instructions to: receive a voice input with a voice-enabled electronic device, the voice input including an original request that includes first and second portions, the second portion including a first context sensitive entity among a plurality of context sensitive entities that are associated with a context sensitive parameter and that potentially may be spoken in the voice input; and in the voice-enabled electronic device, and responsive to receiving the first portion of the voice input: perform local processing of the first portion of the voice input to dynamically build at least a portion of a voice action prior to completely receiving the voice input with the voice-enabled electronic device; determine during the local processing whether the voice action is associated with the context sensitive parameter; and in response to a determination that the voice action is associated with the context sensitive parameter and prior to performing local processing of the second portion of the voice input including the first context sensitive entity, initiate a dynamic update to a local voice to text model used by the voice-enabled electronic device prior to completing the voice action to facilitate recognition of the first context sensitive entity. 14. The apparatus of claim 13 , wherein the instructions include: first instructions implementing a streaming voice to text module that converts a digital audio signal of the voice input to text, wherein the first instructions dynamically generate a plurality of text tokens from the digital audio signal; and second instructions implementing a streaming semantic processor that dynamically builds the portion of the voice action from at least a portion of the plurality of text tokens. | 0.631818 |
8,595,370 | 4 | 7 | 4. A method comprising: receiving, from a process associated with a particular webpage, a request to display a clickable item on said particular webpage; providing, to said process, said clickable item to be displayed on said particular webpage; after providing said clickable item to said process, receiving an indication that the clickable item has been selected; and in response to said indication, providing a new page to be displayed that contains at least one of (a) URLs corresponding to a subset of linking webpages that each contains a link to said particular webpage, wherein the linking webpages are determined to contain a link to said particular webpage by an automated web crawler or (b) a subset of tags that have been associated with said particular webpage by a plurality of users who have visited said particular webpage, wherein each tag is one or more words and is created, by a user of the plurality of users who has visited said particular webpage to describe content of said particular webpage, subsequent to the creation of said particular webpage. | 4. A method comprising: receiving, from a process associated with a particular webpage, a request to display a clickable item on said particular webpage; providing, to said process, said clickable item to be displayed on said particular webpage; after providing said clickable item to said process, receiving an indication that the clickable item has been selected; and in response to said indication, providing a new page to be displayed that contains at least one of (a) URLs corresponding to a subset of linking webpages that each contains a link to said particular webpage, wherein the linking webpages are determined to contain a link to said particular webpage by an automated web crawler or (b) a subset of tags that have been associated with said particular webpage by a plurality of users who have visited said particular webpage, wherein each tag is one or more words and is created, by a user of the plurality of users who has visited said particular webpage to describe content of said particular webpage, subsequent to the creation of said particular webpage. 7. The method of claim 4 , wherein: the new page contains the URLs corresponding to the subset of linking webpages; and the method further comprising, for each URL of said URLs, providing, to be displayed on said new page, at least one of (a) anchor text from the linking webpage corresponding to said each URL or (b) text, from the corresponding linking webpage, that is adjacent to said anchor text. | 0.790272 |
9,990,919 | 14 | 16 | 14. An article, comprising: a non-transitory computer-readable medium having stored instructions that enable a machine to: perform speech recognition on user dictated words to generate a dictation; parse the dictation using a deterministic formatting grammar module to build a concept-tagged formatting graph; extract features from the formatting graph; estimate scores for the extracted features using a discriminative statistical model, wherein the discriminative statistical model is derived from a deterministic formatting grammar module and user formatted documents; choose a path in the formatting graph as a formatting selection based on the estimated scores; and output the dictation as formatted text based on the formatting selection to provide an integrated stochastic and deterministic formatting of the dictation for disambiguation of the user dictated words. | 14. An article, comprising: a non-transitory computer-readable medium having stored instructions that enable a machine to: perform speech recognition on user dictated words to generate a dictation; parse the dictation using a deterministic formatting grammar module to build a concept-tagged formatting graph; extract features from the formatting graph; estimate scores for the extracted features using a discriminative statistical model, wherein the discriminative statistical model is derived from a deterministic formatting grammar module and user formatted documents; choose a path in the formatting graph as a formatting selection based on the estimated scores; and output the dictation as formatted text based on the formatting selection to provide an integrated stochastic and deterministic formatting of the dictation for disambiguation of the user dictated words. 16. The article according to claim 14 , wherein user dictated words include dates, times, addresses, birthdates, currencies, fractions, equations, alphanumeric sequences, abbreviations, telephone numbers, postal codes, email addresses, and measurements. | 0.640625 |
8,576,097 | 1 | 7 | 1. A method comprising: receiving a syntax element to be encoded as a code word, wherein the syntax element relates to at least one of a coded block pattern, a transform split pattern, or motion partition information; determining, by a computing device, a mapping between the syntax element and the code word on the basis of a hierarchy level in a tree structure, wherein the tree structure relates to at least one of a transform block size, a prediction block size, or a block size, and wherein the hierarchy level represents division of a block into smaller blocks; using the mapping to obtain the code word; and updating the mapping. | 1. A method comprising: receiving a syntax element to be encoded as a code word, wherein the syntax element relates to at least one of a coded block pattern, a transform split pattern, or motion partition information; determining, by a computing device, a mapping between the syntax element and the code word on the basis of a hierarchy level in a tree structure, wherein the tree structure relates to at least one of a transform block size, a prediction block size, or a block size, and wherein the hierarchy level represents division of a block into smaller blocks; using the mapping to obtain the code word; and updating the mapping. 7. The method according to claim 1 , further comprising using at least two sorting tables, and using the hierarchy level to select a sorting table from said at least two sorting tables. | 0.858129 |
9,613,618 | 2 | 4 | 2. The method as claimed in claim 1 , wherein the context information comprises at least one of: whether a name of a country exists within the voice input signal; information on a place where an apparatus for recognizing the voice input signal is located; dialogue history information; and an updated non-primary language database. | 2. The method as claimed in claim 1 , wherein the context information comprises at least one of: whether a name of a country exists within the voice input signal; information on a place where an apparatus for recognizing the voice input signal is located; dialogue history information; and an updated non-primary language database. 4. The method as claimed in claim 2 , wherein determining the language of the segment of the voice input signal based on the context information comprises: determining that the language of the segment of the voice input signal is a language for at least one of characteristics of a country and a place where the apparatus for recognizing the voice input signal is located, based on measured Global Positioning System (GPS) coordinates. | 0.898931 |
8,266,163 | 6 | 8 | 6. A data processing system for utilizing reference/identification (ID) linking in extensible markup language (XML) wrapper code generation in a data processing system, said data processing system comprising: a processor; an interconnect coupled to said processor; and a computer-readable storage medium embodying computer program code, said computer program code comprising instructions executable by said processor and configured for: receiving a type document and reference/ID constraints document; and accessing said reference/ID constraints document to translate between XML structures and object structures, wherein said instructions for accessing further include instructions configured for: creating a directed constraint graph from said reference/ID constraints document, wherein said directed constraint graph comprises at least one root XML structure that is not referenced by other XML structures and at least one leaf XML structure that does not reference other XML structures; generating a first set of deserialization code for at least one XML structure not in said directed constraint graph, wherein said first set of deserialization code translates said at least one XML structure not in said directed constraint graph into at least one object structure not in said directed constraint graph; creating a second set of deserialization code for said at least one XML leaf structure in said directed constraint graph, wherein said second set of deserialization code translates said at least one leaf XML structure into at least one leaf object structure; generating a third set of deserialization code for at least one next highest XML structure in said directed constraint graph, wherein said third set of deserialization code translates said at least one next highest XML structure into at least one next highest object structure; storing at least one intermediate object structure in at least one temporary hash table, wherein said at least one intermediate object structure is not a root object structure or a leaf object structure; and creating cleanup functions within said first, second, and third sets of deserialization code, wherein said cleanup functions remove all temporary hash tables utilized in object serialization. | 6. A data processing system for utilizing reference/identification (ID) linking in extensible markup language (XML) wrapper code generation in a data processing system, said data processing system comprising: a processor; an interconnect coupled to said processor; and a computer-readable storage medium embodying computer program code, said computer program code comprising instructions executable by said processor and configured for: receiving a type document and reference/ID constraints document; and accessing said reference/ID constraints document to translate between XML structures and object structures, wherein said instructions for accessing further include instructions configured for: creating a directed constraint graph from said reference/ID constraints document, wherein said directed constraint graph comprises at least one root XML structure that is not referenced by other XML structures and at least one leaf XML structure that does not reference other XML structures; generating a first set of deserialization code for at least one XML structure not in said directed constraint graph, wherein said first set of deserialization code translates said at least one XML structure not in said directed constraint graph into at least one object structure not in said directed constraint graph; creating a second set of deserialization code for said at least one XML leaf structure in said directed constraint graph, wherein said second set of deserialization code translates said at least one leaf XML structure into at least one leaf object structure; generating a third set of deserialization code for at least one next highest XML structure in said directed constraint graph, wherein said third set of deserialization code translates said at least one next highest XML structure into at least one next highest object structure; storing at least one intermediate object structure in at least one temporary hash table, wherein said at least one intermediate object structure is not a root object structure or a leaf object structure; and creating cleanup functions within said first, second, and third sets of deserialization code, wherein said cleanup functions remove all temporary hash tables utilized in object serialization. 8. The system according to claim 6 , wherein said instructions for accessing are further configured for: for at least a first object structure to be serialized, generating a first serialization code for at least one child object structure, wherein only an identifying attribute of said at least one child object structure is serialized into an XML structure of said at least first object structure; and creating a second serialization code for at least one non-referenced child object. | 0.501029 |
8,966,645 | 2 | 3 | 2. The method of claim 1 , where: the text entry context information comprises at least one of run-time text-based and run-time time-based analysis of a manner of entry and content of characters of the text entry that omits evaluation of known passwords; and evaluating, via the processor without the use of any configured password, the text entry context information associated with the text entry within the inter-user communication application comprises: determining whether the text entry comprises a single-string input; and determining, in response to determining that the text entry comprises the single-string input, whether a time since a last text entry is greater than or equal to a configured text evaluation threshold of time. | 2. The method of claim 1 , where: the text entry context information comprises at least one of run-time text-based and run-time time-based analysis of a manner of entry and content of characters of the text entry that omits evaluation of known passwords; and evaluating, via the processor without the use of any configured password, the text entry context information associated with the text entry within the inter-user communication application comprises: determining whether the text entry comprises a single-string input; and determining, in response to determining that the text entry comprises the single-string input, whether a time since a last text entry is greater than or equal to a configured text evaluation threshold of time. 3. The method of claim 2 , where: determining that the evaluated text entry context information identifies the text string entered by the user as the potential password inadvertently entered into the inter-user communication application by the user comprises: performing, in response to determining that the text entry comprises the single-string input, a spell check on the text entry; and determining that the spell check failed. | 0.88634 |
8,924,391 | 10 | 12 | 10. The method of claim 9 , wherein said mapping assigns each of said plurality of texts a position in concept space by assigning, for each of said plurality of texts, a relevance score against each of the n Wikipedia articles and creating a vector that contains each of the n relevance scores for a given one of the plurality of texts. | 10. The method of claim 9 , wherein said mapping assigns each of said plurality of texts a position in concept space by assigning, for each of said plurality of texts, a relevance score against each of the n Wikipedia articles and creating a vector that contains each of the n relevance scores for a given one of the plurality of texts. 12. The method of claim 10 , wherein a relevance score for said given one of the plurality of texts against a given one of the n Wikipedia articles is calculated by determining the relevance of each 2-gram in said given one of the plurality of texts to one of the n Wikipedia articles and combining the relevances of each of the 2-grams. | 0.852063 |
8,666,992 | 1 | 7 | 1. A method of querying a remote service without revealing a private document to the remote service, comprising: at a main computer, receiving from a client a signature generated from a user's private document, without receiving the document; querying an intermediate database with the signature of the private document to generate an intermediate result set comprising intermediate database documents, based on a computation of similarity of the signatures of the intermediate database documents to the signature of the private document; computing a relevance factor for each document of the intermediate result set; computing a reconstruction error based on the relevance factors of all the documents in the intermediate result set and determining a confidence in the intermediate result set based on the reconstruction error; querying the remote service with a query which is based on the intermediate result set, whereby the user's private document and the signature of the private document are not revealed to the remote service; receiving a final result set from the remote service based on the query; and weighting the final result set based on the relevance factors. | 1. A method of querying a remote service without revealing a private document to the remote service, comprising: at a main computer, receiving from a client a signature generated from a user's private document, without receiving the document; querying an intermediate database with the signature of the private document to generate an intermediate result set comprising intermediate database documents, based on a computation of similarity of the signatures of the intermediate database documents to the signature of the private document; computing a relevance factor for each document of the intermediate result set; computing a reconstruction error based on the relevance factors of all the documents in the intermediate result set and determining a confidence in the intermediate result set based on the reconstruction error; querying the remote service with a query which is based on the intermediate result set, whereby the user's private document and the signature of the private document are not revealed to the remote service; receiving a final result set from the remote service based on the query; and weighting the final result set based on the relevance factors. 7. The method of claim 1 , wherein the remote service provides a category of document search and the final result set comprises category labels for the documents in intermediate result set. | 0.788117 |
9,171,070 | 11 | 12 | 11. A method comprising: generating, using at least one processor, a first attribute set and a second attribute set for use in classifying electronic documents; receiving an electronic document having an unknown query signature; analyzing the electronic document to determine whether the electronic document contains one or more attributes selected from the first attribute set; making a first determination as to whether the electronic document contains a number of attributes selected from the first attribute set above a first threshold; classifying the electronic document based on the first determination; if the electronic document does not contain a number of attributes selected from the first attribute set above the first threshold, analyzing the electronic document to determine whether the electronic document contains one or more attributes selected from the second attribute set; making a second determination as to whether the electronic document contains a number of attributes selected from the second attribute set above the second threshold; and classifying the electronic document based on the second determination. | 11. A method comprising: generating, using at least one processor, a first attribute set and a second attribute set for use in classifying electronic documents; receiving an electronic document having an unknown query signature; analyzing the electronic document to determine whether the electronic document contains one or more attributes selected from the first attribute set; making a first determination as to whether the electronic document contains a number of attributes selected from the first attribute set above a first threshold; classifying the electronic document based on the first determination; if the electronic document does not contain a number of attributes selected from the first attribute set above the first threshold, analyzing the electronic document to determine whether the electronic document contains one or more attributes selected from the second attribute set; making a second determination as to whether the electronic document contains a number of attributes selected from the second attribute set above the second threshold; and classifying the electronic document based on the second determination. 12. The method of claim 11 , further comprising assigning a query signature to the electronic document based on the classification of the electronic document. | 0.878834 |
7,593,843 | 8 | 14 | 8. The method of claim 1 , wherein calculating a score for each transfer mapping in the set of transfer mappings that describe a select node of the input semantic structure comprises: computing separate scores for a plurality of models; and combining the separate scores to determine the score for each transfer mapping that describe a select node of the input semantic structure. | 8. The method of claim 1 , wherein calculating a score for each transfer mapping in the set of transfer mappings that describe a select node of the input semantic structure comprises: computing separate scores for a plurality of models; and combining the separate scores to determine the score for each transfer mapping that describe a select node of the input semantic structure. 14. The method of claim 8 wherein combining the separate scores comprises: multiplying each score by a weight to form weighted model scores; and summing the weighted model scores to determine the score for each transfer mapping that describe a select node of the input semantic structure. | 0.885624 |
8,612,359 | 37 | 38 | 37. The client device of claim 33 , wherein the machine instructions further cause the processor to perform the operation of enabling the online portal subscriber to select a public activity in which to participate. | 37. The client device of claim 33 , wherein the machine instructions further cause the processor to perform the operation of enabling the online portal subscriber to select a public activity in which to participate. 38. The client device of claim 37 , wherein the existing member of the online social network has expressed an interest in the public activity, and the machine instructions further cause the processor to perform the operation of making available to the existing member, a predefined subset of the portal subscriber information related to the public activity. | 0.938596 |
8,639,636 | 29 | 33 | 29. A computer-readable storage device having instructions stored which, when executed on a computing device, cause the computing device to perform operations comprising: tracking user behavior across multiple modalities for interacting with a device; storing representations of the user behavior in a log as descriptors, each descriptor associated with a modality, the descriptors comprising a first descriptor associated with a first modality and a second descriptor associated with a second modality, wherein the first modality and the second modality are distinct modalities; normalizing the descriptors, wherein the first descriptor and the second descriptor are normalized based on: (1) the first modality, (2) the second modality, (3) the device, and (4) a format associated with the device, to yield normalized descriptors; merging the normalized descriptors into a unified click stream; generating a behavioral model by analyzing the unified click stream; and upon receiving user input associated with modifying a presentation of search results associated with a search, dynamically modifying the presentation by using the behavioral model to generate the search results. | 29. A computer-readable storage device having instructions stored which, when executed on a computing device, cause the computing device to perform operations comprising: tracking user behavior across multiple modalities for interacting with a device; storing representations of the user behavior in a log as descriptors, each descriptor associated with a modality, the descriptors comprising a first descriptor associated with a first modality and a second descriptor associated with a second modality, wherein the first modality and the second modality are distinct modalities; normalizing the descriptors, wherein the first descriptor and the second descriptor are normalized based on: (1) the first modality, (2) the second modality, (3) the device, and (4) a format associated with the device, to yield normalized descriptors; merging the normalized descriptors into a unified click stream; generating a behavioral model by analyzing the unified click stream; and upon receiving user input associated with modifying a presentation of search results associated with a search, dynamically modifying the presentation by using the behavioral model to generate the search results. 33. The computer-readable storage device of claim 29 , wherein user behavior is filtered according to relevance. | 0.854922 |
8,576,430 | 1 | 14 | 1. A method for determining a print job schedule for a printing production facility having a set of availably printing resources, comprising: defining one or more scheduling classifications; receiving one or more print jobs, each print job having a print job description specified by a set of print job attributes; determining one or more scheduling classification corresponding to the received print jobs; using a processor to automatically determine the print job schedule for the received print jobs using an answer set programming language solver responsive to: the print job descriptions; a set of resource descriptions for the available printing resources; a set of scheduling rules, wherein the scheduling rules are answer set programming statements; and a historical decision database stored in a processor accessible memory, wherein the historical decision database stores an indication of previously successful decision frequencies as a function of scheduling classification; wherein the print job schedule assigns a time schedule and one or more printing resources for each of the received print jobs. | 1. A method for determining a print job schedule for a printing production facility having a set of availably printing resources, comprising: defining one or more scheduling classifications; receiving one or more print jobs, each print job having a print job description specified by a set of print job attributes; determining one or more scheduling classification corresponding to the received print jobs; using a processor to automatically determine the print job schedule for the received print jobs using an answer set programming language solver responsive to: the print job descriptions; a set of resource descriptions for the available printing resources; a set of scheduling rules, wherein the scheduling rules are answer set programming statements; and a historical decision database stored in a processor accessible memory, wherein the historical decision database stores an indication of previously successful decision frequencies as a function of scheduling classification; wherein the print job schedule assigns a time schedule and one or more printing resources for each of the received print jobs. 14. The method of claim 1 wherein the answer set programming language solver utilizes a search strategy to search a decision tree, and wherein the search strategy is adjusted responsive to the historical decision database. | 0.502242 |
7,836,394 | 1 | 9 | 1. A computer program product, comprising a computer-readable storage medium including computer-readable instructions embodied therein, that when executed by one or more processors, implement a method for the retrieval, analysis and display of electronically tagged financial data, the instructions comprising: an integrated file access component, analysis component and presentation component for accessing, analyzing and presenting electronically tagged financial data within the application; the file access component comprising: one or more user selection modules for selecting a plurality of files, the files including at least electronically tagged financial data which adhere to different taxonomies that are associated with the same type of content, the analysis component comprising: one or more analysis modules for calculating at least a first common analysis measure for comparison and analysis of electronically tagged financial data from a first file which adheres to a first taxonomy and corresponding electronically tagged financial data from a second file which adheres to a second taxonomy that are associated with the same type of content, including (i) a first formula having components based on the first taxonomy for calculating the first common analysis measure from electronically tagged financial data from the first file, and (ii) a second formula having components based on the second taxonomy for calculating the first common analysis measure from electronically tagged financial data from the second file, wherein the first common analysis measure comprises an analytical metric not present in either the first file or the second file; and the presentation component comprising: one or more presentation modules for presenting information associated with the selected files, the presented information including data elements and a calculation of at least the first common analysis measure automatically formatted according to presentation information associated with the selected files so as to provide simultaneous line-by-line display of at least the first calculated common analysis measures that correspond to different taxonomies and another calculated common analysis measure. | 1. A computer program product, comprising a computer-readable storage medium including computer-readable instructions embodied therein, that when executed by one or more processors, implement a method for the retrieval, analysis and display of electronically tagged financial data, the instructions comprising: an integrated file access component, analysis component and presentation component for accessing, analyzing and presenting electronically tagged financial data within the application; the file access component comprising: one or more user selection modules for selecting a plurality of files, the files including at least electronically tagged financial data which adhere to different taxonomies that are associated with the same type of content, the analysis component comprising: one or more analysis modules for calculating at least a first common analysis measure for comparison and analysis of electronically tagged financial data from a first file which adheres to a first taxonomy and corresponding electronically tagged financial data from a second file which adheres to a second taxonomy that are associated with the same type of content, including (i) a first formula having components based on the first taxonomy for calculating the first common analysis measure from electronically tagged financial data from the first file, and (ii) a second formula having components based on the second taxonomy for calculating the first common analysis measure from electronically tagged financial data from the second file, wherein the first common analysis measure comprises an analytical metric not present in either the first file or the second file; and the presentation component comprising: one or more presentation modules for presenting information associated with the selected files, the presented information including data elements and a calculation of at least the first common analysis measure automatically formatted according to presentation information associated with the selected files so as to provide simultaneous line-by-line display of at least the first calculated common analysis measures that correspond to different taxonomies and another calculated common analysis measure. 9. The computer program product of claim 1 , further comprising a multiple document interface for displaying and navigating the presented information. | 0.866548 |
9,020,822 | 13 | 15 | 13. The method of claim 11 , further comprising determining one or more salient portions of the input window of sound, wherein extracting one or more auditory attention features from the auditory spectrum includes extracting one or more auditory attention features from the one or more salient portions. | 13. The method of claim 11 , further comprising determining one or more salient portions of the input window of sound, wherein extracting one or more auditory attention features from the auditory spectrum includes extracting one or more auditory attention features from the one or more salient portions. 15. The method of claim 13 , wherein determining one or more emotion classes corresponding to the input window of sound includes comparing the auditory attention features extracted from the one or more salient portions to one or more learned auditory attention features for known emotion classes. | 0.844211 |
10,133,448 | 4 | 5 | 4. The non-transitory computer storage medium of claim 1 , further comprising instructions for conducting polls to obtain additional information pertaining to said reviewer's preference and said reviewer account. | 4. The non-transitory computer storage medium of claim 1 , further comprising instructions for conducting polls to obtain additional information pertaining to said reviewer's preference and said reviewer account. 5. The non-transitory computer storage medium of claim 4 , further comprising instructions for adding new questions for said polls via said website. | 0.960065 |
9,485,207 | 16 | 17 | 16. The one or more non-transitory computer readable media of claim 12 , wherein provide a notification of the message collection comprises provide a visual notification on a personal computing device associated with the user, the visual notification indicating that the message collection is available for viewing and information about the message collection, including number of messages, a theme of the message collection, and the modalities associated with messages in the message collection. | 16. The one or more non-transitory computer readable media of claim 12 , wherein provide a notification of the message collection comprises provide a visual notification on a personal computing device associated with the user, the visual notification indicating that the message collection is available for viewing and information about the message collection, including number of messages, a theme of the message collection, and the modalities associated with messages in the message collection. 17. The one or more non-transitory computer readable media of claim 16 , wherein the visual notification is selectable using an input device, and wherein the message collection is displayed in response to selection of the visual notification by the user. | 0.939924 |
8,250,046 | 20 | 21 | 20. A system for performing cross-language search, comprising: a data processing apparatus; a data store storing instructions that, when executed by the data processing apparatus, cause the data processing apparatus to define: an input module operable to receive an original search query in a first language from a user; a query evaluation module operable to determine that the original search query includes an entity, the entity being one or more words that are a noun indicative of a place of origin where a second language is primarily spoken, the second language being different from the first language; and in response to the determination: obtain a translated search query for the original search query, the translated search query being in the second language; determine that the translated search query is a candidate for a cross-language search, wherein the determining comprises: obtaining a number of previous queries that correspond to the translated search query; comparing the number of previous queries to a threshold number of queries; determining that the number of previous queries exceeds the threshold number of queries; and determining that the translated search query is a candidate for a cross-language search in response to determining that the number of previous queries exceeds the threshold number of queries; and an output module operable to generate search results relevant to the translated search query in response to determining that the translated search query is a candidate for a cross-language search. | 20. A system for performing cross-language search, comprising: a data processing apparatus; a data store storing instructions that, when executed by the data processing apparatus, cause the data processing apparatus to define: an input module operable to receive an original search query in a first language from a user; a query evaluation module operable to determine that the original search query includes an entity, the entity being one or more words that are a noun indicative of a place of origin where a second language is primarily spoken, the second language being different from the first language; and in response to the determination: obtain a translated search query for the original search query, the translated search query being in the second language; determine that the translated search query is a candidate for a cross-language search, wherein the determining comprises: obtaining a number of previous queries that correspond to the translated search query; comparing the number of previous queries to a threshold number of queries; determining that the number of previous queries exceeds the threshold number of queries; and determining that the translated search query is a candidate for a cross-language search in response to determining that the number of previous queries exceeds the threshold number of queries; and an output module operable to generate search results relevant to the translated search query in response to determining that the translated search query is a candidate for a cross-language search. 21. The system of claim 20 , determining that the translated search query is a candidate for a cross-language search further comprises: identifying a set of web pages responsive to the translated search query and a set of relevance scores for the set of web pages; comparing the relevance score to a threshold relevance score; determining that the relevance score exceeds the threshold relevance score; and determining that the translated search query is a candidate for a cross-language search in response to determining that the relevance score exceeds the threshold relevance score. | 0.607909 |
7,953,679 | 8 | 13 | 8. The method of claim 1 , wherein the generating of a document index comprises: computing a similarity between each layout block in the provided document and each representative block; and generating a document index for each provided document based on the computed similarities. | 8. The method of claim 1 , wherein the generating of a document index comprises: computing a similarity between each layout block in the provided document and each representative block; and generating a document index for each provided document based on the computed similarities. 13. The method of claim 8 , wherein the computing of the similarity between each layout block in a provided document and each representative block comprises determining an extent of overlap between the layout block and the representative block. | 0.93829 |
8,122,043 | 9 | 17 | 9. A system for ranking the relevance of each of a plurality of documents in a corpus to a search query comprising: a) a processing unit capable of performing calculations; b) a storage device on which is stored a corpus of documents; c) an input device for receiving the search query; d) an output device for displaying the results of the ranking; wherein the processing unit groups words in the search query by synonym into one or more word groups; wherein the processing unit, for each word group, counts the number of instances (the “FQ” value) that a word from the word group appears in the search query; wherein the processing unit determines the maximum FQ value among all the word groups; wherein the processing unit calculates a scaling factor K; wherein the processing unit, for each word group, calculates a term frequency (“TF”) value by dividing the FQ value for the word group by the maximum FQ value and applying scaling factor K to the resulting quotient; wherein the processing unit, for each word group, counts the number of documents (“FC”) in the corpus that contain at least one word from the word group; wherein the processing unit counts the number of documents (“N”) in the corpus; wherein the processing unit, for each word group, calculates an inverse document frequency (“IDF”) value by dividing N by FC, adding one to the resulting quotient, and taking the natural logarithm of the resulting sum; wherein the processing unit, for each word group, calculates a TF-IDF value by multiplying said TF value by said IDF value; and wherein the processing unit ranks the relevance of each document in the corpus utilizing the TF-IDF values for the word groups in the search query. | 9. A system for ranking the relevance of each of a plurality of documents in a corpus to a search query comprising: a) a processing unit capable of performing calculations; b) a storage device on which is stored a corpus of documents; c) an input device for receiving the search query; d) an output device for displaying the results of the ranking; wherein the processing unit groups words in the search query by synonym into one or more word groups; wherein the processing unit, for each word group, counts the number of instances (the “FQ” value) that a word from the word group appears in the search query; wherein the processing unit determines the maximum FQ value among all the word groups; wherein the processing unit calculates a scaling factor K; wherein the processing unit, for each word group, calculates a term frequency (“TF”) value by dividing the FQ value for the word group by the maximum FQ value and applying scaling factor K to the resulting quotient; wherein the processing unit, for each word group, counts the number of documents (“FC”) in the corpus that contain at least one word from the word group; wherein the processing unit counts the number of documents (“N”) in the corpus; wherein the processing unit, for each word group, calculates an inverse document frequency (“IDF”) value by dividing N by FC, adding one to the resulting quotient, and taking the natural logarithm of the resulting sum; wherein the processing unit, for each word group, calculates a TF-IDF value by multiplying said TF value by said IDF value; and wherein the processing unit ranks the relevance of each document in the corpus utilizing the TF-IDF values for the word groups in the search query. 17. The system of claim 9 further comprising: a) a document search server; b) a search appliance; and c) a database. | 0.864486 |
8,719,244 | 1 | 4 | 1. A method comprising: based on a search query, using a computer server system having one or more processors to select a first entry in an index that is stored at a storage device, wherein the first entry is relevant to the search query and comprises a first information item and a first sentence fragment, wherein the first sentence fragment and the first information item are extracted from text of a first electronic document and wherein the first sentence fragment differs from the first information item; generating a search result set comprising at least the first information item of the first entry using the computer server system; and outputting the search result set from the computer server system for use by a client device. | 1. A method comprising: based on a search query, using a computer server system having one or more processors to select a first entry in an index that is stored at a storage device, wherein the first entry is relevant to the search query and comprises a first information item and a first sentence fragment, wherein the first sentence fragment and the first information item are extracted from text of a first electronic document and wherein the first sentence fragment differs from the first information item; generating a search result set comprising at least the first information item of the first entry using the computer server system; and outputting the search result set from the computer server system for use by a client device. 4. The method of claim 1 , wherein the selecting the first entry in the index comprises identifying that the first sentence fragment includes a term in the search query. | 0.803488 |
8,019,705 | 5 | 15 | 5. A hardware active element machine implemented method comprising: translating a first computer language into a second computer language, and translating the second language into active element instructions, which are instructions implemented by the active element machine and which indicate settings of parameters of components of the active element machine, which is a machine that includes at least a multiplicity of man-made computing elements, and a multiplicity of man-made couplings communicatively connecting the multiplicity of man-made computing elements to one another, such that the man-made couplings are capable of transmitting messages between the multiplicity of computing elements; one of the settings of the parameters including an indication of a time when the active element instruction will be implemented. | 5. A hardware active element machine implemented method comprising: translating a first computer language into a second computer language, and translating the second language into active element instructions, which are instructions implemented by the active element machine and which indicate settings of parameters of components of the active element machine, which is a machine that includes at least a multiplicity of man-made computing elements, and a multiplicity of man-made couplings communicatively connecting the multiplicity of man-made computing elements to one another, such that the man-made couplings are capable of transmitting messages between the multiplicity of computing elements; one of the settings of the parameters including an indication of a time when the active element instruction will be implemented. 15. The system of claim 5 , wherein the first computer language is a program for a Linux operating system kernel. | 0.973879 |
9,459,995 | 1 | 5 | 1. An apparatus for testing compliance of a computing system, the apparatus comprising a processor and a memory storing executable instructions that in response to execution by the processor cause the apparatus to at least: receive a collection of rules in a first set of markup-language statements, the collection of rules representing a configuration benchmark against which a computing system is to be tested for compliance, the computing system having interconnected components; parse the collection of rules to obtain test references to tests and comparison values used therein, the tests being defined in a second set of markup-language statements, with references to at least some of the interconnected components and their attributes as represented in a database organized as an object model of the computing system, the object model expressing physical and functional relationships among the interconnected components; and invoke an interpreter with the test references and comparison values to perform the tests defined in the second set of markup-language statements using the comparison values, performance of the tests including the apparatus being caused to: access the database using the references to the at least some of the interconnected components and their attributes to obtain actual values of their attributes; and perform the tests to generate results based on comparisons of the actual values and corresponding ones of the comparison values, the results indicating whether the computing system is compliant with the configuration benchmark. | 1. An apparatus for testing compliance of a computing system, the apparatus comprising a processor and a memory storing executable instructions that in response to execution by the processor cause the apparatus to at least: receive a collection of rules in a first set of markup-language statements, the collection of rules representing a configuration benchmark against which a computing system is to be tested for compliance, the computing system having interconnected components; parse the collection of rules to obtain test references to tests and comparison values used therein, the tests being defined in a second set of markup-language statements, with references to at least some of the interconnected components and their attributes as represented in a database organized as an object model of the computing system, the object model expressing physical and functional relationships among the interconnected components; and invoke an interpreter with the test references and comparison values to perform the tests defined in the second set of markup-language statements using the comparison values, performance of the tests including the apparatus being caused to: access the database using the references to the at least some of the interconnected components and their attributes to obtain actual values of their attributes; and perform the tests to generate results based on comparisons of the actual values and corresponding ones of the comparison values, the results indicating whether the computing system is compliant with the configuration benchmark. 5. The apparatus of claim 1 , wherein the interconnected components include different types of hardware components, and the object model expresses physical and functional relationships among the interconnected components including the different types of hardware components. | 0.822997 |
7,644,057 | 9 | 10 | 9. The computerized text classifier system of claim 7 , wherein the statistical engine is further configured to receive real-time feedback to adapt the statistical information provided to one or more learning nodes of the set of learning nodes. | 9. The computerized text classifier system of claim 7 , wherein the statistical engine is further configured to receive real-time feedback to adapt the statistical information provided to one or more learning nodes of the set of learning nodes. 10. The computerized text classifier system of claim 9 , wherein the real-time feedback comprises a response of a human agent to the relevance of the text to associated categories based upon the set of match scores. | 0.933968 |
7,920,132 | 30 | 32 | 30. The system of claim 1 , where the processor is programmed such that the scoring operation comprises: for each interaction location in the entry sequence, computing a square of a distance from the interaction location to the location occupied by the associated character in the given object; summing all the computed squares; multiplying the sum of the computed squares by a frequency adjustment factor. | 30. The system of claim 1 , where the processor is programmed such that the scoring operation comprises: for each interaction location in the entry sequence, computing a square of a distance from the interaction location to the location occupied by the associated character in the given object; summing all the computed squares; multiplying the sum of the computed squares by a frequency adjustment factor. 32. The system of claim 30 , where the processor is programmed to perform an additional operation comprising, prior to multiplying the sum of the computed squares by the frequency adjustment factor, adding a fixed increment to the sum. | 0.951566 |
7,650,633 | 7 | 12 | 7. A computer program product comprising a computer-useable medium having a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: accessing existing permissions granted to users in an organizational environment; analyzing the permissions to create permission characteristics; performing cladistics analysis on the permission characteristics to determine role perspective relationships between individual users of the organizational environment; and generating a role based access control model for the organizational environment based on the determined role perspective relationships between individual users of the organizational environment. | 7. A computer program product comprising a computer-useable medium having a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: accessing existing permissions granted to users in an organizational environment; analyzing the permissions to create permission characteristics; performing cladistics analysis on the permission characteristics to determine role perspective relationships between individual users of the organizational environment; and generating a role based access control model for the organizational environment based on the determined role perspective relationships between individual users of the organizational environment. 12. The computer program product of claim 7 , wherein generating a role based access control model comprises receiving an indication of one or more modifications to the determined role perspective relationships. | 0.643581 |
8,943,184 | 24 | 25 | 24. One or more non-transitory computer readable storage media encoded with executable instructions that, when executed by a processor, are operable to: receive a trigger for an operation command to be executed on one or more network devices in a network; establish a connection to one or more network devices in the network; generate a command line interface command for execution of the operation command by one or more network devices, a randomly generated string being included at the end of the command line interface command; send the command line interface command over the network in order to invoke the operation command on one or more network devices on the network; receive output of the operation command from one or more devices; detect an end of the operation command output based on the randomly generated string; and parse the operation command output generated by the device using an XML based parser. | 24. One or more non-transitory computer readable storage media encoded with executable instructions that, when executed by a processor, are operable to: receive a trigger for an operation command to be executed on one or more network devices in a network; establish a connection to one or more network devices in the network; generate a command line interface command for execution of the operation command by one or more network devices, a randomly generated string being included at the end of the command line interface command; send the command line interface command over the network in order to invoke the operation command on one or more network devices on the network; receive output of the operation command from one or more devices; detect an end of the operation command output based on the randomly generated string; and parse the operation command output generated by the device using an XML based parser. 25. The non-transitory computer readable storage media of claim 24 , wherein the instructions operable to supply comprise instructions operable to supply the command line interface command, followed by a carriage return followed by the randomly generated string. | 0.791733 |
9,411,617 | 1 | 16 | 1. A method for transforming name synthesized classes of existing classes of an application running on a computer system, in response to dynamic class updates to the existing classes, the method comprising: in response to a run-time event that reloads the name synthesized classes of the existing classes with reloaded name synthesized classes, comparing unique identifiers created for each of the reloaded name synthesized classes with entries in a data structure that include unique identifiers created for previously loaded name synthesized classes, wherein the entries in the data structure include a synthetic name and a replacement synthetic name for each of the reloaded name synthesized classes corresponding to the unique identifiers created for the reloaded name synthesized classes; and in response to finding that a unique identifier for a reloaded name synthesized class matches a unique identifier of an entry in the data structure, replacing occurrences of the synthetic name within bytecode of the reloaded name synthesized class with a corresponding replacement synthetic name in the data structure. | 1. A method for transforming name synthesized classes of existing classes of an application running on a computer system, in response to dynamic class updates to the existing classes, the method comprising: in response to a run-time event that reloads the name synthesized classes of the existing classes with reloaded name synthesized classes, comparing unique identifiers created for each of the reloaded name synthesized classes with entries in a data structure that include unique identifiers created for previously loaded name synthesized classes, wherein the entries in the data structure include a synthetic name and a replacement synthetic name for each of the reloaded name synthesized classes corresponding to the unique identifiers created for the reloaded name synthesized classes; and in response to finding that a unique identifier for a reloaded name synthesized class matches a unique identifier of an entry in the data structure, replacing occurrences of the synthetic name within bytecode of the reloaded name synthesized class with a corresponding replacement synthetic name in the data structure. 16. The method of claim 1 , further comprising leaving bytecode unchanged for classes other than the name synthesized classes during the dynamic class updates to existing classes. | 0.647638 |
7,765,208 | 9 | 20 | 9. A method implemented at a client device having a processor, the method comprising: extracting, at the computing device, a plurality of keywords from a plurality of items on the client device, the extracting comprising: determining a number of instances of each word contained in the plurality of items, determining a total number of words contained in the plurality of items, determining, for each of the plurality of items, a number of instances of each word contained in that item, determining, for each of the plurality of items, a total number of words contained in that item, and determining the plurality of keywords by selecting a number of the words each having a ratio that exceeds a threshold, wherein the ratio is calculated as
ratio =X/Y/a/b where: X is the number of instances of the word contained in a particular item; Y is the total number of words contained in the particular item; a is the total number of instances of the word contained in the plurality of items; and b is the total number of words found in the plurality of items; automatically creating, at the client device, top-level hierarchies from the plurality of keywords, each of the top-level hierarchies having a plurality of keywords positioned at different hierarchical levels, the creating comprising: organizing the plurality of keywords to create a plurality of small hierarchies based on the relative closeness of the plurality of keywords; reducing number of the plurality of small hierarchies to form a predetermined number of top-level hierarchies, the reducing comprising: combining the plurality of small hierarchies to multiple high-level hierarchies each having a subset of the plurality of small hierarchies, the multiple high-level hierarchies having at least a first high-level hierarchy and a second high-level hierarchy; determining that a set of small hierarchies to be combined to the first high-level hierarchy will cause the first high-level hierarchy to include an unbalanced number of small hierarchies; maintaining the first high-level hierarchy balanced by moving the set of small hierarchies to be combined to the second high-level hierarchy, wherein the second high-level hierarchy has less closeness value than the first high-level hierarchy, and wherein the closeness value defines a relevancy of one of the plurality of small hierarchies to another one of the plurality of small hierarchies; and repeating the combining, determining and maintaining until the predetermined number of top-level hierarchies are formed; and categorizing a collection of said items on the client device based on words contained in the respective items according to the created hierarchies for display at the client device. | 9. A method implemented at a client device having a processor, the method comprising: extracting, at the computing device, a plurality of keywords from a plurality of items on the client device, the extracting comprising: determining a number of instances of each word contained in the plurality of items, determining a total number of words contained in the plurality of items, determining, for each of the plurality of items, a number of instances of each word contained in that item, determining, for each of the plurality of items, a total number of words contained in that item, and determining the plurality of keywords by selecting a number of the words each having a ratio that exceeds a threshold, wherein the ratio is calculated as
ratio =X/Y/a/b where: X is the number of instances of the word contained in a particular item; Y is the total number of words contained in the particular item; a is the total number of instances of the word contained in the plurality of items; and b is the total number of words found in the plurality of items; automatically creating, at the client device, top-level hierarchies from the plurality of keywords, each of the top-level hierarchies having a plurality of keywords positioned at different hierarchical levels, the creating comprising: organizing the plurality of keywords to create a plurality of small hierarchies based on the relative closeness of the plurality of keywords; reducing number of the plurality of small hierarchies to form a predetermined number of top-level hierarchies, the reducing comprising: combining the plurality of small hierarchies to multiple high-level hierarchies each having a subset of the plurality of small hierarchies, the multiple high-level hierarchies having at least a first high-level hierarchy and a second high-level hierarchy; determining that a set of small hierarchies to be combined to the first high-level hierarchy will cause the first high-level hierarchy to include an unbalanced number of small hierarchies; maintaining the first high-level hierarchy balanced by moving the set of small hierarchies to be combined to the second high-level hierarchy, wherein the second high-level hierarchy has less closeness value than the first high-level hierarchy, and wherein the closeness value defines a relevancy of one of the plurality of small hierarchies to another one of the plurality of small hierarchies; and repeating the combining, determining and maintaining until the predetermined number of top-level hierarchies are formed; and categorizing a collection of said items on the client device based on words contained in the respective items according to the created hierarchies for display at the client device. 20. One or more computer readable storage media having stored thereon a plurality of executable instructions that, when executed by a computing device having one or more processors, configure the one or more processors to implement the method as recited in claim 9 . | 0.507407 |
9,734,130 | 2 | 7 | 2. The method of claim 1 , wherein the method further comprises: after said matching is performed for one matched element of the matched elements, said processor determining that at least one condition is indicated for the one matched element; responsive to determining that at least one condition is indicated for the one matched element, said processor fulfilling each condition of the at least one condition for the one matched element, wherein the at least one condition is selected from the group consisting of specificity, proximity, both specificity and proximity, both specificity and completeness, and both proximity and completeness, wherein fulfilling specificity for the one matched element comprises identifying an activity associated with the at least one matched element, wherein fulfilling completeness for the one matched element comprises obtaining additional information associated with the at least one matched element, and wherein fulfilling proximity for the one matched element comprises identifying proximity relationships for the one matched element. | 2. The method of claim 1 , wherein the method further comprises: after said matching is performed for one matched element of the matched elements, said processor determining that at least one condition is indicated for the one matched element; responsive to determining that at least one condition is indicated for the one matched element, said processor fulfilling each condition of the at least one condition for the one matched element, wherein the at least one condition is selected from the group consisting of specificity, proximity, both specificity and proximity, both specificity and completeness, and both proximity and completeness, wherein fulfilling specificity for the one matched element comprises identifying an activity associated with the at least one matched element, wherein fulfilling completeness for the one matched element comprises obtaining additional information associated with the at least one matched element, and wherein fulfilling proximity for the one matched element comprises identifying proximity relationships for the one matched element. 7. The method of claim 2 , wherein the at least one condition consists of both proximity and completeness. | 0.961087 |
8,458,115 | 6 | 13 | 6. A method comprising: identifying a travelogue for location-related mining; decomposing the travelogue; representing a decomposed travelogue with a term-document matrix, wherein each word from the travelogue represents one of: a local topic; or a global topic; selecting a candidate set of travelogues based at least on the local topic; ranking the travelogues in the candidate set of travelogues based at least on the local topic; and returning travelogues in the candidate set of travelogues based at least on the ranking. | 6. A method comprising: identifying a travelogue for location-related mining; decomposing the travelogue; representing a decomposed travelogue with a term-document matrix, wherein each word from the travelogue represents one of: a local topic; or a global topic; selecting a candidate set of travelogues based at least on the local topic; ranking the travelogues in the candidate set of travelogues based at least on the local topic; and returning travelogues in the candidate set of travelogues based at least on the ranking. 13. A method as recited in claim 6 , further comprising providing recommendations based at least on the ranking. | 0.929737 |
7,995,823 | 11 | 12 | 11. A computer program product according to claim 7 , the computer readable program code adapted to be executed to implement a method for analysis of an image from a clinical examination of a subject, comprising retrieving a plurality of prior findings of the selected feature from at least one prior analysis of an image, and displaying an element of the prior findings in a graphical display to describe a chronology of the element. | 11. A computer program product according to claim 7 , the computer readable program code adapted to be executed to implement a method for analysis of an image from a clinical examination of a subject, comprising retrieving a plurality of prior findings of the selected feature from at least one prior analysis of an image, and displaying an element of the prior findings in a graphical display to describe a chronology of the element. 12. A computer program product according to claim 11 , the computer readable program code adapted to be executed to implement a method for analysis of an image from a clinical examination of a subject, wherein the element comprises at least one of an area, volume, and a size of the selected feature. | 0.89782 |
8,214,350 | 1 | 4 | 1. A computer implemented method, comprising: identifying, by one or more processors, one or more web page impressions satisfying one or more simple queries, each of the one or more web page impressions associated with a respective impression ID, each web page impression being an instance of a previous presentation of a web page, where each web page has one or more attributes and associated values that describe entities that are targeted by the web page and where identifying one or more web page impressions includes comparing terms of a respective simple query to the one or more attributes and associated values of a given web page; storing the respective impression IDs of the one or more web pages satisfying the one or more simple queries; subsequent to storing the respective impression IDs, receiving a query from a client device; determining a number of criteria included within the query; comparing the number of criteria to a predetermined number; and identifying, by one or more processors, a number of impression IDs for the one or more web pages satisfying the query based on the identified one or more web page impressions satisfying the one or more simple queries, wherein identifying the number of impression IDs for the one or more web pages satisfying the query based on the identified one or more web page impressions satisfying the one or more simple queries occurs if the number of criteria is less than or equal to the predetermined number. | 1. A computer implemented method, comprising: identifying, by one or more processors, one or more web page impressions satisfying one or more simple queries, each of the one or more web page impressions associated with a respective impression ID, each web page impression being an instance of a previous presentation of a web page, where each web page has one or more attributes and associated values that describe entities that are targeted by the web page and where identifying one or more web page impressions includes comparing terms of a respective simple query to the one or more attributes and associated values of a given web page; storing the respective impression IDs of the one or more web pages satisfying the one or more simple queries; subsequent to storing the respective impression IDs, receiving a query from a client device; determining a number of criteria included within the query; comparing the number of criteria to a predetermined number; and identifying, by one or more processors, a number of impression IDs for the one or more web pages satisfying the query based on the identified one or more web page impressions satisfying the one or more simple queries, wherein identifying the number of impression IDs for the one or more web pages satisfying the query based on the identified one or more web page impressions satisfying the one or more simple queries occurs if the number of criteria is less than or equal to the predetermined number. 4. The method of claim 1 , further comprising storing a number of web page impressions satisfying the one or more simple queries. | 0.881215 |
7,624,371 | 7 | 8 | 7. The extensible automation development system of claim 1 further comprising: a custom automation object; wherein the custom automation object is developed by a party other than a party that develops the interface for performing a common command and the interface for responding to a common event. | 7. The extensible automation development system of claim 1 further comprising: a custom automation object; wherein the custom automation object is developed by a party other than a party that develops the interface for performing a common command and the interface for responding to a common event. 8. The extensible automation development system of claim 7 wherein: the custom automation object comprises a handler selected from the group consisting of: a custom handler for performing at least one of the common commands and a custom handler for responding to at least one of the common events. | 0.914606 |
9,798,714 | 9 | 15 | 9. A system for representing a first dictionary for faster searching, the system comprising: an external memory, storing the first dictionary, wherein the first dictionary comprises first textual phrases; a cache memory having a faster access speed than the external memory; and a processor, which is configured to: derive from the first dictionary a second dictionary comprising second textual phrases, wherein the second dictionary has a smaller data size than the first dictionary, and wherein each first textual phrase in the first dictionary corresponds to at least one of the second textual phrases in the second dictionary, and store the second dictionary in the cache memory to represent the first dictionary stored in the external memory. | 9. A system for representing a first dictionary for faster searching, the system comprising: an external memory, storing the first dictionary, wherein the first dictionary comprises first textual phrases; a cache memory having a faster access speed than the external memory; and a processor, which is configured to: derive from the first dictionary a second dictionary comprising second textual phrases, wherein the second dictionary has a smaller data size than the first dictionary, and wherein each first textual phrase in the first dictionary corresponds to at least one of the second textual phrases in the second dictionary, and store the second dictionary in the cache memory to represent the first dictionary stored in the external memory. 15. The method according to claim 9 , wherein a plurality of first textual phrases in the first dictionary correspond to a single second textual phrase in the second dictionary. | 0.650198 |
8,694,593 | 7 | 8 | 7. The computer-implemented method of claim 1 , wherein generating the list of the account references that are relevant to the object reference includes at least one of the users that are explicitly associated with the object reference and the users that would find the object reference interesting. | 7. The computer-implemented method of claim 1 , wherein generating the list of the account references that are relevant to the object reference includes at least one of the users that are explicitly associated with the object reference and the users that would find the object reference interesting. 8. The computer-implemented method of claim 7 , wherein generating the account references of the users that would find the object reference interesting is based at least in part on at least one of a preference of the users, activities on the social network, an interaction of the users with a webpage and a heterogeneous data source. | 0.904145 |
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