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9,239,657 | 1 | 8 | 1. A character input method comprising the steps of: displaying, when a user brings a mouse cursor into contact with a term input box of a web browser or website or clicks the term input box, a character input window in abutment with the term input box, the character input window comprising a first section that includes a plurality of character buttons and a second section that includes a completion button for enabling input of a signal indicative of completion of character entry; entering, when a character button of the plurality of character buttons is clicked, a character corresponding to the clicked character button into the term input box; generating, when the completion button is clicked, an activation signal that causes a search engine associated with the term input box to run is run using as search data the character entered into the term input box; making, when the user locates the mouse cursor on a portion of a screen outside the character input window, the character input window disappear and the portion of the screen outside the character input window remains visible; and displaying an extended term window that displays an extended term including the character entered in the term input box, wherein the extended term window is displayed in contact with a contour of the term input box or the character input window, wherein the character input window is displayed in contact with one side of the contour of the term input box, and the extended term window is displayed in contact with opposite side of the contour of the term input box. | 1. A character input method comprising the steps of: displaying, when a user brings a mouse cursor into contact with a term input box of a web browser or website or clicks the term input box, a character input window in abutment with the term input box, the character input window comprising a first section that includes a plurality of character buttons and a second section that includes a completion button for enabling input of a signal indicative of completion of character entry; entering, when a character button of the plurality of character buttons is clicked, a character corresponding to the clicked character button into the term input box; generating, when the completion button is clicked, an activation signal that causes a search engine associated with the term input box to run is run using as search data the character entered into the term input box; making, when the user locates the mouse cursor on a portion of a screen outside the character input window, the character input window disappear and the portion of the screen outside the character input window remains visible; and displaying an extended term window that displays an extended term including the character entered in the term input box, wherein the extended term window is displayed in contact with a contour of the term input box or the character input window, wherein the character input window is displayed in contact with one side of the contour of the term input box, and the extended term window is displayed in contact with opposite side of the contour of the term input box. 8. The method of claim 1 , wherein the character buttons are arranged within the first section so as to minimize the distance between the second section and a character button, of the displayed character buttons, disposed farthest from the second section. | 0.601563 |
8,311,967 | 1 | 2 | 1. A computer-implemented system comprising: one or more computers; one or more data storage devices coupled to the one or more computers, storing: a predictive model repository of a plurality of trained predictive models, information that describes each of the trained predictive models, which information includes an indication for each trained predictive model of one or more input types of input data that are compatible with the trained predictive model and an output type of a predictive output that can be generated using the trained predictive model, and instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a request from a client-subscriber computing system for access to a trained predictive model from the predictive model repository, which trained predictive model can generate a predictive output in response to receiving input data having one or more input types, wherein the one or more input types can be determined from the request; determining from the information that describes each of the trained predictive models that one or more models included in the predictive model repository match the request from the client-subscriber computing system, wherein determining a match is based at least in part on a comparison of the one or more input types determined from the request to input types included in the information that describes the trained predictive models; and providing access to at least one of the one or more models to the client-subscriber computing system; wherein the one or more models that match the request are models that were trained using training data provided by a computing system other than the client-subscriber computing system. | 1. A computer-implemented system comprising: one or more computers; one or more data storage devices coupled to the one or more computers, storing: a predictive model repository of a plurality of trained predictive models, information that describes each of the trained predictive models, which information includes an indication for each trained predictive model of one or more input types of input data that are compatible with the trained predictive model and an output type of a predictive output that can be generated using the trained predictive model, and instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a request from a client-subscriber computing system for access to a trained predictive model from the predictive model repository, which trained predictive model can generate a predictive output in response to receiving input data having one or more input types, wherein the one or more input types can be determined from the request; determining from the information that describes each of the trained predictive models that one or more models included in the predictive model repository match the request from the client-subscriber computing system, wherein determining a match is based at least in part on a comparison of the one or more input types determined from the request to input types included in the information that describes the trained predictive models; and providing access to at least one of the one or more models to the client-subscriber computing system; wherein the one or more models that match the request are models that were trained using training data provided by a computing system other than the client-subscriber computing system. 2. The system of claim 1 , the operations further comprising: determining an output type for predictive output for the client-subscriber computing system, wherein: if the output type is included in the request, then determining the output type comprises receiving the output type in the request; and if the output type is not included in the request, then determining the output type comprises determining from the information that describes each of the trained predictive models that one or more models included in the predictive model repository are compatible with the one or more input types determined from the request to input types and that the one or more models can generate output of one or more output types, and selecting the output type from the one or more output types. | 0.500637 |
8,719,701 | 1 | 2 | 1. A machine readable medium storing a program which when executed by at least one processing unit analyzes a document that comprises a plurality of words, each word comprising an associated set of glyphs, each glyph having location coordinates, the program comprising sets of instructions for: identifying a group of words aligned in a first direction based on the location coordinates of a particular glyph in each of the words in the group of aligned words; based on the identified group of aligned words, defining an alignment element for the particular glyphs at a particular location in the first direction, wherein the alignment element that indicates a particular alignment for a plurality of text lines containing the group of aligned words; removing particular locations from the alignment element in a second direction based on an analysis of the group of aligned words, wherein each particular location of the alignment element corresponds to a particular text line; and defining a structured document based on the glyphs and remaining locations of the defined alignment element. | 1. A machine readable medium storing a program which when executed by at least one processing unit analyzes a document that comprises a plurality of words, each word comprising an associated set of glyphs, each glyph having location coordinates, the program comprising sets of instructions for: identifying a group of words aligned in a first direction based on the location coordinates of a particular glyph in each of the words in the group of aligned words; based on the identified group of aligned words, defining an alignment element for the particular glyphs at a particular location in the first direction, wherein the alignment element that indicates a particular alignment for a plurality of text lines containing the group of aligned words; removing particular locations from the alignment element in a second direction based on an analysis of the group of aligned words, wherein each particular location of the alignment element corresponds to a particular text line; and defining a structured document based on the glyphs and remaining locations of the defined alignment element. 2. The machine readable medium of claim 1 , wherein the program further comprises a set of instructions for defining at least one region of empty space between a pair of alignment elements, wherein the structured document is further defined based on the region of empty space. | 0.669065 |
9,293,061 | 1 | 6 | 1. A method for creating a mnemonic experience for a user, which comprises: selecting a concentration of information to be remembered; gathering information on said concentration, said information being intended to be remembered by the user; providing a building; placing a display to be observed in said building, said display teaching said information when observed by the user; providing a character to interact with the user and said display, said character being contextually related to said display; interacting said character with the user with while the user observes said display; gathering further information on said concentration; determining an importance of said information relative to an importance of said further information; and not creating a display of said further information when said importance of said further information is less than the importance of said piece of information. | 1. A method for creating a mnemonic experience for a user, which comprises: selecting a concentration of information to be remembered; gathering information on said concentration, said information being intended to be remembered by the user; providing a building; placing a display to be observed in said building, said display teaching said information when observed by the user; providing a character to interact with the user and said display, said character being contextually related to said display; interacting said character with the user with while the user observes said display; gathering further information on said concentration; determining an importance of said information relative to an importance of said further information; and not creating a display of said further information when said importance of said further information is less than the importance of said piece of information. 6. The method according to claim 1 , which further comprises incorporating as many senses as possible in said display. | 0.920805 |
8,626,742 | 1 | 3 | 1. A method of processing correlated keywords, the method comprising: providing a web page having a first input box and an embedded window object that provides a frame for a second input box and a keyword list container; receiving a primary keyword inputted by a user into the first input box of the web page; establishing a link between the embedded window object in the web page and a server and obtaining, from the server via the link, candidate related keywords of the primary keyword; creating a keyword list to present the candidate related keywords in the web page by the embedded window object; presenting, in the keyword list container of the frame of the embedded window object in the web page, the keyword list to the user; obtaining at least one related keyword from the keyword list, wherein the at least one related keyword corresponds to a respective candidate related keyword selected by the user; adding the at least one related keyword into the second input box of the frame of the embedded window object in the web page; and presenting, the second input box of the frame of the embedded window object in the web page to the user, wherein the first input box with the primary keyword therein, the second input box with the at least one related keyword therein and the keyword list container with the candidate related keywords therein are concurrently presented, and the concurrent presentation further comprises determining whether a number of the at least one related keyword in the second input box being greater than or equal to a predetermined threshold, and closing the keyword list if affirmative. | 1. A method of processing correlated keywords, the method comprising: providing a web page having a first input box and an embedded window object that provides a frame for a second input box and a keyword list container; receiving a primary keyword inputted by a user into the first input box of the web page; establishing a link between the embedded window object in the web page and a server and obtaining, from the server via the link, candidate related keywords of the primary keyword; creating a keyword list to present the candidate related keywords in the web page by the embedded window object; presenting, in the keyword list container of the frame of the embedded window object in the web page, the keyword list to the user; obtaining at least one related keyword from the keyword list, wherein the at least one related keyword corresponds to a respective candidate related keyword selected by the user; adding the at least one related keyword into the second input box of the frame of the embedded window object in the web page; and presenting, the second input box of the frame of the embedded window object in the web page to the user, wherein the first input box with the primary keyword therein, the second input box with the at least one related keyword therein and the keyword list container with the candidate related keywords therein are concurrently presented, and the concurrent presentation further comprises determining whether a number of the at least one related keyword in the second input box being greater than or equal to a predetermined threshold, and closing the keyword list if affirmative. 3. The method as recited in claim 1 , the method further comprising: determining whether the at least one related keyword selected by the user is a duplicate of a related keyword already in the second input box, and not adding the selected at least one related keyword into the second input box if affirmative. | 0.785615 |
9,495,460 | 6 | 7 | 6. A method as claimed in claim 1 , which further comprises selecting a subset of the received results lists from which to form the complete results list where that subset comprises less than all of the received results lists. | 6. A method as claimed in claim 1 , which further comprises selecting a subset of the received results lists from which to form the complete results list where that subset comprises less than all of the received results lists. 7. A method as claimed in claim 6 , which comprises making the selection at least on the basis of probability values obtained from the merging model. | 0.953727 |
8,015,051 | 1 | 2 | 1. An automated method comprising: storing, using a computer processor, semantic information in a database, the semantic information being related to steps of business processes and describing the steps of the business processes in natural language expressions, the semantic information including functionality metadata, service metadata and instance descriptor metadata, wherein the functionality metadata provides a semantic context containing various levels of specificity and arranged in a hierarchical structure, the service metadata includes technical aspects relating to services implemented in software applications, and the instance descriptor metadata contains data transformation information relating to a transform of data between software applications and cross-references between the functionality metadata and runtime instances of the services; storing, using the computer processor, syntactic information for the services in the database, the syntactic information being cross-referenced to semantic information and related to the software applications each implementing a step of the business processes; comparing, by the computer processor, user input relating to business process with the semantic information and syntactic information, and associations therebetween on a match between the input and the semantic information, identifying, by the computer processor, corresponding syntactic information based on the associations; and from the corresponding syntactic information, identifying, by the computer processor, a software application that implements the step of the business process specified in the user input; identifying, by the computer processor, the data transformation information corresponding to the identified software application; and generating, by the computer processor, an integrated sequence of runtime instances of identified software applications to implement the business process by repeating the above comparing, identifying corresponding syntactic information and identifying a software application steps, wherein each runtime instance in the sequence implements a respective step of the business process and communicates with adjacent runtime instances via adapters created based on the identified data transformation information. | 1. An automated method comprising: storing, using a computer processor, semantic information in a database, the semantic information being related to steps of business processes and describing the steps of the business processes in natural language expressions, the semantic information including functionality metadata, service metadata and instance descriptor metadata, wherein the functionality metadata provides a semantic context containing various levels of specificity and arranged in a hierarchical structure, the service metadata includes technical aspects relating to services implemented in software applications, and the instance descriptor metadata contains data transformation information relating to a transform of data between software applications and cross-references between the functionality metadata and runtime instances of the services; storing, using the computer processor, syntactic information for the services in the database, the syntactic information being cross-referenced to semantic information and related to the software applications each implementing a step of the business processes; comparing, by the computer processor, user input relating to business process with the semantic information and syntactic information, and associations therebetween on a match between the input and the semantic information, identifying, by the computer processor, corresponding syntactic information based on the associations; and from the corresponding syntactic information, identifying, by the computer processor, a software application that implements the step of the business process specified in the user input; identifying, by the computer processor, the data transformation information corresponding to the identified software application; and generating, by the computer processor, an integrated sequence of runtime instances of identified software applications to implement the business process by repeating the above comparing, identifying corresponding syntactic information and identifying a software application steps, wherein each runtime instance in the sequence implements a respective step of the business process and communicates with adjacent runtime instances via adapters created based on the identified data transformation information. 2. The method of claim 1 , further comprising presenting results including the identified software application to a user. | 0.678191 |
8,619,090 | 10 | 17 | 10. A non-transitory computer-readable medium for storing instructions, the instructions comprising: one or more instructions that, when executed by a processor of a device, cause the processor to: receive text that includes data values, convert the text to identify data types associated with the data values, generate, based on the data values and the data types, a graphical representation of the text that includes data cells corresponding to the data values, provide the graphical representation for display, receive one or more selections of one or more data cells in the graphical representation, store the one or more selections as a selection history, the selection history storing a plurality of selections, and the plurality of selections including the one or more selections and one or more other selections received prior to receiving the one or more selections, provide the selection history for display, receive a selection of a particular selection, of the plurality of selections, from the selection history, identify one or more data cells associated with the particular selection in the graphical representation, receive an instruction to import the particular selection to a technical computing environment, highlight, based on the instruction, only the one or more data cells associated with the particular selection in the graphical representation, the one or more data cells being associated with the data types, generate a data container associated with the technical computing environment, based on the particular selection and the data types associated with the one or more data cells of the particular selection, and provide the data container to the technical computing environment. | 10. A non-transitory computer-readable medium for storing instructions, the instructions comprising: one or more instructions that, when executed by a processor of a device, cause the processor to: receive text that includes data values, convert the text to identify data types associated with the data values, generate, based on the data values and the data types, a graphical representation of the text that includes data cells corresponding to the data values, provide the graphical representation for display, receive one or more selections of one or more data cells in the graphical representation, store the one or more selections as a selection history, the selection history storing a plurality of selections, and the plurality of selections including the one or more selections and one or more other selections received prior to receiving the one or more selections, provide the selection history for display, receive a selection of a particular selection, of the plurality of selections, from the selection history, identify one or more data cells associated with the particular selection in the graphical representation, receive an instruction to import the particular selection to a technical computing environment, highlight, based on the instruction, only the one or more data cells associated with the particular selection in the graphical representation, the one or more data cells being associated with the data types, generate a data container associated with the technical computing environment, based on the particular selection and the data types associated with the one or more data cells of the particular selection, and provide the data container to the technical computing environment. 17. The non-transitory computer-readable medium of claim 10 , where the instructions further comprise: one or more instructions that, when executed by the processor, cause the processor to: detect a portion of the text that is being displayed, parse only the detected portion of the text, generate a user interface that depicts the parsed detected portion of the text, and provide the user interface for display. | 0.819298 |
10,115,215 | 18 | 30 | 18. A system comprising: a computing device comprising: a memory configured to store instructions; and a processor to execute the instructions to perform operations comprising: attaining data representing features of a font capable of representing one or more glyphs; and determining a rating for pairing the font and at least one other font using a machine learning system and the data representing the features of the font, wherein at least one of the features or at least one category of a set of categories is identified to represent the font by the machine learning system using the features of the font, and wherein the machine learning system produces a vector of numerical values, each numerical value represents one of the features or one of the categories in the set of categories. | 18. A system comprising: a computing device comprising: a memory configured to store instructions; and a processor to execute the instructions to perform operations comprising: attaining data representing features of a font capable of representing one or more glyphs; and determining a rating for pairing the font and at least one other font using a machine learning system and the data representing the features of the font, wherein at least one of the features or at least one category of a set of categories is identified to represent the font by the machine learning system using the features of the font, and wherein the machine learning system produces a vector of numerical values, each numerical value represents one of the features or one of the categories in the set of categories. 30. The system of claim 18 , wherein determining the rating for pairing the font and the at least one other font uses a ruling provided by the machine learning system. | 0.652083 |
8,041,746 | 7 | 8 | 7. The method of claim 1 , wherein generating the new name for each first data element definition comprises: receiving a human-understandable description of a specific first data element definition for which a new name is to be created, the new name complying with a predefined name format that is same as a predefined name format of the second names; identifying a noun phrase and a verb phrase in the human-understandable description; and generating the new name using a first noun obtained from the noun phrase and a second noun obtained from the verb phrase. | 7. The method of claim 1 , wherein generating the new name for each first data element definition comprises: receiving a human-understandable description of a specific first data element definition for which a new name is to be created, the new name complying with a predefined name format that is same as a predefined name format of the second names; identifying a noun phrase and a verb phrase in the human-understandable description; and generating the new name using a first noun obtained from the noun phrase and a second noun obtained from the verb phrase. 8. The method of claim 7 , wherein identifying the noun phrase and the verb phrase includes generating a hierarchical tree for the human-understandable description. | 0.964942 |
8,311,838 | 18 | 19 | 18. A method for defining input windows to associate with provided prompts, comprising: at an electronic device with at least one processor and memory: identifying a plurality of prompts to provide in sequence, wherein each prompt is associated with a distinct electronic device operation; defining an offset relative to at least one of a start time and an end time for providing each of the plurality of prompts; and determining, for each of the plurality of prompts, an input window defined by an initial time and a final time for determining which provided prompt of the plurality of prompts to associate with a received voice input, wherein at least one of the initial time and the final time are offset from the start time and end time by the defined offset. | 18. A method for defining input windows to associate with provided prompts, comprising: at an electronic device with at least one processor and memory: identifying a plurality of prompts to provide in sequence, wherein each prompt is associated with a distinct electronic device operation; defining an offset relative to at least one of a start time and an end time for providing each of the plurality of prompts; and determining, for each of the plurality of prompts, an input window defined by an initial time and a final time for determining which provided prompt of the plurality of prompts to associate with a received voice input, wherein at least one of the initial time and the final time are offset from the start time and end time by the defined offset. 19. The method of claim 18 , further comprising: determining the importance of each prompt; and varying the defined offset for each prompt based on the importance of the prompt. | 0.791765 |
8,239,199 | 1 | 2 | 1. A method comprising: identifying, electronically, a first syllable in a first audio of a first word and a second syllable in a second audio of a second word, the first syllable having a first set of properties and the second syllable having a second set of properties; detecting, electronically, the first syllable in a first instance of the first word in a file having audio, the first syllable in the first instance of the first word having a third set of properties; determining, electronically, one or more transformations for transforming the first set of properties of the first syllable in the first audio to the third set of properties in the first syllable in the first instance of the first word; applying, electronically, the one or more transformations to the second set of properties of the second syllable to yield a transformed second syllable; and replacing, electronically, the first syllable in the first instance of the first word with the transformed second syllable in the file having audio. | 1. A method comprising: identifying, electronically, a first syllable in a first audio of a first word and a second syllable in a second audio of a second word, the first syllable having a first set of properties and the second syllable having a second set of properties; detecting, electronically, the first syllable in a first instance of the first word in a file having audio, the first syllable in the first instance of the first word having a third set of properties; determining, electronically, one or more transformations for transforming the first set of properties of the first syllable in the first audio to the third set of properties in the first syllable in the first instance of the first word; applying, electronically, the one or more transformations to the second set of properties of the second syllable to yield a transformed second syllable; and replacing, electronically, the first syllable in the first instance of the first word with the transformed second syllable in the file having audio. 2. The method as claimed in claim 1 , wherein each set of properties comprises at least one of: amplitude; frequency; and time duration. | 0.905556 |
8,838,617 | 1 | 4 | 1. A method for searching for recommended music using emotional information of music, the method being performed by a music search apparatus capable of searching for recommended music using the emotional information of music, the method comprising: inputting a search condition that is used to search for recommended music; searching a music emotion database (DB), which stores information about emotional values including valence values and arousal values of respective pieces of music, for emotional value information corresponding to the input search condition; retrieving the emotional value information from the input search condition, the emotional value information including a valence value and an arousal value; extracting a combination of emotion ranks corresponding to the retrieved emotional value information by using an emotion model that includes information about mixed emotions corresponding to valence values and arousal values; searching the music emotion DB for music information corresponding to the extracted emotion ranks combination; and outputting a recommended music list including music information that corresponds to the extracted emotion ranks combination. | 1. A method for searching for recommended music using emotional information of music, the method being performed by a music search apparatus capable of searching for recommended music using the emotional information of music, the method comprising: inputting a search condition that is used to search for recommended music; searching a music emotion database (DB), which stores information about emotional values including valence values and arousal values of respective pieces of music, for emotional value information corresponding to the input search condition; retrieving the emotional value information from the input search condition, the emotional value information including a valence value and an arousal value; extracting a combination of emotion ranks corresponding to the retrieved emotional value information by using an emotion model that includes information about mixed emotions corresponding to valence values and arousal values; searching the music emotion DB for music information corresponding to the extracted emotion ranks combination; and outputting a recommended music list including music information that corresponds to the extracted emotion ranks combination. 4. The method of claim 1 , wherein extracting emotional value information from the input search condition includes extracting an emotion rank combination of emotions contained in an emotional keyword when the input search condition is an emotional keyword. | 0.801242 |
9,141,346 | 5 | 7 | 5. The method of claim 1 , further comprising storing the grouping relationship in an application model datastore, along with alignment information setting forth an alignment relationship between the widgets in each determined group. | 5. The method of claim 1 , further comprising storing the grouping relationship in an application model datastore, along with alignment information setting forth an alignment relationship between the widgets in each determined group. 7. The method of claim 5 , further comprising transmitting an access control list to the remote computing device, the access control list including one or more identifiers associated with users authorized to access the group of widgets and the included alignment information. | 0.947013 |
5,404,319 | 19 | 20 | 19. The translator of claim 17 wherein said analysis module (34) includes a behavior specific normalizer (32b) for determining a specific character of the components from the behavior description thereof from among a predetermined character set for converting the behavior to a simplified normal form. | 19. The translator of claim 17 wherein said analysis module (34) includes a behavior specific normalizer (32b) for determining a specific character of the components from the behavior description thereof from among a predetermined character set for converting the behavior to a simplified normal form. 20. The translator of claim 19 wherein said predetermined character set is taken from the group consisting of: a set of nonlinear algebraic and differential equations with respect to time; a Laplace transform expressed as the product of rational polynomials in S; a Z domain transform expressed as the product of rational polynomials in Z; a set of poles and zeros in S representing the roots of the numerator and denominator of the associated transfer function in S; a set of poles and zeros in Z representing the roots of the numerator and denominator of the associated transfer function in Z; and a frequency response expressed as a list of frequency, magnitude and phase triplets. | 0.801278 |
9,036,083 | 7 | 9 | 7. The method of claim 4 , further comprising providing the additional information to a software application on a media content device. | 7. The method of claim 4 , further comprising providing the additional information to a software application on a media content device. 9. The method of claim 7 , wherein the media content device comprises one of a television, a laptop computer, a desktop computer, a tablet computer, and a smartphone. | 0.944924 |
9,417,758 | 13 | 14 | 13. A computer implemented method executed on a device that includes a processor to execute a player application, the method comprises: receiving by the player application information content from one or more user selected resources; determining by the player application formats of the information content from the one or more user selected resources; determining by the player application which of the one or more user selected resources are not in a specified mark-up language format; converting by the player application content from the one or more user selected resources that are not in the specified mark-up language format into the specified mark-up language format: parsing and decoding by the player application the converted information content into code functions and data elements to provide a dataset; loading by the player application the dataset and the code functions into a player window to convert the dataset into produced visual playable content items; storing by the player application the produced visual playable content items in a queue of visual playable content items; and rendering by the player application user selected ones of the visual playable content items in a player window produced by the player application to cause the selected ones of the visual playable content items to be displayed in the player window in a sequence for a period of time and regularly repeated, with the sequence and with the period of time of the sequence, the selection of the queued visual playable content items, and a repetition rate of the sequence being based on user defined parameters. | 13. A computer implemented method executed on a device that includes a processor to execute a player application, the method comprises: receiving by the player application information content from one or more user selected resources; determining by the player application formats of the information content from the one or more user selected resources; determining by the player application which of the one or more user selected resources are not in a specified mark-up language format; converting by the player application content from the one or more user selected resources that are not in the specified mark-up language format into the specified mark-up language format: parsing and decoding by the player application the converted information content into code functions and data elements to provide a dataset; loading by the player application the dataset and the code functions into a player window to convert the dataset into produced visual playable content items; storing by the player application the produced visual playable content items in a queue of visual playable content items; and rendering by the player application user selected ones of the visual playable content items in a player window produced by the player application to cause the selected ones of the visual playable content items to be displayed in the player window in a sequence for a period of time and regularly repeated, with the sequence and with the period of time of the sequence, the selection of the queued visual playable content items, and a repetition rate of the sequence being based on user defined parameters. 14. The method of claim 13 wherein the one or more resources includes feeds, and the method further comprises: converting by the player application the information content from the feeds to produce ad-hoc collections of the visual playable content items by: collecting visual playable contend produced from the transformed information content and received, non-transformed information content; and storing the collected visual playable content items in a computer storage as an ad-hoc collection of the visual playable content items. | 0.687573 |
8,151,254 | 2 | 9 | 2. A compilation method for translating a source program into a machine language program, using operation definition information in which an operation that corresponds to a machine language instruction for a target processor is defined in a format of a function invocation, the compilation method comprising: a parser step of analyzing, using a processor, the source program; and a code generation step of generating machine language instructions including first instructions and second instructions from the analyzed source program which includes operations defined in the operation definition information, the first instructions corresponding to the operations, the second instructions not corresponding to the operations, wherein the code generation step includes a removing sub-step of removing redundancy between the first instructions and the second instructions. | 2. A compilation method for translating a source program into a machine language program, using operation definition information in which an operation that corresponds to a machine language instruction for a target processor is defined in a format of a function invocation, the compilation method comprising: a parser step of analyzing, using a processor, the source program; and a code generation step of generating machine language instructions including first instructions and second instructions from the analyzed source program which includes operations defined in the operation definition information, the first instructions corresponding to the operations, the second instructions not corresponding to the operations, wherein the code generation step includes a removing sub-step of removing redundancy between the first instructions and the second instructions. 9. The compilation method according to claim 2 , wherein the operations include a function that returns a zero-expanded value based on bits extracted at designated bit positions from input data, and one of the first instructions takes out bits at the bit positions designated by a second register from a value stored in a first register, zero-expands said bits and stores the zero-expanded bits in a third register. | 0.525172 |
8,705,707 | 1 | 2 | 1. A method performed by at least one processor of a communication device, the method comprising: determining, by the communication device, that a call has been answered, missed, or terminated by the communication device; generating, at a graphical user interface associated with the communication device, an indication of the call being answered, missed, or terminated; responsive to determining that the call has been answered, missed, or terminated by the communication device, automatically: determining, by the communication device, one or more contextual identifiers associated with the call, wherein the one or more contextual identifiers are based on a geographic location of the communication device at a time of the call, and storing the one or more contextual identifiers in association with the indication of the call in at least one data structure that includes other contextual identifiers associated with other indications of other calls, wherein the one or more contextual identifiers and the other contextual identifiers included in the at least one data structure are searchable; and determining that the one or more contextual identifiers satisfy a search query based at least in part on a second input received at the graphical user interface, wherein the one or more contextual identifiers and the indication of the call are determined in response to the search query. | 1. A method performed by at least one processor of a communication device, the method comprising: determining, by the communication device, that a call has been answered, missed, or terminated by the communication device; generating, at a graphical user interface associated with the communication device, an indication of the call being answered, missed, or terminated; responsive to determining that the call has been answered, missed, or terminated by the communication device, automatically: determining, by the communication device, one or more contextual identifiers associated with the call, wherein the one or more contextual identifiers are based on a geographic location of the communication device at a time of the call, and storing the one or more contextual identifiers in association with the indication of the call in at least one data structure that includes other contextual identifiers associated with other indications of other calls, wherein the one or more contextual identifiers and the other contextual identifiers included in the at least one data structure are searchable; and determining that the one or more contextual identifiers satisfy a search query based at least in part on a second input received at the graphical user interface, wherein the one or more contextual identifiers and the indication of the call are determined in response to the search query. 2. The method of claim 1 , wherein at least one contextual identifier in the at least one data structure is determined by the communication device from a first input that includes at least one of image data, audio data, and textual data. | 0.797089 |
9,031,828 | 1 | 21 | 1. A computer-implemented method comprising: receiving, using one or more processors, an initial message of a first user in a first language from a first chat client system; querying, using the one or more processors, a data store for a first corresponding message in a second language, the first corresponding message being based on the initial message in the first language; determining, using the one or more processors, that the data store does not include the first corresponding message and, based thereon: selecting, using the one or more processors, an order for a plurality of different transformation modules based on the initial message, wherein each transformation module accepts as respective input a portion of a message and provides as respective output a transformed version of the respective input in the first language, and wherein the order is selected based on at least one of (i) precedence, (ii) a priority of transformation operations, (iii) a transformation operation that is most likely to generate a transformed message suitable for translation, and (iv) a transformation operation that generates a most formal transformed message; for each of one or more portions of the initial message, providing, using the one or more processors, the portion as input to a first transformation module in the order and providing the respective output of each transformation module as the respective input to a following transformation module in the order; selecting, using the one or more processors, the respective output of the last transformation module in the order as the transformed message in the first language; and querying, using the one or more processors, the data store for a second corresponding message in the second language, the second corresponding message being based on the transformed message in the first language. | 1. A computer-implemented method comprising: receiving, using one or more processors, an initial message of a first user in a first language from a first chat client system; querying, using the one or more processors, a data store for a first corresponding message in a second language, the first corresponding message being based on the initial message in the first language; determining, using the one or more processors, that the data store does not include the first corresponding message and, based thereon: selecting, using the one or more processors, an order for a plurality of different transformation modules based on the initial message, wherein each transformation module accepts as respective input a portion of a message and provides as respective output a transformed version of the respective input in the first language, and wherein the order is selected based on at least one of (i) precedence, (ii) a priority of transformation operations, (iii) a transformation operation that is most likely to generate a transformed message suitable for translation, and (iv) a transformation operation that generates a most formal transformed message; for each of one or more portions of the initial message, providing, using the one or more processors, the portion as input to a first transformation module in the order and providing the respective output of each transformation module as the respective input to a following transformation module in the order; selecting, using the one or more processors, the respective output of the last transformation module in the order as the transformed message in the first language; and querying, using the one or more processors, the data store for a second corresponding message in the second language, the second corresponding message being based on the transformed message in the first language. 21. The method of claim 1 , further comprising transforming at least a portion of the second corresponding message to at least one of chatspeak, an abbreviation, an acronym, a colloquialism, and profanity, in the second language. | 0.896847 |
8,417,691 | 1 | 2 | 1. A method, comprising: collecting, with a processor of a computer, client information for client applications running on a client computer, wherein the client information includes a client application identifier for each client application that issues queries to a database along with text of each of the queries that the client application issues; collecting, with the processor of the computer, database monitoring information that includes the text of each of the queries issued against the database and performance information for each of the queries, wherein the database monitoring information does not include the client application identifier of each client application that issues the queries; matching, with the processor of the computer, the text of the queries in the client information and the text of the queries in the database monitoring information to obtain combined information that provides the client application identifier and the performance information for each of the queries; identifying, with the processor of the computer, a problem query using the combined information; identifying, with the processor of the computer, multiple client applications that issued the problem query using the combined information; and in response to determining that a comparison window can be expanded, wherein the comparison window represents a number of queries that were issued in a particular order and include the problem query being compared to the combined information, expanding the comparison window; and attempting to identify a single client application that issued the problem query using the expanded comparison window. | 1. A method, comprising: collecting, with a processor of a computer, client information for client applications running on a client computer, wherein the client information includes a client application identifier for each client application that issues queries to a database along with text of each of the queries that the client application issues; collecting, with the processor of the computer, database monitoring information that includes the text of each of the queries issued against the database and performance information for each of the queries, wherein the database monitoring information does not include the client application identifier of each client application that issues the queries; matching, with the processor of the computer, the text of the queries in the client information and the text of the queries in the database monitoring information to obtain combined information that provides the client application identifier and the performance information for each of the queries; identifying, with the processor of the computer, a problem query using the combined information; identifying, with the processor of the computer, multiple client applications that issued the problem query using the combined information; and in response to determining that a comparison window can be expanded, wherein the comparison window represents a number of queries that were issued in a particular order and include the problem query being compared to the combined information, expanding the comparison window; and attempting to identify a single client application that issued the problem query using the expanded comparison window. 2. The method of claim 1 , further comprising: in response to determining that the comparison window can not be expanded, generating a report with information indicating that there is an ambiguity regarding which client application issued the problem query. | 0.642061 |
9,384,226 | 22 | 24 | 22. A computer-implemented method performed at a user computer comprising one or more processors, the method comprising: obtaining, by at least one of the processors, a search query to search user's content items hosted by an online content management service; using, by at least one of the processors, the search query to identify in a local index at the user computer a first set of one or more of the user's hosted content items that satisfy the search query; displaying, by at least one of the processors, in a graphical user interface at the user computer, for at least a first content item in the first set of one or more of the user's hosted content items that satisfy the search query, a first search answer summary for the first content item; sending, by at least one of the processors, the search query over a communications network to the online content management service; receiving, by at least one of the processors, over the communications network from the online content management service, one or more remote answers to the search query, the one or more remote answers corresponding to a second set of one or more of the user's hosted content items identified by the online content management service, using a remote index at the online content management service, as satisfying the search query; updating, by at least one of the processors, the graphical user interface at the user computer to display, for at least a second content item in the second set of one or more content items of the user's hosted content items that satisfy the search query, a second search answer summary for the second content item; wherein a version of the second content item is stored at the user computer at the time the search query is obtained; wherein the second search answer summary indicates that the version of the second content item stored at the user computer is older than a version of the second content item hosted by the online content management service; and wherein, after the updating, the graphical user interface at the user computer displays at least both the first search answer summary for the first content item and the second search answer summary for the second content item. | 22. A computer-implemented method performed at a user computer comprising one or more processors, the method comprising: obtaining, by at least one of the processors, a search query to search user's content items hosted by an online content management service; using, by at least one of the processors, the search query to identify in a local index at the user computer a first set of one or more of the user's hosted content items that satisfy the search query; displaying, by at least one of the processors, in a graphical user interface at the user computer, for at least a first content item in the first set of one or more of the user's hosted content items that satisfy the search query, a first search answer summary for the first content item; sending, by at least one of the processors, the search query over a communications network to the online content management service; receiving, by at least one of the processors, over the communications network from the online content management service, one or more remote answers to the search query, the one or more remote answers corresponding to a second set of one or more of the user's hosted content items identified by the online content management service, using a remote index at the online content management service, as satisfying the search query; updating, by at least one of the processors, the graphical user interface at the user computer to display, for at least a second content item in the second set of one or more content items of the user's hosted content items that satisfy the search query, a second search answer summary for the second content item; wherein a version of the second content item is stored at the user computer at the time the search query is obtained; wherein the second search answer summary indicates that the version of the second content item stored at the user computer is older than a version of the second content item hosted by the online content management service; and wherein, after the updating, the graphical user interface at the user computer displays at least both the first search answer summary for the first content item and the second search answer summary for the second content item. 24. The method of claim 22 , wherein the first content item is stored at the user computer at the time the search query is obtained; and wherein the first search answer summary for the first content item indicates that the first content item is stored at the user computer. | 0.776961 |
6,069,939 | 4 | 5 | 4. The method of claim 1, wherein said determining geographic location step includes the step of analyzing received dialed digits. | 4. The method of claim 1, wherein said determining geographic location step includes the step of analyzing received dialed digits. 5. The method of claim 4, wherein said received dialed digits include digits that alert a network that a calling party desires to make an international call, digits representing a dialed country code, and digits representing said called party's phone number. | 0.80031 |
8,542,950 | 15 | 22 | 15. A computer system comprising: a memory for storing computer-executable instructions; and a processor for executing the instructions, the instructions for: receiving a plurality of candidate images; using a learned probabilistic composition model to divide each candidate image in the plurality of candidate images into a most probable rectangular object region and a background region, wherein the most probable rectangular object region has a maximal composition score from possible composition scores computed according to the composition model for possible divisions of the candidate image into object and background regions, each possible composition score is based upon at least one image feature cue computed over the object and background regions, and the composition model is trained on a set of images independent of the plurality of candidate images; ranking the plurality of candidate images according to the maximal composition score of the most probable rectangular object region of each image determined using the learned probabilistic composition model; removing non-discriminative images from the plurality of candidate images; clustering a plurality of highest-ranked images from the plurality of candidate images ranked according to the maximal composition score of the most probable rectangular object region of each image determined using the learned probabilistic composition model to form a plurality of clusters, wherein each cluster includes a plurality of images selected from the plurality of highest-ranked images and having similar object regions according to a feature match score; selecting a representative image from each cluster as an iconic image representative of an object category; and causing display of the iconic image. | 15. A computer system comprising: a memory for storing computer-executable instructions; and a processor for executing the instructions, the instructions for: receiving a plurality of candidate images; using a learned probabilistic composition model to divide each candidate image in the plurality of candidate images into a most probable rectangular object region and a background region, wherein the most probable rectangular object region has a maximal composition score from possible composition scores computed according to the composition model for possible divisions of the candidate image into object and background regions, each possible composition score is based upon at least one image feature cue computed over the object and background regions, and the composition model is trained on a set of images independent of the plurality of candidate images; ranking the plurality of candidate images according to the maximal composition score of the most probable rectangular object region of each image determined using the learned probabilistic composition model; removing non-discriminative images from the plurality of candidate images; clustering a plurality of highest-ranked images from the plurality of candidate images ranked according to the maximal composition score of the most probable rectangular object region of each image determined using the learned probabilistic composition model to form a plurality of clusters, wherein each cluster includes a plurality of images selected from the plurality of highest-ranked images and having similar object regions according to a feature match score; selecting a representative image from each cluster as an iconic image representative of an object category; and causing display of the iconic image. 22. The system of claim 15 , wherein the composition model is trained using a plurality of hand-labeled training images, wherein a correct layout and an incorrect layout are labeled for each training image. | 0.840804 |
7,814,404 | 3 | 4 | 3. The method of claim 2 , wherein the events are selected from the group comprising screen navigation between screens of the component based application, data persistence on the device, incoming and outgoing messages with respect to the device, and data transfer between screens of the component based application. | 3. The method of claim 2 , wherein the events are selected from the group comprising screen navigation between screens of the component based application, data persistence on the device, incoming and outgoing messages with respect to the device, and data transfer between screens of the component based application. 4. The method of claim 3 , wherein the messages are selected from the group comprising synchronous messages and asynchronous messages. | 0.960378 |
8,756,561 | 17 | 18 | 17. A computing apparatus comprising: a processor; and a storage media, the storage media containing processor executable customer specific software application, wherein the processor executable customer specific software application is derived from a specific enterprise resource planning application and a plurality of software models to enable interacting with the specific enterprise resource planning application using the plurality of software models, the plurality of software models being derived from the specific enterprise resource planning application by executing at least one query on a repository associated with the specific enterprise resource planning application, each of the plurality of software models being compliant with a meta-model by sharing a subset of common structures and functions with the meta-model, the meta-model not being dependent on a software application, the meta-model being derived by identifying the subset of common structures and functions from a plurality of enterprise resource planning applications. | 17. A computing apparatus comprising: a processor; and a storage media, the storage media containing processor executable customer specific software application, wherein the processor executable customer specific software application is derived from a specific enterprise resource planning application and a plurality of software models to enable interacting with the specific enterprise resource planning application using the plurality of software models, the plurality of software models being derived from the specific enterprise resource planning application by executing at least one query on a repository associated with the specific enterprise resource planning application, each of the plurality of software models being compliant with a meta-model by sharing a subset of common structures and functions with the meta-model, the meta-model not being dependent on a software application, the meta-model being derived by identifying the subset of common structures and functions from a plurality of enterprise resource planning applications. 18. The computing apparatus of claim 17 , wherein the meta-model is derived using Universal Modeling Language or Eclipse Modeling Framework. | 0.831731 |
8,706,680 | 1 | 7 | 1. An automated method that enables a user to prepare a report using a computer system having a processor, an input interface, and an output interface, said method comprising: entering context information into the input interface; displaying a single lexeme query and associated lexeme responses from a lexicon containing a plurality of such queries and associated responses on the computer system's output interface; allowing the user to select a response to the lexeme query from the display wherein the queries are displayed iteratively one-at-a-time in an order established by the system's coherence and predicance, and wherein the user is constrained to respond to the queries in the order they are presented by the system; determining whether the selected lexeme response instructs the system to move forward to the next section of the report, and if so, moving the system forward to the next section of the report; determining whether the selected lexeme is an active lexeme, and if so, executing the task associated with the active lexeme; determining whether the selected lexeme sets new predicants to be true, and if so, adding the predicants to a predicant list stored by the system; determining the next lexeme query in the order established by the coherence of the lexicon which contains one or more predicants matching the current predicant list and displaying this next lexeme query on the computer system's output interface; iterating this process until the report is complete; and concatenating and exporting the content of the selected lexeme responses in one or more styles. | 1. An automated method that enables a user to prepare a report using a computer system having a processor, an input interface, and an output interface, said method comprising: entering context information into the input interface; displaying a single lexeme query and associated lexeme responses from a lexicon containing a plurality of such queries and associated responses on the computer system's output interface; allowing the user to select a response to the lexeme query from the display wherein the queries are displayed iteratively one-at-a-time in an order established by the system's coherence and predicance, and wherein the user is constrained to respond to the queries in the order they are presented by the system; determining whether the selected lexeme response instructs the system to move forward to the next section of the report, and if so, moving the system forward to the next section of the report; determining whether the selected lexeme is an active lexeme, and if so, executing the task associated with the active lexeme; determining whether the selected lexeme sets new predicants to be true, and if so, adding the predicants to a predicant list stored by the system; determining the next lexeme query in the order established by the coherence of the lexicon which contains one or more predicants matching the current predicant list and displaying this next lexeme query on the computer system's output interface; iterating this process until the report is complete; and concatenating and exporting the content of the selected lexeme responses in one or more styles. 7. The method of claim 1 further comprising the step of entering text into the report manually. | 0.616935 |
9,996,620 | 14 | 15 | 14. The method of claim 13 and further comprising selecting a third topic from the saved topics via the interface. | 14. The method of claim 13 and further comprising selecting a third topic from the saved topics via the interface. 15. The method of claim 14 , wherein selecting the third topic from the saved topics is performed manually or automatically. | 0.968969 |
8,234,274 | 15 | 19 | 15. A method for extracting characteristics from a corpus of linked documents, comprising: deriving a content link model that explicitly captures direct and indirect relations represented by the links where the model is a generative probabilistic model of the corpus along with citation information among documents, each document represented as a mixture over latent topics, and each relationship among documents is modeled by another generative process, with a topic distribution of each document being a mixture of distributions associated with related documents, using a citation-topic (CT) model with a generative process for each word w in the document d in the corpus, with document probabilities Ξ, topic distribution matrix Θ and word probabilities matrix Ψ, including: choosing a related document c from p(c|d,Ξ), a multinomial probability conditioned on the document d; choosing a topic z from the topic distribution of the document c, p(z|c Θ); choosing a word w which follows the multinomial distribution p(w|z,Ψ) conditioned on the topic z; and extracting document topics and the topic distributions for all the documents in the corpus using the content-link model, wherein the content link model captures direct and indirect relationships represented by the links. | 15. A method for extracting characteristics from a corpus of linked documents, comprising: deriving a content link model that explicitly captures direct and indirect relations represented by the links where the model is a generative probabilistic model of the corpus along with citation information among documents, each document represented as a mixture over latent topics, and each relationship among documents is modeled by another generative process, with a topic distribution of each document being a mixture of distributions associated with related documents, using a citation-topic (CT) model with a generative process for each word w in the document d in the corpus, with document probabilities Ξ, topic distribution matrix Θ and word probabilities matrix Ψ, including: choosing a related document c from p(c|d,Ξ), a multinomial probability conditioned on the document d; choosing a topic z from the topic distribution of the document c, p(z|c Θ); choosing a word w which follows the multinomial distribution p(w|z,Ψ) conditioned on the topic z; and extracting document topics and the topic distributions for all the documents in the corpus using the content-link model, wherein the content link model captures direct and indirect relationships represented by the links. 19. The method of claim 15 , comprising applying the topics and the topic distributions to derive features for document clustering or classification. | 0.929183 |
7,809,564 | 8 | 10 | 8. A data processing system for matching voice based keywords to keyword indexed search items, the data processing system comprising: a bus; a storage device connected to the bus, wherein the storage device contains computer usable code; at least one managed device connected to the bus; a communications unit connected to the bus; and a processing unit connected to the bus, wherein the processing unit executes the computer usable code to identify, in response to receiving a spoken search request from a caller, keywords within the spoken search request, create a list of candidates comprising a match to at least one of the keywords, wherein each candidate in the list is assigned a level of confidence in the match, locate keyword indexed search items having at least one of the keywords as an index and an original matching score, weight the original matching score of each keyword indexed search item with the level of confidence in the list of candidates to form weighted matching scores, sort the keyword indexed search items based on the weighted matching scores, and create a list of the sorted keyword indexed search items. | 8. A data processing system for matching voice based keywords to keyword indexed search items, the data processing system comprising: a bus; a storage device connected to the bus, wherein the storage device contains computer usable code; at least one managed device connected to the bus; a communications unit connected to the bus; and a processing unit connected to the bus, wherein the processing unit executes the computer usable code to identify, in response to receiving a spoken search request from a caller, keywords within the spoken search request, create a list of candidates comprising a match to at least one of the keywords, wherein each candidate in the list is assigned a level of confidence in the match, locate keyword indexed search items having at least one of the keywords as an index and an original matching score, weight the original matching score of each keyword indexed search item with the level of confidence in the list of candidates to form weighted matching scores, sort the keyword indexed search items based on the weighted matching scores, and create a list of the sorted keyword indexed search items. 10. The data processing system of claim 8 , wherein the processing unit further executes the computer usable code to determine, in response to creating the list of candidates, that at least one candidate in the list of candidates comprises a plurality of keywords, and assigns an individual level of confidence to each of the plurality of keywords. | 0.596288 |
9,564,121 | 1 | 5 | 1. A method comprising: adding a supplemental phoneset to a speech synthesizer front end having an existing phoneset wherein the supplemental phoneset is a cluster feature where initial consonant clusters are marked with diacritics; modifying a unit selection process by adding costs associated with the supplemental phoneset to a selection cost that is part of the unit selection process, to yield a modified unit selection process; and generating speech using units from the supplemental phoneset and the existing phoneset, wherein the units are selected by the modified unit selection process. | 1. A method comprising: adding a supplemental phoneset to a speech synthesizer front end having an existing phoneset wherein the supplemental phoneset is a cluster feature where initial consonant clusters are marked with diacritics; modifying a unit selection process by adding costs associated with the supplemental phoneset to a selection cost that is part of the unit selection process, to yield a modified unit selection process; and generating speech using units from the supplemental phoneset and the existing phoneset, wherein the units are selected by the modified unit selection process. 5. The method of claim 1 , adjusting the costs using weights. | 0.913105 |
8,305,622 | 1 | 9 | 1. A method of previewing messages comprising: receiving at a message preview system a plurality of electronic messages including a plurality of voice messages, the message preview system including a processor and memory including executable instructions configured to decompose at least a subset of electronic messages to form message components; identifying contextual message information and content that includes audio associated with the plurality of voice messages; decomposing the audio of the plurality of voice messages into the message components; identifying searchable identifiers associated with a subset of the message components, the searchable identifiers including searchable text; receiving a preview request to provide preview information, the preview request including a string of text to identify a subset of the voice messages that include a searchable identifier matching the string of text; identifying the subset of voice messages that include the searchable identifier that matches the string of text; causing display of representations for the subset of voice messages in a touch screen interface of a mobile device, and causing display of a subset of the contextual message information associated with the subset of voice messages as a portion of the preview information in the touch screen interface of the mobile device. | 1. A method of previewing messages comprising: receiving at a message preview system a plurality of electronic messages including a plurality of voice messages, the message preview system including a processor and memory including executable instructions configured to decompose at least a subset of electronic messages to form message components; identifying contextual message information and content that includes audio associated with the plurality of voice messages; decomposing the audio of the plurality of voice messages into the message components; identifying searchable identifiers associated with a subset of the message components, the searchable identifiers including searchable text; receiving a preview request to provide preview information, the preview request including a string of text to identify a subset of the voice messages that include a searchable identifier matching the string of text; identifying the subset of voice messages that include the searchable identifier that matches the string of text; causing display of representations for the subset of voice messages in a touch screen interface of a mobile device, and causing display of a subset of the contextual message information associated with the subset of voice messages as a portion of the preview information in the touch screen interface of the mobile device. 9. The method of claim 1 wherein the searchable identifier is a word derived from converting the audio of the voice messages into the searchable text. | 0.878247 |
10,121,517 | 8 | 9 | 8. The computer implemented method of claim 7 , further comprising identifying a second portion of the displayed text comprising a first number of consecutive characters starting form the first character, wherein the first number of consecutive characters divided by the total number of characters is equal to or approximately equal to the calculated percentage of time the first video was viewed. | 8. The computer implemented method of claim 7 , further comprising identifying a second portion of the displayed text comprising a first number of consecutive characters starting form the first character, wherein the first number of consecutive characters divided by the total number of characters is equal to or approximately equal to the calculated percentage of time the first video was viewed. 9. The computer implemented method of claim 8 , wherein the graphic element indicating the duration of time that the first video was viewed comprises highlighting applied to the second portion of the displayed text. | 0.868902 |
9,875,098 | 10 | 12 | 10. A computer implemented system for extracting a business rule embedded in an application source code, the system comprising: a processor; and a memory coupled to the processor, wherein the processor is capable of executing a plurality of modules stored in the memory, the plurality of modules comprising: a creating module configured to create and analyze a call structure of one or more programs present in an application source code by performing a control flow analysis on the application source code, wherein the control flow analysis is performed using at least one of abstract representation, resolving of a dynamic call, object resolution, and a control transfer to determine a control flow between the one or more programs; a recognizing module configured to identify, from the one or more programs, one or more parent programs and one or more child programs for the parent program based on the call structure, wherein the parent program is capable of calling the one or more child programs and using the call structure to enable the recognizing module to establish at least one of a relation and dependency between the one or more programs; a grouping module configured to group the parent program and the one or more child programs, each program in the group including a plurality of conditional statements, wherein the grouping is performed based on a plurality of identical characteristics of the one or more child programs and wherein the identical characteristics comprise the one or more programs starting with same naming convention; an identification module configured to identify one or more conditional statements among the plurality of conditional statements, wherein the one or more conditional statements comprise a business rule, and wherein the identification module is further configured to identify the one or more conditional statements by: comparing the plurality of conditional statements with a plurality of pre-defined patterns identified from the application source code, wherein the plurality of predefined patterns comprises at least one pattern associated with the business rule, and at least another pattern lacking the business rule, or comparing a variable with a hard-coded value; generating a hierarchy of the conditional statements, wherein the hierarchy defines one or more parent conditional statements and one or more child conditional statements dependent on the parent conditional statements, wherein the parent conditional statements and the child conditional statements are nested conditions occurring in a plurality of sub-entities; and extracting a business rule embedded in the application source code, by a mapping module configured to map the one or more conditional statements with a business rule selected among business rules stored in a predefined business rule template and a business rule created using the ore-defined business rule template. | 10. A computer implemented system for extracting a business rule embedded in an application source code, the system comprising: a processor; and a memory coupled to the processor, wherein the processor is capable of executing a plurality of modules stored in the memory, the plurality of modules comprising: a creating module configured to create and analyze a call structure of one or more programs present in an application source code by performing a control flow analysis on the application source code, wherein the control flow analysis is performed using at least one of abstract representation, resolving of a dynamic call, object resolution, and a control transfer to determine a control flow between the one or more programs; a recognizing module configured to identify, from the one or more programs, one or more parent programs and one or more child programs for the parent program based on the call structure, wherein the parent program is capable of calling the one or more child programs and using the call structure to enable the recognizing module to establish at least one of a relation and dependency between the one or more programs; a grouping module configured to group the parent program and the one or more child programs, each program in the group including a plurality of conditional statements, wherein the grouping is performed based on a plurality of identical characteristics of the one or more child programs and wherein the identical characteristics comprise the one or more programs starting with same naming convention; an identification module configured to identify one or more conditional statements among the plurality of conditional statements, wherein the one or more conditional statements comprise a business rule, and wherein the identification module is further configured to identify the one or more conditional statements by: comparing the plurality of conditional statements with a plurality of pre-defined patterns identified from the application source code, wherein the plurality of predefined patterns comprises at least one pattern associated with the business rule, and at least another pattern lacking the business rule, or comparing a variable with a hard-coded value; generating a hierarchy of the conditional statements, wherein the hierarchy defines one or more parent conditional statements and one or more child conditional statements dependent on the parent conditional statements, wherein the parent conditional statements and the child conditional statements are nested conditions occurring in a plurality of sub-entities; and extracting a business rule embedded in the application source code, by a mapping module configured to map the one or more conditional statements with a business rule selected among business rules stored in a predefined business rule template and a business rule created using the ore-defined business rule template. 12. The system of claim 10 , wherein the mapping module is further configured to map related conditional statements to the business rule, wherein the related conditional statements comprises the parent conditional statements and the child conditional statements, the one or more conditional statements comparing the variable with hard coded value. | 0.501437 |
8,285,273 | 9 | 19 | 9. A method for use on a wireless mobile device, the method comprising: receiving at the wireless mobile device a spoken command requesting a query; receiving at the wireless mobile device spoken information for the query; based on the spoken command and the spoken information, generating text at the wireless mobile device that specifies the requested query; formatting, in the wireless device, from the generated text, the text for a text messaging protocol to create a message in the text messaging protocol, specifying the query; addressing the message to an internet search engine; and transmitting the message from the wireless device, over a wireless network, to the search engine. | 9. A method for use on a wireless mobile device, the method comprising: receiving at the wireless mobile device a spoken command requesting a query; receiving at the wireless mobile device spoken information for the query; based on the spoken command and the spoken information, generating text at the wireless mobile device that specifies the requested query; formatting, in the wireless device, from the generated text, the text for a text messaging protocol to create a message in the text messaging protocol, specifying the query; addressing the message to an internet search engine; and transmitting the message from the wireless device, over a wireless network, to the search engine. 19. The method of claim 9 , further comprising receiving, over the wireless network, search results produced by the search engine in response to the query. | 0.814149 |
9,275,023 | 13 | 18 | 13. A non-transitory computer readable medium having stored thereon instructions for further adapting eXtensible Stylesheet Language (XSL) to HyperText Markup Language (HTML) document transformations comprising machine executable code which when executed by at least one processor, causes the processor to perform steps comprising: identifying a plurality of rules matching one or more elements in an HTML document; identifying a plurality of actions associated with each of the identified plurality of rules; grouping each of the matching identified plurality of actions together into one or more corresponding groups; filtering the grouped plurality of actions based on one or more filtering rules when two or more of the grouped plurality of actions match; removing one or more of the plurality of actions in each of the one or more corresponding groups based on the one or more filtering rules; applying the remaining grouped plurality of actions that match after the filtering to transform the matching one or more elements in the HTML document; and providing the transformed HTML document. | 13. A non-transitory computer readable medium having stored thereon instructions for further adapting eXtensible Stylesheet Language (XSL) to HyperText Markup Language (HTML) document transformations comprising machine executable code which when executed by at least one processor, causes the processor to perform steps comprising: identifying a plurality of rules matching one or more elements in an HTML document; identifying a plurality of actions associated with each of the identified plurality of rules; grouping each of the matching identified plurality of actions together into one or more corresponding groups; filtering the grouped plurality of actions based on one or more filtering rules when two or more of the grouped plurality of actions match; removing one or more of the plurality of actions in each of the one or more corresponding groups based on the one or more filtering rules; applying the remaining grouped plurality of actions that match after the filtering to transform the matching one or more elements in the HTML document; and providing the transformed HTML document. 18. The medium as set forth in claim 13 , wherein the one or more filtering rules comprises removing remove-element or set-meta-category when the identified plurality of actions in the one or more corresponding groups comprises set-meta-category. | 0.753507 |
9,208,501 | 1 | 2 | 1. An electronic computing device for providing a personalized information recommendation, comprising: an input/output interface, being configured to receive a first behavior data of a first user and a second behavior data of a second user, wherein the first behavior data and the second behavior data are arranged in a first period; a storage electrically connected to the input/output interface, being configured to store the first behavior data and the second behavior data; and a processor electrically connected to the storage, being configured to execute the following operations: retrieving the first behavior data and the second behavior data from the storage; establishing a first tree structure data and a second tree structure data according to the first behavior data and the second behavior data respectively by using an ontology construction algorithm; calculating a first similarity between the first tree structure data and the second tree structure data by using a similarity evaluation algorithm; analyzing the first similarity to subsume the first tree structure data and the second tree structure data into a first group by using a clustering algorithm; determining a piece of first difference information between the first tree structure data and the second tree structure data according to the first group; and generating a piece of first recommending information corresponding to the first user which is arranged in the first period according to the piece of first difference information so that a first monitor displays the piece of first recommending information. | 1. An electronic computing device for providing a personalized information recommendation, comprising: an input/output interface, being configured to receive a first behavior data of a first user and a second behavior data of a second user, wherein the first behavior data and the second behavior data are arranged in a first period; a storage electrically connected to the input/output interface, being configured to store the first behavior data and the second behavior data; and a processor electrically connected to the storage, being configured to execute the following operations: retrieving the first behavior data and the second behavior data from the storage; establishing a first tree structure data and a second tree structure data according to the first behavior data and the second behavior data respectively by using an ontology construction algorithm; calculating a first similarity between the first tree structure data and the second tree structure data by using a similarity evaluation algorithm; analyzing the first similarity to subsume the first tree structure data and the second tree structure data into a first group by using a clustering algorithm; determining a piece of first difference information between the first tree structure data and the second tree structure data according to the first group; and generating a piece of first recommending information corresponding to the first user which is arranged in the first period according to the piece of first difference information so that a first monitor displays the piece of first recommending information. 2. The electronic computing device as claimed in claim 1 , wherein the input/output interface is further configured to receive a third behavior data of a third user, the third behavior data is arranged in the first period, the storage is further configured to store the third behavior data, and the processor is further configured to execute the following operations: retrieving the third behavior data from the storage; establishing a third tree structure data according to the third behavior data by using the ontology construction algorithm; calculating a second similarity between the first tree structure data and the third tree structure data, and a third similarity between the second tree structure data and the third tree structure data by using the similarity evaluation algorithm; and wherein the first group further comprises the third tree structure data that is obtained by the processor by further using the clustering algorithm to analyze the first similarity, the second similarity and the third similarity; wherein the piece of first difference information is further obtained by the processor by determining a difference between the first tree structure data and the second and the third tree structure data according to the first group. | 0.76275 |
8,656,371 | 21 | 24 | 21. The report representation system of claim 16 , wherein the optimization is bi-directional. | 21. The report representation system of claim 16 , wherein the optimization is bi-directional. 24. The report representation system of claim 21 , wherein the report representation system allows the report to be modified by a client, the report representation system further comprising: a synchronizer to synchronize modifications to the report from the client back to a server. | 0.942284 |
7,996,384 | 1 | 7 | 1. A computer-implemented method comprising: receiving a rule set container storing a plurality of abstract rules, wherein each abstract rule includes (i) a conditional statement and (ii) a consequential statement defining a result returned by an abstract rule for a data record supplied to the abstract rule satisfying the conditional statement; identifying a first abstract rule among the plurality of abstract rules, wherein the consequential statement of the first abstract rule specifies to reject data records that satisfy the conditional statement of the first abstract rule from being processed by other abstract rules among the plurality of abstract rules; identifying a second abstract rule among the plurality of abstract rules, wherein the consequential statement of the second abstract rule specifies an inference message to return for data records that satisfy the conditional statement of the second abstract rule; transforming the first abstract rule and the second abstract rule into a single executable rule, wherein the single executable rule includes the consequential statement of the second abstract rule and a new conditional statement, the new conditional statement comprising the conditional statement of the second abstract rule and an exclusionary conditional statement that excludes data records satisfying the conditional statement of the first abstract rule; and storing the single executable rule for execution against a database query result. | 1. A computer-implemented method comprising: receiving a rule set container storing a plurality of abstract rules, wherein each abstract rule includes (i) a conditional statement and (ii) a consequential statement defining a result returned by an abstract rule for a data record supplied to the abstract rule satisfying the conditional statement; identifying a first abstract rule among the plurality of abstract rules, wherein the consequential statement of the first abstract rule specifies to reject data records that satisfy the conditional statement of the first abstract rule from being processed by other abstract rules among the plurality of abstract rules; identifying a second abstract rule among the plurality of abstract rules, wherein the consequential statement of the second abstract rule specifies an inference message to return for data records that satisfy the conditional statement of the second abstract rule; transforming the first abstract rule and the second abstract rule into a single executable rule, wherein the single executable rule includes the consequential statement of the second abstract rule and a new conditional statement, the new conditional statement comprising the conditional statement of the second abstract rule and an exclusionary conditional statement that excludes data records satisfying the conditional statement of the first abstract rule; and storing the single executable rule for execution against a database query result. 7. The computer-implemented method of claim 1 , wherein the exclusionary conditional statement is based on a rejection query, wherein the rejection query returns a rejection set comprising a plurality of data records to be excluded from processing. | 0.760155 |
7,606,797 | 14 | 16 | 14. A computer system for extracting attribute values from formatted data, the computer system comprising a physical computing device with a processor and a memory, said physical computing device being programmed to execute the following steps: maintaining an attribute repository containing information concerning a plurality of attributes, wherein an attribute comprises an entity to which is assigned one from a finite group of values, and wherein the information concerning each attribute comprises at least one matching attribute name and at least one matching value for that attribute; parsing formatted data and creating a plurality of elements, each element representing a segment of the data, comprising a canonical representation of the data, independent of the data format, said canonical representation comprising a sequence at least of text elements, each text element representing a contiguous unit of text, wherein said canonical representation excludes non-substantive content; scanning the elements of the plurality for occurrences of attribute values; ranking, by a computer, each element based on how many distinct attributes occur in that element; for each of a plurality of attributes, ranking, by a computer, each matching value for that attribute based on the highest ranking of an element in which that value occurs, and on an occurrence of that value in the same element as an occurrence of a matching name of that attribute; for each of a plurality of values occurring that occur in the formatted data, inferring, by a computer, occurrence in the formatted data of the attribute for which that value has the highest ranking, and assigning that value to that attribute; and preparing a summary of the data, using at least one attribute inferred to occur in the data and an assigned value of said at least one attribute. | 14. A computer system for extracting attribute values from formatted data, the computer system comprising a physical computing device with a processor and a memory, said physical computing device being programmed to execute the following steps: maintaining an attribute repository containing information concerning a plurality of attributes, wherein an attribute comprises an entity to which is assigned one from a finite group of values, and wherein the information concerning each attribute comprises at least one matching attribute name and at least one matching value for that attribute; parsing formatted data and creating a plurality of elements, each element representing a segment of the data, comprising a canonical representation of the data, independent of the data format, said canonical representation comprising a sequence at least of text elements, each text element representing a contiguous unit of text, wherein said canonical representation excludes non-substantive content; scanning the elements of the plurality for occurrences of attribute values; ranking, by a computer, each element based on how many distinct attributes occur in that element; for each of a plurality of attributes, ranking, by a computer, each matching value for that attribute based on the highest ranking of an element in which that value occurs, and on an occurrence of that value in the same element as an occurrence of a matching name of that attribute; for each of a plurality of values occurring that occur in the formatted data, inferring, by a computer, occurrence in the formatted data of the attribute for which that value has the highest ranking, and assigning that value to that attribute; and preparing a summary of the data, using at least one attribute inferred to occur in the data and an assigned value of said at least one attribute. 16. The computer system of claim 14 , wherein inferring occurrence of specific attributes in the formatted data and assigning most appropriate occurring values to the specific attributes is based at least upon at least one maintained datum concerning attributes from a group of data concerning attributes consisting of: a set of matching values for each of a plurality of attributes; a set of matching names for each of a plurality of attributes; and a number of matching values for each of a plurality of attributes. | 0.621523 |
7,594,173 | 1 | 6 | 1. A document control apparatus for storing and controlling electronic documents accessible from an external apparatus, comprising: a storage device registering means for registering at least one electronic document to the storage device, the electronic document being transmitted from the external apparatus; period controlling means for storing information of a document control period of the electronic document registered by said registering means; keeping means for keeping the electronic document in the storage device even after the document control period of the electronic document has expired; access prohibiting means for prohibiting access from the external apparatus to the electronic document whose document control period has expired; first confirming means for confirming whether or not the document control period may be extended when the document control period has expired; second confirming means for confirming whether or not a user requests temporary access to the electronic document with an additional charge, when said first confirming means confirms that the control period may not be extended; temporary access allowing means for allowing temporary access to the electronic document whose document control period has expired when the additional charge has been confirmed for the temporary access to the electronic document, when said second confirming means confirms that the user requests the temporary access to the electronic document with the additional charge; and transferring means for transferring the electronic document to the external apparatus based on a user request, when said first confirming means confirms that the control period may be extended, or when said temporary access allowing means allows the temporary access to the electronic document. | 1. A document control apparatus for storing and controlling electronic documents accessible from an external apparatus, comprising: a storage device registering means for registering at least one electronic document to the storage device, the electronic document being transmitted from the external apparatus; period controlling means for storing information of a document control period of the electronic document registered by said registering means; keeping means for keeping the electronic document in the storage device even after the document control period of the electronic document has expired; access prohibiting means for prohibiting access from the external apparatus to the electronic document whose document control period has expired; first confirming means for confirming whether or not the document control period may be extended when the document control period has expired; second confirming means for confirming whether or not a user requests temporary access to the electronic document with an additional charge, when said first confirming means confirms that the control period may not be extended; temporary access allowing means for allowing temporary access to the electronic document whose document control period has expired when the additional charge has been confirmed for the temporary access to the electronic document, when said second confirming means confirms that the user requests the temporary access to the electronic document with the additional charge; and transferring means for transferring the electronic document to the external apparatus based on a user request, when said first confirming means confirms that the control period may be extended, or when said temporary access allowing means allows the temporary access to the electronic document. 6. The document control apparatus according to claim 1 , wherein said keeping means keeps an electronic document that is frequently accessed from the external apparatus, and wherein said temporary access allowing means allows the temporary access to the stored electronic document based on the predetermined charge. | 0.605263 |
8,510,340 | 13 | 16 | 13. A processor-readable medium encoded with processor-readable code that, when executed, performs a method comprising: identifying a plurality of alternative hypotheses for a medical billing code corresponding to a portion of text documenting a patient encounter; selecting at least two of the alternative hypotheses; and displaying the selected hypotheses to a user documenting the patient encounter; wherein the selecting comprises: scoring each hypotheses of the plurality of alternative hypotheses; and selecting hypotheses of the plurality of alternative hypotheses that exceed a threshold score. | 13. A processor-readable medium encoded with processor-readable code that, when executed, performs a method comprising: identifying a plurality of alternative hypotheses for a medical billing code corresponding to a portion of text documenting a patient encounter; selecting at least two of the alternative hypotheses; and displaying the selected hypotheses to a user documenting the patient encounter; wherein the selecting comprises: scoring each hypotheses of the plurality of alternative hypotheses; and selecting hypotheses of the plurality of alternative hypotheses that exceed a threshold score. 16. The processor-readable medium of claim 13 , wherein the method further comprises: allowing the user to choose a billing code from among the displayed alternative hypotheses; and designating the billing code chosen by the user as accurately representing information corresponding to the portion of the text. | 0.528875 |
9,361,586 | 1 | 6 | 1. A method to facilitate pattern recognition comprising: processing a set of vectors into feature vectors; wherein the processing comprises employing machine learning component adjusted parameters; wherein the machine learning component adjusted parameters are adjusted based at least in part on at least partially conflicting learning objectives including an input fidelity objective and an invariance objective, and are further adjusted at least in part by adding one or more scaled derivatives of the input fidelity objective approximately concurrently with one or more scaled derivatives of the invariance objective to one or more of the machine learning component adjusted parameters. | 1. A method to facilitate pattern recognition comprising: processing a set of vectors into feature vectors; wherein the processing comprises employing machine learning component adjusted parameters; wherein the machine learning component adjusted parameters are adjusted based at least in part on at least partially conflicting learning objectives including an input fidelity objective and an invariance objective, and are further adjusted at least in part by adding one or more scaled derivatives of the input fidelity objective approximately concurrently with one or more scaled derivatives of the invariance objective to one or more of the machine learning component adjusted parameters. 6. The method of claim 1 wherein the at least partially conflicting learning objectives comprises a temporal coherence objective. | 0.724359 |
9,275,368 | 21 | 22 | 21. The non-transitory computer-readable storage medium of claim 19 , wherein generating alignments further comprises: determining that a difference is not an insert or a delete, a small replacement, a split word, or a merge word; and applying a word sequence alignment algorithm to generate an alignment for the difference. | 21. The non-transitory computer-readable storage medium of claim 19 , wherein generating alignments further comprises: determining that a difference is not an insert or a delete, a small replacement, a split word, or a merge word; and applying a word sequence alignment algorithm to generate an alignment for the difference. 22. The non-transitory computer-readable storage medium of claim 21 , wherein the word sequence alignment algorithm is customized for aligning word sequences, wherein the word sequence alignment algorithm outputs a word similarity matrix. | 0.923962 |
8,306,808 | 1 | 2 | 1. A computer-implemented method comprising: accessing, by a computer system, a string of characters that are associated with a computing device; identifying, by the computer system, a plurality of candidate languages for segmenting the string of characters, wherein the plurality of candidate languages are identified based on one or more language indicators associated with the string of characters or the computing device; determining weights for the plurality of candidate languages based on the one or more language indicators, wherein each of the weights indicates a probability that a corresponding candidate language from the plurality of candidate languages is an appropriate language to use for interpreting the string of characters based on the string of characters or the computing device; determining one or more segmented results from the string of characters for each of the plurality of candidate languages, wherein a segmented result comprises a plurality of tokens that are created by inserting one or more breaks into the string of characters; identifying, from the plurality of candidate languages, an operable language for the string of characters based, at least in part, on a comparison of weighted frequencies associated with the candidate languages, wherein each of the weighted frequencies comprises a frequency with which the segmented results occur in a corpus associated with a corresponding candidate language, the frequency being weighted according to a corresponding weight from the determined weights that is associated with the corresponding candidate language; and providing information that identifies the operable language. | 1. A computer-implemented method comprising: accessing, by a computer system, a string of characters that are associated with a computing device; identifying, by the computer system, a plurality of candidate languages for segmenting the string of characters, wherein the plurality of candidate languages are identified based on one or more language indicators associated with the string of characters or the computing device; determining weights for the plurality of candidate languages based on the one or more language indicators, wherein each of the weights indicates a probability that a corresponding candidate language from the plurality of candidate languages is an appropriate language to use for interpreting the string of characters based on the string of characters or the computing device; determining one or more segmented results from the string of characters for each of the plurality of candidate languages, wherein a segmented result comprises a plurality of tokens that are created by inserting one or more breaks into the string of characters; identifying, from the plurality of candidate languages, an operable language for the string of characters based, at least in part, on a comparison of weighted frequencies associated with the candidate languages, wherein each of the weighted frequencies comprises a frequency with which the segmented results occur in a corpus associated with a corresponding candidate language, the frequency being weighted according to a corresponding weight from the determined weights that is associated with the corresponding candidate language; and providing information that identifies the operable language. 2. The method of claim 1 , wherein the string of characters is received as part of a request from the computing device, and wherein the information is provided for further processing of the string of characters in association with the received request. | 0.852975 |
10,083,231 | 15 | 16 | 15. A computer program product for building and applying fuzzy term partitions, comprising: one or more computer-readable storage media and program instructions stored on at least one of the one or more tangible storage media, the program instructions executable by a processor to cause the processor to perform a method comprising: receiving a fuzzy term input; building a fuzzy category taxonomy based on the received input; implementing the built fuzzy category taxonomy into a fuzzy category classifier; building a fuzzy term extractor based on the implemented fuzzy category classifier; building a fuzzy term association map based on the built fuzzy term extractor; processing a plurality of words stored on a database; extracting a fuzzy term from the processed plurality of words; associating the extracted fuzzy term with a plurality of context data; producing a context data partition for the extracted fuzzy term based on the associated plurality of context data; and applying a weight to the extracted fuzzy term. | 15. A computer program product for building and applying fuzzy term partitions, comprising: one or more computer-readable storage media and program instructions stored on at least one of the one or more tangible storage media, the program instructions executable by a processor to cause the processor to perform a method comprising: receiving a fuzzy term input; building a fuzzy category taxonomy based on the received input; implementing the built fuzzy category taxonomy into a fuzzy category classifier; building a fuzzy term extractor based on the implemented fuzzy category classifier; building a fuzzy term association map based on the built fuzzy term extractor; processing a plurality of words stored on a database; extracting a fuzzy term from the processed plurality of words; associating the extracted fuzzy term with a plurality of context data; producing a context data partition for the extracted fuzzy term based on the associated plurality of context data; and applying a weight to the extracted fuzzy term. 16. The computer program product of claim 15 , further comprising: analyzing a usage context for the received fuzzy term input; applying a fuzzy partition value to the received fuzzy term input; applying a contextual relevancy to the received fuzzy term input; and providing an output based on the applied contextual relevancy. | 0.641447 |
9,298,693 | 1 | 6 | 1. A system comprising: one or more processors; memory; and programming instructions stored on the memory that, when executed by the one or more processors, configure the one or more processors to perform operations comprising: receiving a search string; selecting a plurality of transformation rules based on a composition of the search string; and generating a set of candidate string transformations for the search string based on the plurality of transformation rules and on weights associated with the plurality of transformation rules, the weights being determined based on probability distributions of string pairs associated with the transformation rules, the generating further comprising eliminating one or more candidate string transformations, the eliminating being based at least in part on a score associated with the candidate string transformation; the eliminating comprises comparing an intermediate score of a candidate string transformation with a minimum score, wherein the candidate string transformation is eliminated if the intermediate score is less than the minimum score. | 1. A system comprising: one or more processors; memory; and programming instructions stored on the memory that, when executed by the one or more processors, configure the one or more processors to perform operations comprising: receiving a search string; selecting a plurality of transformation rules based on a composition of the search string; and generating a set of candidate string transformations for the search string based on the plurality of transformation rules and on weights associated with the plurality of transformation rules, the weights being determined based on probability distributions of string pairs associated with the transformation rules, the generating further comprising eliminating one or more candidate string transformations, the eliminating being based at least in part on a score associated with the candidate string transformation; the eliminating comprises comparing an intermediate score of a candidate string transformation with a minimum score, wherein the candidate string transformation is eliminated if the intermediate score is less than the minimum score. 6. The system of claim 1 , wherein the eliminating comprises traversing a dictionary tree with a candidate string transformation under string construction wherein the candidate string transformation is eliminated if a corresponding node is absent from the dictionary tree. | 0.558442 |
6,115,686 | 10 | 11 | 10. The method of claim 9 further comprising the steps of: scanning content text of said HTML document, replacing each content text string of said HTML document that matches one of said text strings that indexes one of said entries in said terminology translation table with said replacement text string contained in said corresponding terminology translation table entry indexed by said matching text string, and replacing each content text string of said HTML document that matches one of said text strings that indexes one of said entries of said enunciation table with said replacement text string contained in said corresponding enunciation translation table entry indexed by said matching text string. | 10. The method of claim 9 further comprising the steps of: scanning content text of said HTML document, replacing each content text string of said HTML document that matches one of said text strings that indexes one of said entries in said terminology translation table with said replacement text string contained in said corresponding terminology translation table entry indexed by said matching text string, and replacing each content text string of said HTML document that matches one of said text strings that indexes one of said entries of said enunciation table with said replacement text string contained in said corresponding enunciation translation table entry indexed by said matching text string. 11. The method of claim 10 wherein a particular entry of said enunciation table further comprises a candidate text string, and wherein said content text string of said HTML document is only replaced with said replacement text string contained in said particular enunciation table entry if said content text string is contained in a second content text string of said HTML document that matches said candidate text string. | 0.882271 |
9,092,516 | 29 | 31 | 29. A system for constructing at least one data structure encoding a preference graph that represents user preferences, the system comprising: at least one processor configured to receive a plurality of first-order user preferences indicative of user preferences among values of attributes of items in a plurality of items, receive at least one second-order user preference indicative of user preferences among the attributes of items in the plurality of items, wherein the preference graph comprises a first node for a first item in the plurality of items and a second node for a second item in the plurality of items, and compute a weight for an edge between the first node and the second node based at least in part on the plurality of first-order user preferences and the at least one second-order user preference, wherein the weight is indicative of a degree of preference for the first item over the second item. | 29. A system for constructing at least one data structure encoding a preference graph that represents user preferences, the system comprising: at least one processor configured to receive a plurality of first-order user preferences indicative of user preferences among values of attributes of items in a plurality of items, receive at least one second-order user preference indicative of user preferences among the attributes of items in the plurality of items, wherein the preference graph comprises a first node for a first item in the plurality of items and a second node for a second item in the plurality of items, and compute a weight for an edge between the first node and the second node based at least in part on the plurality of first-order user preferences and the at least one second-order user preference, wherein the weight is indicative of a degree of preference for the first item over the second item. 31. The system of claim 29 , wherein the at least one processor is further configured to: constructing the at least one data structure encoding the preference graph to include a node for each item in the plurality of items and an edge for every pair of nodes associated with items related by a first-order user preference in the plurality of first-order user preferences. | 0.792506 |
8,515,786 | 1 | 6 | 1. A rule generation system to generate rules for a computer program, the system comprising: a processor; a memory storage device comprising a computer program, the computer program comprising instructions executable with the processor, the instructions comprising: an evaluative expression parameter module configured to generate a graphical user interface for creation of a navigation rule, the navigation rule being indicative of whether to navigate from a first page of the computer program to a second page of the computer program; the evaluative expression parameter module further configured to receive an expression parameter, a logical operator, and at least one expression parameter value from the graphical user interface in response to user input via the graphical user interface at runtime, the expression parameter identifying a question displayed on the first page of the computer program, the at least one expression parameter value including at least one potential answer to the question, wherein the expression parameter and the at least one expression parameter value are operands of the logical operator; an evaluative expression generator configured to generate the navigation rule, the navigation rule including a combination of a first evaluative expression and a second evaluative expression, the first evaluative expression comprising the expression parameter, the operator, and the at least one expression parameter value; instructions executable with the processor to store the first and second evaluative expressions in a database; instructions executable with the processor to receive an answer to the question displayed on the first page from user input at runtime; instructions executable with the processor to evaluate the first and second evaluative expressions retrieved from the database at runtime, the expression parameter set to the answer in the evaluation of the first evaluative expression; and instructions executable with the processor to navigate to the second page from the first page at runtime based on the evaluation of the first and second evaluative expressions retrieved from the database. | 1. A rule generation system to generate rules for a computer program, the system comprising: a processor; a memory storage device comprising a computer program, the computer program comprising instructions executable with the processor, the instructions comprising: an evaluative expression parameter module configured to generate a graphical user interface for creation of a navigation rule, the navigation rule being indicative of whether to navigate from a first page of the computer program to a second page of the computer program; the evaluative expression parameter module further configured to receive an expression parameter, a logical operator, and at least one expression parameter value from the graphical user interface in response to user input via the graphical user interface at runtime, the expression parameter identifying a question displayed on the first page of the computer program, the at least one expression parameter value including at least one potential answer to the question, wherein the expression parameter and the at least one expression parameter value are operands of the logical operator; an evaluative expression generator configured to generate the navigation rule, the navigation rule including a combination of a first evaluative expression and a second evaluative expression, the first evaluative expression comprising the expression parameter, the operator, and the at least one expression parameter value; instructions executable with the processor to store the first and second evaluative expressions in a database; instructions executable with the processor to receive an answer to the question displayed on the first page from user input at runtime; instructions executable with the processor to evaluate the first and second evaluative expressions retrieved from the database at runtime, the expression parameter set to the answer in the evaluation of the first evaluative expression; and instructions executable with the processor to navigate to the second page from the first page at runtime based on the evaluation of the first and second evaluative expressions retrieved from the database. 6. The rule generation system of claim 1 , wherein the evaluative expression parameter module is further configured to create a page display rule, the navigation rule, or a discrepancy rule depending on what evaluative expression category is received from the graphical user interface. | 0.779412 |
7,630,895 | 1 | 3 | 1. A speaker verification method comprising: performing operations executed by a speaker verification machine, the operations comprising: comparing a plurality of different test utterances to a plurality of training utterances for a speaker to form a plurality of preliminary verification decisions, one preliminary verification decision for each of the plurality of different test utterances; weighting each of the plurality of preliminary verification decisions based on a historical error rate corresponding to a respective one of the test utterances; and combining the weighted preliminary verification decisions to form a verification decision. | 1. A speaker verification method comprising: performing operations executed by a speaker verification machine, the operations comprising: comparing a plurality of different test utterances to a plurality of training utterances for a speaker to form a plurality of preliminary verification decisions, one preliminary verification decision for each of the plurality of different test utterances; weighting each of the plurality of preliminary verification decisions based on a historical error rate corresponding to a respective one of the test utterances; and combining the weighted preliminary verification decisions to form a verification decision. 3. The method of claim 1 , further comprising generating a code book covering a plurality of speakers having the plurality of training utterances for each of the plurality of speakers, wherein a first utterance of the plurality of training utterances is not the same as a second utterance of the plurality of training utterances. | 0.5978 |
8,307,372 | 11 | 12 | 11. The method of claim 10 , wherein the disposition includes a condition expression that defines a condition under which the disposition is to occur. | 11. The method of claim 10 , wherein the disposition includes a condition expression that defines a condition under which the disposition is to occur. 12. The method of claim 11 , wherein the condition expression is a Boolean expression. | 0.981337 |
7,941,440 | 1 | 5 | 1. A computer automated method of aggregating data, the method comprising the steps of: inputting a set of user-defined instructions into a computer database system; inputting a user query including data attributes into the computer database system; mining the computer database system for data relevant to the user query; creating a data set comprising the data relevant to the user query; and aggregating data in the data set using domain metrics selected based on any of predefined and configurable rules and past user usage, wherein the aggregation comprises: tagging all data attributes in the data set based on database metadata and inputs from a user, wherein the data attributes comprise any of data identifications (IDs), data grouping attributes, and data measure attributes, wherein the tagging process comprises inputting the user query, the database metadata for the data attributes in the user query, and attributes specifications; and reducing the number of the tagged data attributes in the data set by logically eliminating data attributes; wherein for each of the data attributes in the user query, the tagging process comprises tagging the data attribute as a grouping attribute when the data attribute is to be treated as a grouping attribute based on inputs to any of the computer database system and the database metadata; and wherein when the data attribute comprises a grouping attribute and has a number of unique values less than the maximum numbers of unique values allowed to select a database attribute as a grouping attribute, the tagging process comprises tagging the data attribute as a grouping attribute. | 1. A computer automated method of aggregating data, the method comprising the steps of: inputting a set of user-defined instructions into a computer database system; inputting a user query including data attributes into the computer database system; mining the computer database system for data relevant to the user query; creating a data set comprising the data relevant to the user query; and aggregating data in the data set using domain metrics selected based on any of predefined and configurable rules and past user usage, wherein the aggregation comprises: tagging all data attributes in the data set based on database metadata and inputs from a user, wherein the data attributes comprise any of data identifications (IDs), data grouping attributes, and data measure attributes, wherein the tagging process comprises inputting the user query, the database metadata for the data attributes in the user query, and attributes specifications; and reducing the number of the tagged data attributes in the data set by logically eliminating data attributes; wherein for each of the data attributes in the user query, the tagging process comprises tagging the data attribute as a grouping attribute when the data attribute is to be treated as a grouping attribute based on inputs to any of the computer database system and the database metadata; and wherein when the data attribute comprises a grouping attribute and has a number of unique values less than the maximum numbers of unique values allowed to select a database attribute as a grouping attribute, the tagging process comprises tagging the data attribute as a grouping attribute. 5. The method of claim 1 , further comprising the step of calculating a number of unique values in said data set associated with a given attribute. | 0.961679 |
6,081,775 | 20 | 22 | 20. The computer-readable medium of claim 12 wherein the contents of the computer-readable medium cause the computer system to further: identify within the selected word subgraph a third node representing a third occurrence of the second word, the third node having a word sense characterization; and determine to attribute to the first node the word sense characterization of the second occurrence of the second word rather than the word sense characterization of the third occurrence of the second word based upon a characteristic of the second occurrence of the second word. | 20. The computer-readable medium of claim 12 wherein the contents of the computer-readable medium cause the computer system to further: identify within the selected word subgraph a third node representing a third occurrence of the second word, the third node having a word sense characterization; and determine to attribute to the first node the word sense characterization of the second occurrence of the second word rather than the word sense characterization of the third occurrence of the second word based upon a characteristic of the second occurrence of the second word. 22. The computer-readable medium of claim 20 wherein the determining determines to attribute to the first occurrence of the second word the word sense characterization of the second occurrence of the second word rather than the word sense characterization of the third occurrence of the second word based upon a determination that the second occurrence of the second word is more closely related to the first word than is the third occurrence of the second word. | 0.707965 |
7,774,699 | 1 | 9 | 1. A method of transforming data from a first hierarchical data structure into a second hierarchical data structure, comprising: determining which segments within the first hierarchal data structure are separable by determining segments which are not referenced by another segment; separating the determined separable segments from the first hierarchical data structure into individual segments; transforming each individual segment, wherein the transforming of a set of one or more segments that comprise a portion of the first hierarchical data structure is done independently from transforming another set, and wherein the transforming is defined by a transformation file; analyzing the transformation file to determine one or more sets of repeated transformations that are separable; analyzing the first hierarchical data structure to estimate which set of the separable transformations will utilize the most computing resources, wherein the analyzing comprises counting the data elements and their descendants accessed within a set of transformations, and wherein the number of segments is based upon the number of data elements and their descendants; in response to the number of data elements and their descendants in a set of the separable transformations providing a beneficial reduction in the use of the computing resources, segmenting the set of the separable transformations; and combining the separable transformed segments to form the second hierarchical data structure, by parsing each segment separately until all segments have been parsed. | 1. A method of transforming data from a first hierarchical data structure into a second hierarchical data structure, comprising: determining which segments within the first hierarchal data structure are separable by determining segments which are not referenced by another segment; separating the determined separable segments from the first hierarchical data structure into individual segments; transforming each individual segment, wherein the transforming of a set of one or more segments that comprise a portion of the first hierarchical data structure is done independently from transforming another set, and wherein the transforming is defined by a transformation file; analyzing the transformation file to determine one or more sets of repeated transformations that are separable; analyzing the first hierarchical data structure to estimate which set of the separable transformations will utilize the most computing resources, wherein the analyzing comprises counting the data elements and their descendants accessed within a set of transformations, and wherein the number of segments is based upon the number of data elements and their descendants; in response to the number of data elements and their descendants in a set of the separable transformations providing a beneficial reduction in the use of the computing resources, segmenting the set of the separable transformations; and combining the separable transformed segments to form the second hierarchical data structure, by parsing each segment separately until all segments have been parsed. 9. The method of claim 1 , further comprising: separating a segment into sub-segments; transforming each sub-segment of the segment; and combining each transformed sub-segment. | 0.78744 |
9,734,233 | 20 | 30 | 20. A system for configuring a menu in a smart device, which configures a menu of an application in a smart device for an application designated or download-requested by the smart device including an information and communication terminal or a content display terminal by accessing a specific place, wherein the smart device comprises: a processor configured to designate an application or request download of an application from the specific place, and manage the designated or downloaded application; the processor configured to collect information about one or more of a keyword, a title, and a tag of the application, and determine the collected information as keywords for searching for a semantic menu; the processor configured to classify the semantic menu by using the keyword extracted by the processor; and the processor configured to display the semantic menu classified by the processor on the smart device, wherein the processor looks up a semantic menu dictionary by using the keyword extracted by the keyword extraction processor as a search keyword, extracts a semantic menu name matched to the search keyword from the semantic menu dictionary, and configures a semantic menu file system, and wherein the number of semantic menu names is 7 to 12. | 20. A system for configuring a menu in a smart device, which configures a menu of an application in a smart device for an application designated or download-requested by the smart device including an information and communication terminal or a content display terminal by accessing a specific place, wherein the smart device comprises: a processor configured to designate an application or request download of an application from the specific place, and manage the designated or downloaded application; the processor configured to collect information about one or more of a keyword, a title, and a tag of the application, and determine the collected information as keywords for searching for a semantic menu; the processor configured to classify the semantic menu by using the keyword extracted by the processor; and the processor configured to display the semantic menu classified by the processor on the smart device, wherein the processor looks up a semantic menu dictionary by using the keyword extracted by the keyword extraction processor as a search keyword, extracts a semantic menu name matched to the search keyword from the semantic menu dictionary, and configures a semantic menu file system, and wherein the number of semantic menu names is 7 to 12. 30. The system of claim 20 , wherein the processor configures the semantic menu file system in a tree structure or a network structure. | 0.875 |
9,324,330 | 1 | 11 | 1. A computational method for transforming an input audio encoding of speech into an output that is rhythmically consistent with a target song, the method comprising: segmenting the input audio encoding of the speech into plural segments, the segments corresponding to successive sequences of samples of the audio encoding and delimited by onsets identified therein; mapping individual ones of the plural segments to respective sub-phrase portions of a phrase template for the target song, the mapping establishing one or more phrase candidates; temporally aligning at least one of the phrase candidates with a rhythmic skeleton for the target song; and preparing a resultant audio encoding of the speech in correspondence with the temporally aligned phrase candidate-mapped from onset-delimited segments of the input audio encoding. | 1. A computational method for transforming an input audio encoding of speech into an output that is rhythmically consistent with a target song, the method comprising: segmenting the input audio encoding of the speech into plural segments, the segments corresponding to successive sequences of samples of the audio encoding and delimited by onsets identified therein; mapping individual ones of the plural segments to respective sub-phrase portions of a phrase template for the target song, the mapping establishing one or more phrase candidates; temporally aligning at least one of the phrase candidates with a rhythmic skeleton for the target song; and preparing a resultant audio encoding of the speech in correspondence with the temporally aligned phrase candidate-mapped from onset-delimited segments of the input audio encoding. 11. The computational method of claim 1 , wherein the rhythmic skeleton corresponds to a pulse train encoding of tempo of the target song. | 0.869565 |
8,775,436 | 29 | 30 | 29. A computer-readable memory device including computer-executable instructions, the computer-executable instructions comprising: one or more instructions which, when executed by one or more processors, cause the one or more processors to identify a plurality of images associated with a document; one or more instructions which, when executed by the one or more processors, cause the one or more processors to determine a host associated with the document; one or more instructions which, when executed by the one or more processors, cause the one or more processors to detect captions associated with the plurality of images; one or more instructions which, when executed by the one or more processors, cause the one or more processors to identify an image, of the plurality of images, that is linked to by multiple other documents associated with the host and that has a caption that is unrelated to topics of the multiple other documents; one or more instructions which, when executed by the one or more processors, cause the one or more processors to discard the identified image to create a plurality of remaining images; one or more instructions which, when executed by the one or more processors, cause the one or more processors to select an image of the plurality of remaining images to link with the document based on the detected captions; and one or more instructions which, when executed by the one or more processors, cause the one or more processors to link the selected image with the document. | 29. A computer-readable memory device including computer-executable instructions, the computer-executable instructions comprising: one or more instructions which, when executed by one or more processors, cause the one or more processors to identify a plurality of images associated with a document; one or more instructions which, when executed by the one or more processors, cause the one or more processors to determine a host associated with the document; one or more instructions which, when executed by the one or more processors, cause the one or more processors to detect captions associated with the plurality of images; one or more instructions which, when executed by the one or more processors, cause the one or more processors to identify an image, of the plurality of images, that is linked to by multiple other documents associated with the host and that has a caption that is unrelated to topics of the multiple other documents; one or more instructions which, when executed by the one or more processors, cause the one or more processors to discard the identified image to create a plurality of remaining images; one or more instructions which, when executed by the one or more processors, cause the one or more processors to select an image of the plurality of remaining images to link with the document based on the detected captions; and one or more instructions which, when executed by the one or more processors, cause the one or more processors to link the selected image with the document. 30. The computer-readable memory device of claim 29 , where the one or more instructions to detect captions associated with the plurality of images include: one or more instructions to determine that a particular image, of the plurality of images, is located within a table of the document, one or more instructions to identify text within the table, and one or more instructions to use the identified text as the caption for the particular image. | 0.524468 |
9,613,027 | 1 | 2 | 1. A computer-implemented method, performed by at least one processor, for using training data in a first language to create training data in a second language, comprising: accessing the training data in the first language that include sentences that each comprises one or more carrier phrases, and one or more slot labels with slot values; performing slot abstraction on at least a portion of the training data to create a first plurality of abstract sentences that each comprises one or more carrier phrases, and one or more abstract tokens that replace the slot labels and the slot values; translating at least partially through machine translation the carrier phrases to the second language to generate a second plurality of abstract sentences in the second language; accessing a database of a plurality of locale-dependent entities based on a locale corresponding to the second language; replacing each of abstract tokens in the second plurality of abstract sentences in the second language with multiple locale-dependent entities from the plurality of locale-dependent entities for the slot type, in order to create a plurality of filled translated sentences for inclusion in the training data in the second language; training a locale-dependent statistical model based on the training data in the second language; and recognizing speech in the second language based on the locale-dependent statistical model. | 1. A computer-implemented method, performed by at least one processor, for using training data in a first language to create training data in a second language, comprising: accessing the training data in the first language that include sentences that each comprises one or more carrier phrases, and one or more slot labels with slot values; performing slot abstraction on at least a portion of the training data to create a first plurality of abstract sentences that each comprises one or more carrier phrases, and one or more abstract tokens that replace the slot labels and the slot values; translating at least partially through machine translation the carrier phrases to the second language to generate a second plurality of abstract sentences in the second language; accessing a database of a plurality of locale-dependent entities based on a locale corresponding to the second language; replacing each of abstract tokens in the second plurality of abstract sentences in the second language with multiple locale-dependent entities from the plurality of locale-dependent entities for the slot type, in order to create a plurality of filled translated sentences for inclusion in the training data in the second language; training a locale-dependent statistical model based on the training data in the second language; and recognizing speech in the second language based on the locale-dependent statistical model. 2. The method of claim 1 , wherein translating the carrier phrases to the second language comprises using a domain specific translator. | 0.892687 |
8,756,276 | 4 | 5 | 4. The computer-implemented method of claim 1 , wherein identifying the higher frequency of user interactions with the first set of notifications comprises: identifying patterns in the user interactions with the first set of notifications, the patterns describing the characteristics of the interactions of the user with the first set of notifications. | 4. The computer-implemented method of claim 1 , wherein identifying the higher frequency of user interactions with the first set of notifications comprises: identifying patterns in the user interactions with the first set of notifications, the patterns describing the characteristics of the interactions of the user with the first set of notifications. 5. The computer-implemented method of claim 4 , wherein identifying the patterns in the user interactions comprises: identifying a type of content object from the first set of notifications most frequently interacted with by the user; and providing the second set of notifications of third-party content objects of the identified type of content object to the client device. | 0.872703 |
8,180,626 | 1 | 6 | 1. A method comprising: determining, by one or more computing devices, which human writing system is associated with text characters in a string of one or more text characters based on values representing the text characters; when said values are associated with more than one human language, comparing, by the one or more computing devices, the string with a targeted dictionary to identify a particular said human language associated with the string; and designating, by the one or more computing devices, which linguistic services are available based on one or more service properties of the linguistic services and based on the particular said human language associated with the string. | 1. A method comprising: determining, by one or more computing devices, which human writing system is associated with text characters in a string of one or more text characters based on values representing the text characters; when said values are associated with more than one human language, comparing, by the one or more computing devices, the string with a targeted dictionary to identify a particular said human language associated with the string; and designating, by the one or more computing devices, which linguistic services are available based on one or more service properties of the linguistic services and based on the particular said human language associated with the string. 6. The method of claim 1 , further comprising identifying the particular said human language by scoring, with a frequency module, weighted values for substrings in the string. | 0.857026 |
8,091,028 | 26 | 27 | 26. The apparatus of claim 22 , wherein said computer readable instructions further comprise instructions for causing said processor to perform the functions of a word processing application configured to associate one of a plurality of voices to individual lines within said line-based text document, wherein said text-to-speech converter is configured to use a respectively associated voice when converting each line of said line-based text document. | 26. The apparatus of claim 22 , wherein said computer readable instructions further comprise instructions for causing said processor to perform the functions of a word processing application configured to associate one of a plurality of voices to individual lines within said line-based text document, wherein said text-to-speech converter is configured to use a respectively associated voice when converting each line of said line-based text document. 27. The apparatus of claim 26 , wherein said word processing application comprises a plurality of styles by which said plurality of voices may be associated with said lines of said line-based text document. | 0.929355 |
7,802,238 | 12 | 14 | 12. A method for developing and executing supervisory process control and manufacturing information applications including application object scripts derived from multiple different scripting languages, the method comprising: specifying, by a script editor interface, scripts for application objects, wherein the script editor interface supports multiple distinct user-side script languages; rendering, by a script translation component, execution-side script of a single execution-side scripting language from source script rendered by the script editor and written according to any of a set of user-side script languages, the set of user-side script languages including at least: a first scripting language, and a second scripting language; and executing, by a scripting engine, the execution-side script of the single execution-side scripting language generated by the script translation component for the first scripting language and the second scripting language. | 12. A method for developing and executing supervisory process control and manufacturing information applications including application object scripts derived from multiple different scripting languages, the method comprising: specifying, by a script editor interface, scripts for application objects, wherein the script editor interface supports multiple distinct user-side script languages; rendering, by a script translation component, execution-side script of a single execution-side scripting language from source script rendered by the script editor and written according to any of a set of user-side script languages, the set of user-side script languages including at least: a first scripting language, and a second scripting language; and executing, by a scripting engine, the execution-side script of the single execution-side scripting language generated by the script translation component for the first scripting language and the second scripting language. 14. The method of claim 12 wherein the script translation component supports designating attributes using relative identifiers. | 0.808735 |
8,250,079 | 1 | 6 | 1. A method for identifying near and exact-duplicate documents in a document collection, the method comprising: for each document in the collection performing by a computer the steps of: reading textual content from the document; filtering the textual content based on user settings; determining N most frequent words from the filtered textual content of the document to generate a first most frequent, word- 1 , to an Nth most frequent word, word-N, sorted from highest to lowest frequency; performing a quorum search using the N most frequent words from the filtered textual content in the document with a threshold M, wherein the threshold M is used to retrieve documents from the document collection having a number M of the N most frequent words; sorting results from the quorum search based on relevancy, whereby based on the values of N and M near and exact-duplicate documents are identified in the document collection; and determining the relevancy by taking a number of hits for the quorum search in the document and dividing the number of hits by a size of the document in kilobytes of text in the document or a size in kilobytes for the entire document. | 1. A method for identifying near and exact-duplicate documents in a document collection, the method comprising: for each document in the collection performing by a computer the steps of: reading textual content from the document; filtering the textual content based on user settings; determining N most frequent words from the filtered textual content of the document to generate a first most frequent, word- 1 , to an Nth most frequent word, word-N, sorted from highest to lowest frequency; performing a quorum search using the N most frequent words from the filtered textual content in the document with a threshold M, wherein the threshold M is used to retrieve documents from the document collection having a number M of the N most frequent words; sorting results from the quorum search based on relevancy, whereby based on the values of N and M near and exact-duplicate documents are identified in the document collection; and determining the relevancy by taking a number of hits for the quorum search in the document and dividing the number of hits by a size of the document in kilobytes of text in the document or a size in kilobytes for the entire document. 6. The method of claim 1 , further comprising calculating N based on a recall percentage value user setting by multiplying the percentage value times a number of total words in the filtered text; or calculating N based on a recall percentage value user setting by multiplying the percentage value times a number of unique words in the filtered text; and calculating M based on a precision value percentage user setting by multiplying the percentage value times the N value. | 0.59083 |
9,886,420 | 1 | 3 | 1. A computer system for creating photo stories, comprising: a computer storage configured to store a plurality of photo story design templates characterized by attributes of multiple pages and numbers of photos that the photo story design templates are respectively configured to incorporate across the multiple pages therein; and a computer processor configured to obtain a plurality of photos and metadata associated with the photos, to analyze the plurality of photos, or the metadata, or a combination thereof by the computer system to produce an analysis result, to subdivide the plurality of photos to produce a group of photos based on the analysis result, to automatically select a photo story design template from the plurality of photo story design templates based, at least in part, on number of photos in the group of photos to be placed across the multiple pages, and to incorporate the group of photos into the photo story design template across the multiple pages to produce a photo story. | 1. A computer system for creating photo stories, comprising: a computer storage configured to store a plurality of photo story design templates characterized by attributes of multiple pages and numbers of photos that the photo story design templates are respectively configured to incorporate across the multiple pages therein; and a computer processor configured to obtain a plurality of photos and metadata associated with the photos, to analyze the plurality of photos, or the metadata, or a combination thereof by the computer system to produce an analysis result, to subdivide the plurality of photos to produce a group of photos based on the analysis result, to automatically select a photo story design template from the plurality of photo story design templates based, at least in part, on number of photos in the group of photos to be placed across the multiple pages, and to incorporate the group of photos into the photo story design template across the multiple pages to produce a photo story. 3. The computer system of claim 1 , wherein computer processor is configured to automatically determine the number of photos in the group of photos by the computer system. | 0.790954 |
10,083,227 | 1 | 9 | 1. A computer system comprising one or more processing units and at least one memory coupled to the one or more processing units, the computer system programmed to perform operations comprising: receiving, through a graphical user interface, input from a user for a search area for a database search, the input for the search area including a search area string received from user input and comprising one or more key words; converting the search area string into first query language operations, stored in the at least one memory, when executed by the one or more processing units, the first query language operations configured to identify one or more database tables of plural available database tables of a database, the plural available database tables associated with one or more respective data objects, stored in the at least one memory, storing description information for respective database tables, the identified database tables having one or more data objects storing description information matching at least a portion of the search area string; executing the first query language operations, the executing comprising: accessing the description information for the plural available database tables through respective data objects, the description information comprising, and stored in the respective one or more data objects, one or more of; (1) names of the plural available database tables, (2) text descriptions of the plural available database tables, and (3) data definitions for fields of the plural available database tables; determining the one or more of the plural available database tables that have description information matching the at least a portion of the search area string by comparing, using the one or more processing units, the search area string, according to operations specified by the first query language operations, with the one or more data objects stored in the at least one memory, wherein identifying information for tables determined to have matching description information is appended to first query execution results; generating first query execution results comprising the identifying information, retrieved from at least a portion of the one or more data objects stored in the at least one memory, of the determined one or more of the plural available tables; receiving, through the graphical user interface, input, comprising one or more keywords, from the user for a search string to be executed only against at least a portion of the determined one or more of the plural available tables of the first query execution results, the at least a portion of the determined one or more of the plural available tables of the first query execution results being all of the one or more of the plural available tables of the first query execution results or a portion of the plural available tables of the first query execution results selected by a user through user input received through the graphical user interface; converting the search string into second query language operations, stored in the at least one memory, when executed by the one or more processing units, the second query language operations configured to identify data stored in the at least a portion of the determined one or more of the plurality of available tables of the first query execution results having a relationship with the search string specified by at least a portion of the second query language operations; executing the second query language operations to generate second query results the executing comprising: for each table of the at least a portion of the first query execution results, each table having a plurality of fields, analyzing each field of the respective table to determine whether it can be searched to determine if values of the field have the specified relationship with the search string; for fields that can be searched, searching the table for records having the specified relationship for the respective field; and adding at least a portion of records having the specified relationship to the second query results; and returning the second query results to the user. | 1. A computer system comprising one or more processing units and at least one memory coupled to the one or more processing units, the computer system programmed to perform operations comprising: receiving, through a graphical user interface, input from a user for a search area for a database search, the input for the search area including a search area string received from user input and comprising one or more key words; converting the search area string into first query language operations, stored in the at least one memory, when executed by the one or more processing units, the first query language operations configured to identify one or more database tables of plural available database tables of a database, the plural available database tables associated with one or more respective data objects, stored in the at least one memory, storing description information for respective database tables, the identified database tables having one or more data objects storing description information matching at least a portion of the search area string; executing the first query language operations, the executing comprising: accessing the description information for the plural available database tables through respective data objects, the description information comprising, and stored in the respective one or more data objects, one or more of; (1) names of the plural available database tables, (2) text descriptions of the plural available database tables, and (3) data definitions for fields of the plural available database tables; determining the one or more of the plural available database tables that have description information matching the at least a portion of the search area string by comparing, using the one or more processing units, the search area string, according to operations specified by the first query language operations, with the one or more data objects stored in the at least one memory, wherein identifying information for tables determined to have matching description information is appended to first query execution results; generating first query execution results comprising the identifying information, retrieved from at least a portion of the one or more data objects stored in the at least one memory, of the determined one or more of the plural available tables; receiving, through the graphical user interface, input, comprising one or more keywords, from the user for a search string to be executed only against at least a portion of the determined one or more of the plural available tables of the first query execution results, the at least a portion of the determined one or more of the plural available tables of the first query execution results being all of the one or more of the plural available tables of the first query execution results or a portion of the plural available tables of the first query execution results selected by a user through user input received through the graphical user interface; converting the search string into second query language operations, stored in the at least one memory, when executed by the one or more processing units, the second query language operations configured to identify data stored in the at least a portion of the determined one or more of the plurality of available tables of the first query execution results having a relationship with the search string specified by at least a portion of the second query language operations; executing the second query language operations to generate second query results the executing comprising: for each table of the at least a portion of the first query execution results, each table having a plurality of fields, analyzing each field of the respective table to determine whether it can be searched to determine if values of the field have the specified relationship with the search string; for fields that can be searched, searching the table for records having the specified relationship for the respective field; and adding at least a portion of records having the specified relationship to the second query results; and returning the second query results to the user. 9. The computer system of claim 1 , wherein results of the database search indicate real-time status of the database. | 0.929688 |
8,949,125 | 7 | 8 | 7. A method of selecting a user spoken utterance, comprising: receiving, at a processing device, a plurality of user spoken utterances of a text string, each user spoken utterance being a pronunciation of the text string by a corresponding different user and comprising a location name or a point of interest; the processing device generating a speech model for each received user spoken utterance from each corresponding user; the processing device measuring a distance value between each of the generated speech models and every other generated speech model; the processing device selecting a given one of the user spoken utterances, as a most typical pronunciation of the text string, based on the measured distance values between the speech model for the selected user spoken utterance and every other generated speech model, wherein selecting the given user spoken utterance based on the measured distance values includes identifying either: a sequence of modeling states from one user spoken utterance having a shortest average distance from other sequences for all other user spoken utterances in the plurality of user spoken utterances, or a sequence of modeling states from one user spoken utterance having a lowest average distance from other sequences for all other user spoken utterances in the plurality of user spoken utterances; annotating a mapping application with the selected user spoken utterance; and providing audible output of the text string based on the selected user spoken utterance in response to a user input. | 7. A method of selecting a user spoken utterance, comprising: receiving, at a processing device, a plurality of user spoken utterances of a text string, each user spoken utterance being a pronunciation of the text string by a corresponding different user and comprising a location name or a point of interest; the processing device generating a speech model for each received user spoken utterance from each corresponding user; the processing device measuring a distance value between each of the generated speech models and every other generated speech model; the processing device selecting a given one of the user spoken utterances, as a most typical pronunciation of the text string, based on the measured distance values between the speech model for the selected user spoken utterance and every other generated speech model, wherein selecting the given user spoken utterance based on the measured distance values includes identifying either: a sequence of modeling states from one user spoken utterance having a shortest average distance from other sequences for all other user spoken utterances in the plurality of user spoken utterances, or a sequence of modeling states from one user spoken utterance having a lowest average distance from other sequences for all other user spoken utterances in the plurality of user spoken utterances; annotating a mapping application with the selected user spoken utterance; and providing audible output of the text string based on the selected user spoken utterance in response to a user input. 8. The method of claim 7 , wherein the generated speech models are Hidden Markov Models. | 0.870588 |
7,711,571 | 15 | 21 | 15. An apparatus comprising: a language translation device that includes a database configured to accommodate translation data, the language translation device being equipped to provide a number of language translation services to a user, and the language translation device being responsive to a contextual translation data update signal that updates the database; an electronic data input and output module, configured to provide the contextual translation data update signal to the language translation device, the electronic data input and output module being responsive to a context change signal indicative that the database may need to be updated; and a context comparator configured to provide the context change signal if the translation data is insufficient to cover a present or anticipated context of the apparatus, wherein the contextual translation data update signal is input into the apparatus, and the context change signal is output from the apparatus, wherein the present or anticipated context is a setting in a country having a primary language different from a language in which the user is fluent, and wherein said updates include adding to the database a selected subset of phrases that are suitable for said setting, and removing from the database another selected subset of phrases that are irrelevant to said setting, and said setting includes a temperature. | 15. An apparatus comprising: a language translation device that includes a database configured to accommodate translation data, the language translation device being equipped to provide a number of language translation services to a user, and the language translation device being responsive to a contextual translation data update signal that updates the database; an electronic data input and output module, configured to provide the contextual translation data update signal to the language translation device, the electronic data input and output module being responsive to a context change signal indicative that the database may need to be updated; and a context comparator configured to provide the context change signal if the translation data is insufficient to cover a present or anticipated context of the apparatus, wherein the contextual translation data update signal is input into the apparatus, and the context change signal is output from the apparatus, wherein the present or anticipated context is a setting in a country having a primary language different from a language in which the user is fluent, and wherein said updates include adding to the database a selected subset of phrases that are suitable for said setting, and removing from the database another selected subset of phrases that are irrelevant to said setting, and said setting includes a temperature. 21. The apparatus of claim 15 , wherein the apparatus is configured to provide the language translation assistance, after the update signal updates the database, without requiring support from any language translation resource external to the apparatus. | 0.531481 |
7,640,240 | 1 | 2 | 1. A method comprising: receiving a portion of content of an electronic document; analyzing the portion of the content to identify one or more predetermined words in the portion; associating the one or more predetermined words with contextually relevant information including a coupon information; augmenting the portion with the coupon information including linking the portion to one or more coupons associated with the coupon information by adding a script to the portion, wherein executing the script in a browser causes the browser to generate and display a user interface element in association with each of the one or more predetermined words or the content, receive user input selecting the user interface element with a particular one of the words, select a coupon offer for the one or more coupons that is contextually relevant to the selected particular one of the words, display the coupon offer for the one or more coupons in a window over the portion of content, and download the one or more coupons to the browser; wherein the method is performed by one or more computers. | 1. A method comprising: receiving a portion of content of an electronic document; analyzing the portion of the content to identify one or more predetermined words in the portion; associating the one or more predetermined words with contextually relevant information including a coupon information; augmenting the portion with the coupon information including linking the portion to one or more coupons associated with the coupon information by adding a script to the portion, wherein executing the script in a browser causes the browser to generate and display a user interface element in association with each of the one or more predetermined words or the content, receive user input selecting the user interface element with a particular one of the words, select a coupon offer for the one or more coupons that is contextually relevant to the selected particular one of the words, display the coupon offer for the one or more coupons in a window over the portion of content, and download the one or more coupons to the browser; wherein the method is performed by one or more computers. 2. The method of claim 1 , further comprising receiving one or more keywords, the one or more keywords being associated with the coupon information. | 0.885093 |
8,934,652 | 29 | 30 | 29. The method of claim 1 , further comprising: receiving data representing an ongoing conversation amongst multiple speakers; identifying the multiple speakers based on the data representing the ongoing conversation; and as each of the multiple speakers takes a turn speaking during the ongoing conversation, informing the user of a name or other speaker-related information associated with the speaker. | 29. The method of claim 1 , further comprising: receiving data representing an ongoing conversation amongst multiple speakers; identifying the multiple speakers based on the data representing the ongoing conversation; and as each of the multiple speakers takes a turn speaking during the ongoing conversation, informing the user of a name or other speaker-related information associated with the speaker. 30. The method of claim 29 , wherein the receiving data representing an ongoing conversation amongst multiple speakers includes: receiving audio data from a telephonic conference call, the received audio data representing utterances made by at least one of the multiple speakers. | 0.840571 |
8,843,466 | 12 | 13 | 12. The method of claim 11 , wherein generating the one or more attribute suggestions comprises: identifying a respective number of references to each attribute in the plurality of resources; ranking the attributes based at least in part on the respective numbers of references; and selecting one or more attributes as being attribute suggestions based on the ranking. | 12. The method of claim 11 , wherein generating the one or more attribute suggestions comprises: identifying a respective number of references to each attribute in the plurality of resources; ranking the attributes based at least in part on the respective numbers of references; and selecting one or more attributes as being attribute suggestions based on the ranking. 13. The method of claim 12 , further comprising: identifying respective associated entities and respective associated attributes that are associated with each of the attributes; determining that a total number of associated entities and a total number of associated attributes associated with both a first attribute and a second, lower-ranked attribute exceeds a specified threshold value; and demoting the second, lower-ranked attribute in the ranking. | 0.857458 |
8,316,030 | 9 | 12 | 9. A method of operating a computerized document search system where information is matched against a database containing documents in response to user queries, comprising the steps of: (a) receiving a query identifying a source document that has information content related to the documents within the database; (b) automatically detecting at least one important word within the source document identified as a SearchWord wherein the SearchWord is selected in part by using a WordRatio of the SearchWord related to a topic area and a number of topic areas that contain the SearchWord; (c) processing the documents in the database in which an importance value of the at least one important word within the source document is related to the WordRatio and at least one value selected from a group of values consisting of: a value defined for the at least one important word related to a document section that occurs in a document being processed from the processed documents; a value defined for the at least one important word in at least one classification associated with the document being processed; a value defined for the at least one important word in a document type that applies to the document being processed; a value defined for the at least one important word across multiple document classifications; and a value based on statistical occurrence of the at least one important word across at least two different documents; (d) generating a score for the processed document based partly on the value of the SearchWord in the processed document; creating a document list having the processed document identified that is related to the source document and an indication of a quality of match between the source document and a related document, and using, by a Presentation Manager, the document list to show identity of the processed document from the document list to the user of the user queries. | 9. A method of operating a computerized document search system where information is matched against a database containing documents in response to user queries, comprising the steps of: (a) receiving a query identifying a source document that has information content related to the documents within the database; (b) automatically detecting at least one important word within the source document identified as a SearchWord wherein the SearchWord is selected in part by using a WordRatio of the SearchWord related to a topic area and a number of topic areas that contain the SearchWord; (c) processing the documents in the database in which an importance value of the at least one important word within the source document is related to the WordRatio and at least one value selected from a group of values consisting of: a value defined for the at least one important word related to a document section that occurs in a document being processed from the processed documents; a value defined for the at least one important word in at least one classification associated with the document being processed; a value defined for the at least one important word in a document type that applies to the document being processed; a value defined for the at least one important word across multiple document classifications; and a value based on statistical occurrence of the at least one important word across at least two different documents; (d) generating a score for the processed document based partly on the value of the SearchWord in the processed document; creating a document list having the processed document identified that is related to the source document and an indication of a quality of match between the source document and a related document, and using, by a Presentation Manager, the document list to show identity of the processed document from the document list to the user of the user queries. 12. The method of claim 9 , further comprising the step of the Presentation Manager displaying information from the source document to the user. | 0.732342 |
8,593,406 | 4 | 5 | 4. The interchangeable input module of claim 1 , wherein the storage component is further configured to store a linguistic structure associated with the language, the structure having one or more of a plurality of character strings, at least some of which are words of the language, and/or menus and other components related to the language, and the interface is further configured to electrically provide the linguistic structure to the base device after the interchangeable input module is mated with the base device. | 4. The interchangeable input module of claim 1 , wherein the storage component is further configured to store a linguistic structure associated with the language, the structure having one or more of a plurality of character strings, at least some of which are words of the language, and/or menus and other components related to the language, and the interface is further configured to electrically provide the linguistic structure to the base device after the interchangeable input module is mated with the base device. 5. The interchangeable input module of claim 4 , wherein the storage component is further configured to store predictive logic capable of predicting one or more of the character strings of the language structure based on one or more user actuations of at least one of the plurality of inputs, and the interface is further configured to electrically provide the predictive logic to the base device after the interchangeable input module is mated with the base device. | 0.81449 |
8,683,348 | 1 | 8 | 1. A computer-implemented method for modifying a user experience associated with a software product, comprising: collecting behavioral metrics that are associated with a user's emotional state while the user is using the software product; determining, using a computer, the emotional state based on the collected behavioral metrics; and modifying the user experience based on the determined emotional state by changing a path in a process associated with the software product, wherein said changing involves modifying a flow in the software product so that at least a different user interface is presented based on the emotional state, wherein the different user interface includes additional content in the software product that enables the user to provide user inputs to the document with ease. | 1. A computer-implemented method for modifying a user experience associated with a software product, comprising: collecting behavioral metrics that are associated with a user's emotional state while the user is using the software product; determining, using a computer, the emotional state based on the collected behavioral metrics; and modifying the user experience based on the determined emotional state by changing a path in a process associated with the software product, wherein said changing involves modifying a flow in the software product so that at least a different user interface is presented based on the emotional state, wherein the different user interface includes additional content in the software product that enables the user to provide user inputs to the document with ease. 8. The method of claim 1 , wherein determining the emotional state involves selecting one of a set of predefined emotional states. | 0.917408 |
7,840,546 | 26 | 32 | 26. A method for optimizing data queries for related records in a reliable fashion, to be used with a system having a first computing device communicatively coupled with a second and a third computing device, and communicatively coupled to a first database that stores real-world entity data, having said second computing device communicatively coupled with said first and said third computing device, and communicatively coupled to a second database that stores real-world entity data, having said third computing device communicatively coupled with said first and said second computing device, and communicatively coupled to a third database that stores real-world entity data, a first end-user interface communicatively coupled to said first database, a second end-user interface communicatively coupled to said second database, and a third end-user interface communicatively coupled to said third database, comprising: providing a hierarchical system of Consolidation Strings for said first database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said first database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said first database, acting as a first data-source node in the overall system, by periodically communicating its Consolidation Strings to other data-source nodes; providing a hierarchical system of Consolidation Strings for said second database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said second database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said second database, acting as a second data-source node in the overall system, by periodically communicating its Consolidation Strings to other data-source nodes; providing a hierarchical system of Consolidation Strings for said third database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said third database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said third database, acting as a third data-source node in the overall system, by periodically communicating its Consolidation Strings to other data-source nodes; providing the capability of said first end-user interface to allow a first end-user to query said first data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said second and third data-source nodes, wherein said first data-source node communicates consolidation information to said second and third data-source nodes, wherein said consolidation information is applied against a consolidation algorithm in each said second and third data-source nodes, and wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view; providing the capability of said second end-user interface to allow a second end-user to query said second data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said first and third data-source nodes, wherein said second data-source node communicates consolidation information to said first and third data-source nodes, wherein said consolidation information is applied against a consolidation algorithm in each said first and third data-source nodes, and wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view; and providing the capability of said third end-user interface to allow a third end-user to query said third data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said first and second data-source nodes, wherein said third data-source node communicates consolidation information to said first and second data-source nodes, wherein said consolidation information is applied against a consolidation algorithm in each said first and second data-source nodes, wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view. | 26. A method for optimizing data queries for related records in a reliable fashion, to be used with a system having a first computing device communicatively coupled with a second and a third computing device, and communicatively coupled to a first database that stores real-world entity data, having said second computing device communicatively coupled with said first and said third computing device, and communicatively coupled to a second database that stores real-world entity data, having said third computing device communicatively coupled with said first and said second computing device, and communicatively coupled to a third database that stores real-world entity data, a first end-user interface communicatively coupled to said first database, a second end-user interface communicatively coupled to said second database, and a third end-user interface communicatively coupled to said third database, comprising: providing a hierarchical system of Consolidation Strings for said first database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said first database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said first database, acting as a first data-source node in the overall system, by periodically communicating its Consolidation Strings to other data-source nodes; providing a hierarchical system of Consolidation Strings for said second database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said second database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said second database, acting as a second data-source node in the overall system, by periodically communicating its Consolidation Strings to other data-source nodes; providing a hierarchical system of Consolidation Strings for said third database, wherein each Consolidation String in said hierarchical system represents one or more key pieces of information relating to a real-world entity stored in said third database, wherein the information represented in each Consolidation String is in a character format, wherein the hierarchical ranking of Consolidation String priorities are used to optimize database queries to find matching records for at least one entity of interest with substantial certainty, and wherein Inter-Node Consolidation is set up for said third database, acting as a third data-source node in the overall system, by periodically communicating its Consolidation Strings to other data-source nodes; providing the capability of said first end-user interface to allow a first end-user to query said first data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said second and third data-source nodes, wherein said first data-source node communicates consolidation information to said second and third data-source nodes, wherein said consolidation information is applied against a consolidation algorithm in each said second and third data-source nodes, and wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view; providing the capability of said second end-user interface to allow a second end-user to query said second data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said first and third data-source nodes, wherein said second data-source node communicates consolidation information to said first and third data-source nodes, wherein said consolidation information is applied against a consolidation algorithm in each said first and third data-source nodes, and wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view; and providing the capability of said third end-user interface to allow a third end-user to query said third data-source node, which in turn queries any associated Consolidated Strings associated with the query for the entity to identify related records contained in said first and second data-source nodes, wherein said third data-source node communicates consolidation information to said first and second data-source nodes, wherein said consolidation information is applied against a consolidation algorithm in each said first and second data-source nodes, wherein said consolidation algorithm looks for a pair of entity records with Consolidation Strings on the same priority level that are character-wise identical, and when such an entity match is found, said matching entity records are consolidated from an end-user's point of view. 32. The method in claim 26 , wherein said Inter-Node Consolidation is set up by communicating updated Consolidation Strings to other data-source nodes in a peer-to-peer fashion. | 0.805921 |
8,005,294 | 29 | 30 | 29. A method for recognizing unconstrained cursive handwritten words, comprising: processing an image of a handwritten Arabic word of one or more characters, the processing step including segmenting the imaged word into a set of one or more segments and determining a sequence of segments using an over-segmentation-relabeling algorithm; after the processing step, extracting feature information from one segment or a combination of several consecutive segments of the image word processed in the processing step, wherein the feature information includes at least one of aspect ratio features, location and number of disconnected dots, stroke connectedness features and chain code features, wherein the aspect ratio features include two aspect ratio features, ƒ hv and ƒ vh , which are computed by finding maximum vertical extent (vd) and maximum horizontal extent (hd) of the character, wherein feature ƒ hv is based on a horizontal to vertical aspect ratio, and feature ƒ vh is based on a vertical to horizontal aspect ratio, wherein the location and number of disconnected dots includes three features, ƒ du , ƒ dm , and ƒ dl relating to the number of disconnected diacritics located in an upper zone, a middle zone, and a lower zone, respectively, of the one segment or the combination of several consecutive segments, wherein the stroke connectedness features include two stroke connectedness features, ƒ cr and ƒ cl , wherein the chain code features include three 8-directional chain code based features, ƒ ch , ƒ rough , and ƒ con ; repeating said extracting step until feature information from segments or combinations thereof have been extracted; and classifying the imaged word as having a string of one or more characters using the extracted feature information. | 29. A method for recognizing unconstrained cursive handwritten words, comprising: processing an image of a handwritten Arabic word of one or more characters, the processing step including segmenting the imaged word into a set of one or more segments and determining a sequence of segments using an over-segmentation-relabeling algorithm; after the processing step, extracting feature information from one segment or a combination of several consecutive segments of the image word processed in the processing step, wherein the feature information includes at least one of aspect ratio features, location and number of disconnected dots, stroke connectedness features and chain code features, wherein the aspect ratio features include two aspect ratio features, ƒ hv and ƒ vh , which are computed by finding maximum vertical extent (vd) and maximum horizontal extent (hd) of the character, wherein feature ƒ hv is based on a horizontal to vertical aspect ratio, and feature ƒ vh is based on a vertical to horizontal aspect ratio, wherein the location and number of disconnected dots includes three features, ƒ du , ƒ dm , and ƒ dl relating to the number of disconnected diacritics located in an upper zone, a middle zone, and a lower zone, respectively, of the one segment or the combination of several consecutive segments, wherein the stroke connectedness features include two stroke connectedness features, ƒ cr and ƒ cl , wherein the chain code features include three 8-directional chain code based features, ƒ ch , ƒ rough , and ƒ con ; repeating said extracting step until feature information from segments or combinations thereof have been extracted; and classifying the imaged word as having a string of one or more characters using the extracted feature information. 30. The method of claim 29 , wherein the feature information includes the aspect ratio features. | 0.900415 |
8,055,591 | 21 | 25 | 21. The system of claim 20 , wherein said presentation module configured to present the data indicative of the inferred mental state of the authoring user comprises: a presentation module configured to present the data indicative of the inferred mental state of the authoring user to the authoring user. | 21. The system of claim 20 , wherein said presentation module configured to present the data indicative of the inferred mental state of the authoring user comprises: a presentation module configured to present the data indicative of the inferred mental state of the authoring user to the authoring user. 25. The system of claim 21 , wherein said presentation module configured to present the data indicative of the inferred mental state of the authoring user to the authoring user comprises: a presentation module configured to display at least one of a symbolic representation or a number indicative of the inferred mental state of the authoring user to the authoring user. | 0.747956 |
9,117,174 | 7 | 9 | 7. The non-transitory computer-readable storage medium of claim 5 , wherein the graph search involves incrementally extending multiple independent search paths such that a search path is extended at each increment and such that a same search path is extended continuously until a first occurrence of any of the following conditions: an end of the continuously extended search path is reached; an encountered node represents an association rule that does not satisfy an information gain improvement criteria; and an encountered node represents an association rule that is not improvable through further expansion of the continuously extended search path. | 7. The non-transitory computer-readable storage medium of claim 5 , wherein the graph search involves incrementally extending multiple independent search paths such that a search path is extended at each increment and such that a same search path is extended continuously until a first occurrence of any of the following conditions: an end of the continuously extended search path is reached; an encountered node represents an association rule that does not satisfy an information gain improvement criteria; and an encountered node represents an association rule that is not improvable through further expansion of the continuously extended search path. 9. The non-transitory computer-readable storage medium of claim 7 , wherein the graph search is a depth-first search subject to constraints that limit expansion at any single node to a maximum number of nodes. | 0.938348 |
7,953,591 | 13 | 14 | 13. A computer program product embodied in a non-transitory computer readable storage medium for automatically identifying unique language independent keys comprising the programming steps of: extracting language independent keys and associated text strings from resource files; inserting said extracted language independent keys and associated text strings in a file; receiving a first value of a first locale; searching for language independent keys in said file associated with said received first value of said first locale; identifying a plurality of language independent keys associated with said received first value of said first locale; identifying a second locale to narrow a number of said plurality of language independent keys; receiving a second value of a second locale; searching for language independent keys out of said plurality of language independent keys that are associated with said received first value of said first locale and associated with said received second value of said second locale; and identifying one or more of said plurality of language independent keys that are associated with said first value of said first locale and associated with said second value of said second locale. | 13. A computer program product embodied in a non-transitory computer readable storage medium for automatically identifying unique language independent keys comprising the programming steps of: extracting language independent keys and associated text strings from resource files; inserting said extracted language independent keys and associated text strings in a file; receiving a first value of a first locale; searching for language independent keys in said file associated with said received first value of said first locale; identifying a plurality of language independent keys associated with said received first value of said first locale; identifying a second locale to narrow a number of said plurality of language independent keys; receiving a second value of a second locale; searching for language independent keys out of said plurality of language independent keys that are associated with said received first value of said first locale and associated with said received second value of said second locale; and identifying one or more of said plurality of language independent keys that are associated with said first value of said first locale and associated with said second value of said second locale. 14. The computer program product as recited in claim 13 , wherein if only one of said one or more of said plurality of language independent keys is identified, then said one of said one or more of said plurality of language independent keys is a unique language independent key. | 0.68623 |
9,706,403 | 44 | 46 | 44. The apparatus of claim 37 , wherein the first alert is manually initiated by the supervision case manager via the remote server. | 44. The apparatus of claim 37 , wherein the first alert is manually initiated by the supervision case manager via the remote server. 46. The apparatus of claim 44 , wherein the software application further comprises instructions operable to cause the at least one processor to: prior to receiving the voluntary check-in: receive, from the remote server, a second alert requiring the enrollee to perform a second check-in; receive a second acknowledgement of the second alert from the enrollee; determine that the second acknowledgement has not been received within a pre-defined response period; and record, based on the determining, the second check-in as a missed check-in. | 0.787451 |
10,037,533 | 16 | 17 | 16. The non-transitory computer-readable storage medium of claim 15 , wherein in response to determining that the first count of the identified first plurality of relationships of the first merchant to one or more of the known fraudulent merchants is above the first threshold: generating an augmented first merchant electronic fingerprint for the first merchant based on the set of investigation information and the additional information. | 16. The non-transitory computer-readable storage medium of claim 15 , wherein in response to determining that the first count of the identified first plurality of relationships of the first merchant to one or more of the known fraudulent merchants is above the first threshold: generating an augmented first merchant electronic fingerprint for the first merchant based on the set of investigation information and the additional information. 17. The non-transitory computer-readable storage medium of claim 16 , wherein the second query against the data representing the first graph to identify the second plurality of relationships of the first merchant to one or more of the known fraudulent merchants in the data representing the first graph, is performed based on the augmented first merchant electronic fingerprint. | 0.91864 |
8,234,221 | 1 | 2 | 1. A graphical user interface, comprising: a first display region including a job description that includes at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; and a second display region including a matching resume that satisfies the job description, wherein, for each said at least one job requirement, the required skill or experience-related phrase is associated with at least one implying skill or experience-related phrase, wherein at least one searchable phrase is associated with each said at least one job requirement, one of said at least one searchable phrase including the required skill or experience-related phrase, and said at least one searchable phrase including each said at least one implying skill or experience-related phrase, wherein the matching resume is one of at least one resume, wherein each resume summarizes a candidate's career and qualification, wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer, wherein each said at least one resume includes at least one skill or experience-related phrase, an experience range for each said at least one skill or experience-related phrase determined by examining a use of each said at least one skill or experience-related phrase in the resume, and a computed term of experience for each said at least one skill or experience-related phrase based on the experience range, and wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range. | 1. A graphical user interface, comprising: a first display region including a job description that includes at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; and a second display region including a matching resume that satisfies the job description, wherein, for each said at least one job requirement, the required skill or experience-related phrase is associated with at least one implying skill or experience-related phrase, wherein at least one searchable phrase is associated with each said at least one job requirement, one of said at least one searchable phrase including the required skill or experience-related phrase, and said at least one searchable phrase including each said at least one implying skill or experience-related phrase, wherein the matching resume is one of at least one resume, wherein each resume summarizes a candidate's career and qualification, wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer, wherein each said at least one resume includes at least one skill or experience-related phrase, an experience range for each said at least one skill or experience-related phrase determined by examining a use of each said at least one skill or experience-related phrase in the resume, and a computed term of experience for each said at least one skill or experience-related phrase based on the experience range, and wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range. 2. The graphical user interface of claim 1 , wherein the second display region further includes a marking for at least one occurrence of the searchable phrase for each said at least one job requirement. | 0.502463 |
6,108,656 | 7 | 9 | 7. The method of claim 5 wherein said machine readable symbol also has encoded therein an encryption key associated with said source identifier data string, said encryption key is transposed by said computer input device, said transposed encryption key is used by said client computer to encrypt information specific to a user associated with said client computer, and said encrypted user information is assembled within said computer file transfer request word and transmitted to said target server computer. | 7. The method of claim 5 wherein said machine readable symbol also has encoded therein an encryption key associated with said source identifier data string, said encryption key is transposed by said computer input device, said transposed encryption key is used by said client computer to encrypt information specific to a user associated with said client computer, and said encrypted user information is assembled within said computer file transfer request word and transmitted to said target server computer. 9. The method of claim 7 wherein said machine readable symbol also has encoded therein user demographics data, said user demographics data correlated to a targeted user of said data carrier, said user demographics data is transposed by said computer input device, and wherein said information specific to a user is obtained, prior to encryption thereof, from said transposed user demographics data. | 0.837551 |
4,511,891 | 1 | 5 | 1. A system for converting amount information of plural digits from a numeric to a non-numerical symbolic representation thereof comprising: means for introducing amount information represented as a numerical character string; means for determining the order position of each numerical character representing said amount information; means, responsive to the order position of each numerical character determined by said means for determining, for generating non-numerical symbology representative of the order position of said amount information. | 1. A system for converting amount information of plural digits from a numeric to a non-numerical symbolic representation thereof comprising: means for introducing amount information represented as a numerical character string; means for determining the order position of each numerical character representing said amount information; means, responsive to the order position of each numerical character determined by said means for determining, for generating non-numerical symbology representative of the order position of said amount information. 5. The system of claim 1 wherein said non-numerical symbology is of the English, German or Japanese languages. | 0.833333 |
7,546,242 | 13 | 21 | 13. Audio documents reproduction apparatus comprising a means of command introduction; wherein the apparatus comprises a means of determination of at least one number of the group's representative documents, a means of calculation for partitioning documents into groups of documents possessing at least one similar audio characteristic, a means of determination of a determined number of documents representing each group, a means of calculation of positioning data associated with each document in a space, the data being determined by at least one characteristic specific to the document, a positioning datum also being assigned to the position of the user within the space, a means of selection of each document representing a group, the selected documents having a position situated at a distance less than a determined distance with respect to the position of the user in the space, a means of reproduction reproducing the identifiers of the several documents representing a group loopwise when the group is selected. | 13. Audio documents reproduction apparatus comprising a means of command introduction; wherein the apparatus comprises a means of determination of at least one number of the group's representative documents, a means of calculation for partitioning documents into groups of documents possessing at least one similar audio characteristic, a means of determination of a determined number of documents representing each group, a means of calculation of positioning data associated with each document in a space, the data being determined by at least one characteristic specific to the document, a positioning datum also being assigned to the position of the user within the space, a means of selection of each document representing a group, the selected documents having a position situated at a distance less than a determined distance with respect to the position of the user in the space, a means of reproduction reproducing the identifiers of the several documents representing a group loopwise when the group is selected. 21. Audio documents reproduction apparatus according to claim 13 ; wherein the means of reproduction sequentially reproduces each documents chosen during a determined period. | 0.835849 |
10,157,168 | 6 | 10 | 6. A method for formatting text, comprising: providing text input to a computer processor; providing a mapping input of keys and values by the computer processor, the keys each indicating at least one of the unique pseudo-syntactic hybrids, and the values indicating the uncertainties across word spaces adjacent to the keys; examining by the computer processor the text input to look for the keys in the mapping input; and formatting by the computer processor widths of the adjacent word spaces adjacent to the keys of the text input based on the outcome of the examining to improve a human reading experience, wherein the formatting of the widths of the adjacent spaces of the text input is determined by the values. | 6. A method for formatting text, comprising: providing text input to a computer processor; providing a mapping input of keys and values by the computer processor, the keys each indicating at least one of the unique pseudo-syntactic hybrids, and the values indicating the uncertainties across word spaces adjacent to the keys; examining by the computer processor the text input to look for the keys in the mapping input; and formatting by the computer processor widths of the adjacent word spaces adjacent to the keys of the text input based on the outcome of the examining to improve a human reading experience, wherein the formatting of the widths of the adjacent spaces of the text input is determined by the values. 10. The method of claim 6 , wherein the widths of the adjacent word spaces adjacent to the keys are adjusted by inserting an XHTML tag within an XHTML document. | 0.878419 |
8,713,541 | 1 | 6 | 1. A computer-implemented method for identifying matching elements between a source model and a target model, the method comprising: receiving a source model and a target model, the source model including one or more source elements and the target model including one or more targets elements, the source model and the target model each being stored in computer-readable memory; processing the source model and the target model based on two or more matching algorithms, the processing including: calculating, for each matching algorithm, a similarity value for each combination of the source element and the target element, and generating, for each matching algorithm, a similarity value matrix based on the similarity values associated with the matching algorithm; generating a similarity value cube based on the similarity value matrix associated with each matching algorithm; and identifying matching elements between the source model and the target model based on the similarity value cube. | 1. A computer-implemented method for identifying matching elements between a source model and a target model, the method comprising: receiving a source model and a target model, the source model including one or more source elements and the target model including one or more targets elements, the source model and the target model each being stored in computer-readable memory; processing the source model and the target model based on two or more matching algorithms, the processing including: calculating, for each matching algorithm, a similarity value for each combination of the source element and the target element, and generating, for each matching algorithm, a similarity value matrix based on the similarity values associated with the matching algorithm; generating a similarity value cube based on the similarity value matrix associated with each matching algorithm; and identifying matching elements between the source model and the target model based on the similarity value cube. 6. The method of claim 1 , wherein the processing further includes comparing, for each combination of the source element and the target element, an attribute of the source element to an attribute of the target element. | 0.844063 |
8,706,548 | 1 | 4 | 1. A system, comprising: at least one processor; one or more memories, operatively coupled to the processor, for storing logical instructions wherein execution of the logical instructions by the processor results in the performing of at least the following operations: receiving data indicative of search traffic directed to a website, the search traffic resulting from an unpaid portion of a search advertising campaign and a paid portion of the search advertising campaign, identifying a change made to the paid portion of the search advertising campaign, determining, based on the received data: a first volume of search traffic resulting from the unpaid portion before the change, a second volume of search traffic resulting from the unpaid portion after the change, a third volume of search traffic resulting from the paid portion before the change, and a fourth volume of search traffic resulting from the paid portion after the change; generating a synergy score based upon the first volume, the second volume, the third volume and the fourth volume, wherein the synergy score quantifies an impact of the change on the search traffic resulting from the unpaid portion; and storing the synergy score in the one or more memories in association with an indication of the change. | 1. A system, comprising: at least one processor; one or more memories, operatively coupled to the processor, for storing logical instructions wherein execution of the logical instructions by the processor results in the performing of at least the following operations: receiving data indicative of search traffic directed to a website, the search traffic resulting from an unpaid portion of a search advertising campaign and a paid portion of the search advertising campaign, identifying a change made to the paid portion of the search advertising campaign, determining, based on the received data: a first volume of search traffic resulting from the unpaid portion before the change, a second volume of search traffic resulting from the unpaid portion after the change, a third volume of search traffic resulting from the paid portion before the change, and a fourth volume of search traffic resulting from the paid portion after the change; generating a synergy score based upon the first volume, the second volume, the third volume and the fourth volume, wherein the synergy score quantifies an impact of the change on the search traffic resulting from the unpaid portion; and storing the synergy score in the one or more memories in association with an indication of the change. 4. The system of claim 1 wherein the change comprises beginning advertising for at least a first keyword. | 0.84139 |
9,189,568 | 7 | 11 | 7. A system comprising at least one server to: receive, for a plurality of item listings within a plurality of categories, item attributes expressed in a plurality of languages, each item attribute comprising an item attribute name and an item attribute value; convert the item attribute names and the item attribute values of the item attributes from the plurality of languages into language-independent symbols and store the item attributes for the plurality of item listings, expressed with the language-independent symbols, in an item listing table; receive one or more search attributes expressed in a language that is different from one or more of the plurality of languages of the item attributes, each search attribute comprising a search attribute name and a search attribute value; convert the search attribute name and the search attribute value of each of the one or more search attributes into the language-independent symbols; perform a search within the item listing table to identify at least one item listing with one or more item attributes expressed in the language-independent symbols that match the one or more search attributes expressed in the language-independent symbols; and display the item attributes of the at least one identified item listing in the language in which the search attributes as received were expressed. | 7. A system comprising at least one server to: receive, for a plurality of item listings within a plurality of categories, item attributes expressed in a plurality of languages, each item attribute comprising an item attribute name and an item attribute value; convert the item attribute names and the item attribute values of the item attributes from the plurality of languages into language-independent symbols and store the item attributes for the plurality of item listings, expressed with the language-independent symbols, in an item listing table; receive one or more search attributes expressed in a language that is different from one or more of the plurality of languages of the item attributes, each search attribute comprising a search attribute name and a search attribute value; convert the search attribute name and the search attribute value of each of the one or more search attributes into the language-independent symbols; perform a search within the item listing table to identify at least one item listing with one or more item attributes expressed in the language-independent symbols that match the one or more search attributes expressed in the language-independent symbols; and display the item attributes of the at least one identified item listing in the language in which the search attributes as received were expressed. 11. The system of claim 7 , wherein the language-independent symbols comprise numbers. | 0.926871 |
8,706,725 | 1 | 2 | 1. One or more computer-storage media devices storing computer-useable instructions that, when used by a computing device, cause the computing device to perform a method for using multiple contextual signals to re-rank search results, the method comprising: receiving a set of non-contextual search results generated as a result of a search query entered by a user; receiving a set of contextual signals that include user-specific features that can be used to re-rank documents in the set of non-contextual search results, the set of contextual signals being received from a source other than the user; prior to communicating the set of non-contextual search results for presentation to the user, evaluating each of the user-specific features by a machine-learning model to establish an importance or relevance of each of the user-specific features in relation to the user and the search query; comparing the importance or relevance of the user-specific features, by the machine-learning model, with a current position of each document in the set of non-contextual search results, wherein the machine-learning model uses one or more algorithms to learn which of the user-specific features are more important in re-ranking the documents in the set of non-contextual search results; based on the comparison, algorithmically determining a new position of each document in the set of non-contextual search results; and utilizing the new position of each document in the list of search results to generate a set of contextual search results. | 1. One or more computer-storage media devices storing computer-useable instructions that, when used by a computing device, cause the computing device to perform a method for using multiple contextual signals to re-rank search results, the method comprising: receiving a set of non-contextual search results generated as a result of a search query entered by a user; receiving a set of contextual signals that include user-specific features that can be used to re-rank documents in the set of non-contextual search results, the set of contextual signals being received from a source other than the user; prior to communicating the set of non-contextual search results for presentation to the user, evaluating each of the user-specific features by a machine-learning model to establish an importance or relevance of each of the user-specific features in relation to the user and the search query; comparing the importance or relevance of the user-specific features, by the machine-learning model, with a current position of each document in the set of non-contextual search results, wherein the machine-learning model uses one or more algorithms to learn which of the user-specific features are more important in re-ranking the documents in the set of non-contextual search results; based on the comparison, algorithmically determining a new position of each document in the set of non-contextual search results; and utilizing the new position of each document in the list of search results to generate a set of contextual search results. 2. The computer-storage media devices of claim 1 , wherein the contextual signals are received from two or more contextual signal providers. | 0.886179 |
9,037,472 | 14 | 22 | 14. A system for facilitating communications for a user transaction, the system comprising: a determining module configured to determine a goal transaction for a user to provide input to a human-to-machine interface, said determining module further configured to analyze the human-to-machine interface to determine one or more states and one or more navigation paths of a state machine of the human-to-machine interface defining available interactions for the user to interact with the human-to-machine interface, said determining module further configured to account for at least a subset of the states and associate the goal transaction with at least the one or more navigation paths of the state machine, the user reaching at least one end state of the one or more navigation paths via an individual interaction with a visual representation of a voice input parameter, the state machine operating in a manner consistent with the at least the subset of the states; a constructing module configured to construct and present the visual representation of the voice input parameter for the goal transaction based on at least the subset of the states, the visual representation of the voice input parameter representing multiple operations of the goal transaction optionally available for the user to employ to achieve interaction with the human-to-machine interface in fewer stages than through individual interactions with the human-to-machine interface; and wherein the visual representations enable user interaction with the human-to-machine interface. | 14. A system for facilitating communications for a user transaction, the system comprising: a determining module configured to determine a goal transaction for a user to provide input to a human-to-machine interface, said determining module further configured to analyze the human-to-machine interface to determine one or more states and one or more navigation paths of a state machine of the human-to-machine interface defining available interactions for the user to interact with the human-to-machine interface, said determining module further configured to account for at least a subset of the states and associate the goal transaction with at least the one or more navigation paths of the state machine, the user reaching at least one end state of the one or more navigation paths via an individual interaction with a visual representation of a voice input parameter, the state machine operating in a manner consistent with the at least the subset of the states; a constructing module configured to construct and present the visual representation of the voice input parameter for the goal transaction based on at least the subset of the states, the visual representation of the voice input parameter representing multiple operations of the goal transaction optionally available for the user to employ to achieve interaction with the human-to-machine interface in fewer stages than through individual interactions with the human-to-machine interface; and wherein the visual representations enable user interaction with the human-to-machine interface. 22. The system of claim 14 further comprising a communications interface configured to present the visual representation to the user, the communications interface enabling multi-mode communications with the human-to-machine interface. | 0.788427 |
9,098,476 | 1 | 2 | 1. A method comprising: identifying a logical tree contained within a structured document; identifying nodes of the logical tree; mapping the identified nodes into a logical structure, the logical structure populated with data in each of the identified nodes; and generating an observer structure for observing the data, the observer structure comprising a grid of cells that has a one-to-one structural correspondence with the nodes of the logical structure, with data in each of the nodes of the logical structure mapped into corresponding cells in the grid of cells, the grid of cells accommodating a required attribute and an optional attribute of an element contained in the logical tree, the optional attribute indicated by a null value in the grid of cells when the optional attribute is not present, wherein the observer structure comprises a table, and mapping the data in each of the nodes of the logical structure into corresponding cells in the grid of cells comprises a building of: a data-bound list binding to a first control, the data-bound list comprising a collection of nodes and corresponding to the table of the observer structure, the table having a plurality of rows and a plurality of columns, each row and column intersecting at a cell; a data-bound node binding to a second control, the data-bound node corresponding to a row in the observer structure; and a data-bound node property binding to a third control, the data-bound node property corresponding to a column value in the row of the observer structure. | 1. A method comprising: identifying a logical tree contained within a structured document; identifying nodes of the logical tree; mapping the identified nodes into a logical structure, the logical structure populated with data in each of the identified nodes; and generating an observer structure for observing the data, the observer structure comprising a grid of cells that has a one-to-one structural correspondence with the nodes of the logical structure, with data in each of the nodes of the logical structure mapped into corresponding cells in the grid of cells, the grid of cells accommodating a required attribute and an optional attribute of an element contained in the logical tree, the optional attribute indicated by a null value in the grid of cells when the optional attribute is not present, wherein the observer structure comprises a table, and mapping the data in each of the nodes of the logical structure into corresponding cells in the grid of cells comprises a building of: a data-bound list binding to a first control, the data-bound list comprising a collection of nodes and corresponding to the table of the observer structure, the table having a plurality of rows and a plurality of columns, each row and column intersecting at a cell; a data-bound node binding to a second control, the data-bound node corresponding to a row in the observer structure; and a data-bound node property binding to a third control, the data-bound node property corresponding to a column value in the row of the observer structure. 2. The method of claim 1 , wherein mapping the identified nodes into the logical structure comprises mapping the nodes into a representation of named lists of nodes and creating a structured document view using the logical structure. | 0.874461 |
8,719,260 | 1 | 3 | 1. A method of processing a set of documents for generating a facts database, comprising: at a system having one or more processors and memory storing one or more modules to be executed by the one or more processors: accessing a source document from a document host; extracting one or more facts from the source document; identifying a set of linking documents that have one or more links to the source document, wherein a respective link contains anchor text; generating a set of candidate labels from the anchor text of the linking documents, a respective candidate label of the set of candidate labels comprising text extracted from the anchor text in the one or more links to the source document in the set of linking documents; selecting a respective candidate label from the set of candidate labels as a unifying subject of the one or more facts extracted from the source document; and storing in the facts database an information set distinct from the source document, wherein the information set includes the unifying subject, one or more entries corresponding to the one or more facts extracted from the source document, and source document information for the one or more facts corresponding to the one or more entries. | 1. A method of processing a set of documents for generating a facts database, comprising: at a system having one or more processors and memory storing one or more modules to be executed by the one or more processors: accessing a source document from a document host; extracting one or more facts from the source document; identifying a set of linking documents that have one or more links to the source document, wherein a respective link contains anchor text; generating a set of candidate labels from the anchor text of the linking documents, a respective candidate label of the set of candidate labels comprising text extracted from the anchor text in the one or more links to the source document in the set of linking documents; selecting a respective candidate label from the set of candidate labels as a unifying subject of the one or more facts extracted from the source document; and storing in the facts database an information set distinct from the source document, wherein the information set includes the unifying subject, one or more entries corresponding to the one or more facts extracted from the source document, and source document information for the one or more facts corresponding to the one or more entries. 3. The method of claim 1 , wherein selecting the candidate label comprises: for each of the set of candidate labels: determining a set of frequencies of one or more substrings of the candidate label; and generating a frequency vector associated with the candidate label based on the set of frequencies; and determining a centroid vector based on the frequency vectors of the candidate labels, wherein the selected candidate label is associated with a respective frequency vector having a shortest distance to the centroid vector. | 0.63007 |
8,543,384 | 11 | 12 | 11. The method of claim 8 , further comprising generating an N-best list of candidate words from the core lexicon and the extended lexicon. | 11. The method of claim 8 , further comprising generating an N-best list of candidate words from the core lexicon and the extended lexicon. 12. The method of claim 11 , further comprising ranking the N-best list of candidate words according to at least one criterion. | 0.958224 |
9,323,987 | 1 | 3 | 1. An apparatus for detecting forgery/falsification of a homepage, comprising: one or more modules being configured and executed by a processor using algorithms associated with at least one non-transitory storage device, the one or more modules comprising, a homepage image shot generation module configured to generate homepage image shots of an entire screen of an accessed homepage; a character string extraction module configured to extract character strings from each homepage image shot using an Optical Character Recognition (OCR) technique; a character string comparison module configured to detect whether the extracted character string is a normal character string or a falsified character string for detecting homepage forgery/falsification by comparing each of the extracted character strings with character strings required for determination of homepage forgery/falsification; a homepage falsification determination module configured to determine whether the corresponding homepage has been forged/falsified according to the comparison; and a character string learning module configured to compare the character strings extracted using the homepage image shot, to determine whether newly detected character strings are normal character strings using normality determination reference character strings based on the comparison classify the character strings based on the normal character strings or the falsified character strings according to the determination, register the character strings extracted from the corresponding homepage image shot using the OCR technique upon detection of a normal character string, and assign a weight to a character string repeatedly appearing with respect to the character strings extracted from previous image shots. | 1. An apparatus for detecting forgery/falsification of a homepage, comprising: one or more modules being configured and executed by a processor using algorithms associated with at least one non-transitory storage device, the one or more modules comprising, a homepage image shot generation module configured to generate homepage image shots of an entire screen of an accessed homepage; a character string extraction module configured to extract character strings from each homepage image shot using an Optical Character Recognition (OCR) technique; a character string comparison module configured to detect whether the extracted character string is a normal character string or a falsified character string for detecting homepage forgery/falsification by comparing each of the extracted character strings with character strings required for determination of homepage forgery/falsification; a homepage falsification determination module configured to determine whether the corresponding homepage has been forged/falsified according to the comparison; and a character string learning module configured to compare the character strings extracted using the homepage image shot, to determine whether newly detected character strings are normal character strings using normality determination reference character strings based on the comparison classify the character strings based on the normal character strings or the falsified character strings according to the determination, register the character strings extracted from the corresponding homepage image shot using the OCR technique upon detection of a normal character string, and assign a weight to a character string repeatedly appearing with respect to the character strings extracted from previous image shots. 3. The apparatus of claim 1 , wherein the homepage falsification determination module is configured to: determine whether the corresponding homepage having been forged/falsified, in response to determination whether the character string extracted from the homepage image shot is identical to any of falsification determination reference character strings, and to determine whether the homepage is in as normal state in response to detection of a rate at which the character string extracted from the homepage image shot is identical to any of normality determination reference character strings is high. | 0.57234 |
9,720,893 | 12 | 15 | 12. An end-user system comprising: a plurality of user devices, wherein each of the plurality of user devices is configured to display a document to a user; a local data server comprising a plurality of databases, wherein the plurality of databases comprise: a post database, wherein the post database contains the content that is displayed to a user via at least one of the user devices; and a customization database, wherein the customization database comprises at least one customization including a customization file comprising at least one page fragment for insertion into the document and a metadata file; and an end-user server configured to: retrieve a document comprising digital content via a communication network; identify the presence of at least one insertion point within the document, wherein identifying the presence of the at least one insertion point within the document comprises: receiving data identifying one or several indicators of an insertion point; and searching the document via a search engine for indicators of an insertion point; identify a customization comprising a customization file comprising at least one page fragment for insertion into the document and a metadata file from the customization database, wherein the customization has a customization name; parse the customization name; determine a customization location, wherein determining the customization location comprises: identifying a designated insertion point for receiving the customization; and identifying a destination location in displayed digital content for the customization, wherein the destination location is the location at which the customization appears to a user accessing the document, and wherein the destination location is not at the insertion point; insert the customization into the document at the insertion point; and output the document including the inserted customization to at least one of the user devices. | 12. An end-user system comprising: a plurality of user devices, wherein each of the plurality of user devices is configured to display a document to a user; a local data server comprising a plurality of databases, wherein the plurality of databases comprise: a post database, wherein the post database contains the content that is displayed to a user via at least one of the user devices; and a customization database, wherein the customization database comprises at least one customization including a customization file comprising at least one page fragment for insertion into the document and a metadata file; and an end-user server configured to: retrieve a document comprising digital content via a communication network; identify the presence of at least one insertion point within the document, wherein identifying the presence of the at least one insertion point within the document comprises: receiving data identifying one or several indicators of an insertion point; and searching the document via a search engine for indicators of an insertion point; identify a customization comprising a customization file comprising at least one page fragment for insertion into the document and a metadata file from the customization database, wherein the customization has a customization name; parse the customization name; determine a customization location, wherein determining the customization location comprises: identifying a designated insertion point for receiving the customization; and identifying a destination location in displayed digital content for the customization, wherein the destination location is the location at which the customization appears to a user accessing the document, and wherein the destination location is not at the insertion point; insert the customization into the document at the insertion point; and output the document including the inserted customization to at least one of the user devices. 15. The system of claim 12 , wherein receiving data identifying one or several indicators of the insertion point comprises receiving an electrical signal containing information identifying coding creating an insertion point, wherein the electrical signal is received at an end-user server of an end-user network from a content network. | 0.501488 |
8,924,385 | 11 | 14 | 11. A computer-readable storage medium storing computer-executable instructions that when executed by at least one processor cause the at least one processor to perform a method for providing a query-based diagrammatic presentation of data, the method comprising: generating a filter element that defines a set of groups and includes a set of declarative queries that define information to be included in the set of groups; applying the filter element to a data source, including performing the set of declarative queries on the data source, thereby generating a set of query results for each of the groups; and generating a diagram including a set of shapes representing the set of groups, and a set of nodes nested within each of the shapes, wherein the nodes for each respective group are determined based on the query results for the groups, respectively. | 11. A computer-readable storage medium storing computer-executable instructions that when executed by at least one processor cause the at least one processor to perform a method for providing a query-based diagrammatic presentation of data, the method comprising: generating a filter element that defines a set of groups and includes a set of declarative queries that define information to be included in the set of groups; applying the filter element to a data source, including performing the set of declarative queries on the data source, thereby generating a set of query results for each of the groups; and generating a diagram including a set of shapes representing the set of groups, and a set of nodes nested within each of the shapes, wherein the nodes for each respective group are determined based on the query results for the groups, respectively. 14. The computer-readable storage medium of claim 11 , wherein the data source comprises a set of computer code. | 0.857143 |
9,405,736 | 14 | 15 | 14. A system for processing a markup language file having one or more portions, the system having a computer having at least a processor, a memory operably coupled to the memory, the memory being configured for storing a computer program executable by the processor, the computer program comprising: computer program code for automatically downloading by the processor a first markup language file using the hypertext transfer protocol and automatically referencing by the processor the first markup language file by its uniform resource location (URL) or by a name of a local file on a system on which a user is operating, the first markup language file including arbitrarily named tags; computer program code, responsive to an automatic determination that the steps of downloading and referencing are complete, for automatically parsing by the processor the first markup language file for one or more portions of the first markup language file; computer program code, responsive to an automatic determination that the step of parsing is complete, for automatically storing by the processor each portion of the first markup language file into a directory structure containing one or more folders, and one or more documents, complying with the structure of the first markup language file, wherein each of the one or more folders depends from the tag names in the markup language file; and computer program code, responsive to an automatic determination that the step of storing is complete, for automatically modifying the content of one or more markup language documents. | 14. A system for processing a markup language file having one or more portions, the system having a computer having at least a processor, a memory operably coupled to the memory, the memory being configured for storing a computer program executable by the processor, the computer program comprising: computer program code for automatically downloading by the processor a first markup language file using the hypertext transfer protocol and automatically referencing by the processor the first markup language file by its uniform resource location (URL) or by a name of a local file on a system on which a user is operating, the first markup language file including arbitrarily named tags; computer program code, responsive to an automatic determination that the steps of downloading and referencing are complete, for automatically parsing by the processor the first markup language file for one or more portions of the first markup language file; computer program code, responsive to an automatic determination that the step of parsing is complete, for automatically storing by the processor each portion of the first markup language file into a directory structure containing one or more folders, and one or more documents, complying with the structure of the first markup language file, wherein each of the one or more folders depends from the tag names in the markup language file; and computer program code, responsive to an automatic determination that the step of storing is complete, for automatically modifying the content of one or more markup language documents. 15. The system of claim 14 wherein the computer program further comprises computer program code for reading the URL from a browser via a CGI transaction. | 0.567797 |
7,533,014 | 19 | 20 | 19. An apparatus comprising: input devices to receive an input word through a plurality of input modalities; and a processor coupled to the input devices, the processor to: ascertain an input pool for each input modality, the input pool to contain possible words ordered based upon a probability of being the input word; identify a highest probability word from each input pool, the highest probability word being a word that has a highest probability among the possible words in the input pool; develop a first acoustic profile for the highest probability word of a first input pool; develop second acoustic profiles for the possible words of a second input pool, each of the second acoustic profiles to correspond to one of the possible words of the second input pool; compare the first acoustic profile of the first input pool with each of the second acoustic profiles of the second input pool; and select the highest probability word of the first input pool as a recognized word in response to a determination that the first acoustic profile matches one of the second acoustic profiles. | 19. An apparatus comprising: input devices to receive an input word through a plurality of input modalities; and a processor coupled to the input devices, the processor to: ascertain an input pool for each input modality, the input pool to contain possible words ordered based upon a probability of being the input word; identify a highest probability word from each input pool, the highest probability word being a word that has a highest probability among the possible words in the input pool; develop a first acoustic profile for the highest probability word of a first input pool; develop second acoustic profiles for the possible words of a second input pool, each of the second acoustic profiles to correspond to one of the possible words of the second input pool; compare the first acoustic profile of the first input pool with each of the second acoustic profiles of the second input pool; and select the highest probability word of the first input pool as a recognized word in response to a determination that the first acoustic profile matches one of the second acoustic profiles. 20. The apparatus of claim 19 , wherein the first input pool corresponds to an input modality of speech, and the second input pool corresponds to an input modality of handwriting in Chinese ideograms or pinyin. | 0.66129 |
8,086,668 | 32 | 33 | 32. The computationally-implemented method of claim 1 , wherein said soliciting, based at least in part on a hypothesis that links one or more objective occurrences with one or more subjective user states and in response at least in part to an incidence of at least one subjective user state associated with a user, at least a portion of objective occurrence data including data indicating incidence of at least one objective occurrence comprises: soliciting the data indicating incidence of at least one objective occurrence in response, at least in part, to receiving data indicating incidence of the at least one subjective user state associated with the user. | 32. The computationally-implemented method of claim 1 , wherein said soliciting, based at least in part on a hypothesis that links one or more objective occurrences with one or more subjective user states and in response at least in part to an incidence of at least one subjective user state associated with a user, at least a portion of objective occurrence data including data indicating incidence of at least one objective occurrence comprises: soliciting the data indicating incidence of at least one objective occurrence in response, at least in part, to receiving data indicating incidence of the at least one subjective user state associated with the user. 33. The computationally-implemented method of claim 32 , wherein said soliciting the data indicating incidence of at least one objective occurrence in response, at least in part, to receiving data indicating incidence of the at least one subjective user state associated with the user comprises: soliciting the data indicating incidence of at least one objective occurrence in response, at least in part, to receiving data indicating incidence of the at least one subjective user state associated with the user via one or more blog entries. | 0.752747 |
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