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10. The method of claim 9 further comprising the steps of receiving at the switching system, from a user directly served by the switching system, a second symbol sequence included in the internal numbering plan, and in response to the receipt of the second symbol sequence, parsing the received second symbol sequence by using stored second information defining a syntax and a grammar of the internal numbering plan and defining the second symbol sequence as a feature access code for a corresponding feature, to determine a meaning of the second symbol sequence within the internal numbering plan; wherein the stored first information defines the first symbol sequence as an equivalent of the second symbol sequence, and the step of invoking comprises the step of in response to the determined meaning of either one of the received first symbol sequence and the received second symbol sequence, invoking the feature that corresponds to the second symbol sequence. | 10. The method of claim 9 further comprising the steps of receiving at the switching system, from a user directly served by the switching system, a second symbol sequence included in the internal numbering plan, and in response to the receipt of the second symbol sequence, parsing the received second symbol sequence by using stored second information defining a syntax and a grammar of the internal numbering plan and defining the second symbol sequence as a feature access code for a corresponding feature, to determine a meaning of the second symbol sequence within the internal numbering plan; wherein the stored first information defines the first symbol sequence as an equivalent of the second symbol sequence, and the step of invoking comprises the step of in response to the determined meaning of either one of the received first symbol sequence and the received second symbol sequence, invoking the feature that corresponds to the second symbol sequence. 11. The method of claim 10 wherein: the stored first information defines the first symbol sequence same as the stored second information defines the second symbol sequence; and the step of invoking comprises the steps of in response to the determined meaning of the received second symbol sequence, invoking the feature that corresponds to the second symbol sequence by using the determined meaning and the stored second information, and in response to the determined meaning of the received first symbol sequence, invoking same said feature by using the determined meaning and the stored first information. | 0.678044 |
3. The method according to claim 2 , further comprising: defining a plurality of different scripting commands, each of said commands associated with at least one of said plurality of different scripting languages; constructing at least one scripting object to associate with each of said different scripting commands; binding said scripting object for each of said scripting commands to computer memory dynamically, at runtime, wherein said dynamic binding is done by a CFParser in Java. | 3. The method according to claim 2 , further comprising: defining a plurality of different scripting commands, each of said commands associated with at least one of said plurality of different scripting languages; constructing at least one scripting object to associate with each of said different scripting commands; binding said scripting object for each of said scripting commands to computer memory dynamically, at runtime, wherein said dynamic binding is done by a CFParser in Java. 4. The method according to claim 3 , wherein: said different scripting command is translated for each associated scripting language according to the Bean Scripting Framework. | 0.834081 |
6. A computer-implemented method of preventing alterations of physical entities of data in a database when a query is executed against the database, comprising: providing a logical representation of the data defining a multiplicity of logical fields, each logical field abstractly describing a manner of accessing and exposing, via a user interface, an associated physical entity of the data; wherein each of the multiplicity of logical fields include a reference to an access method selected from at least two different access method types; wherein the at least two different access method types are selected from the group comprising: (i) a simple access method which maps a respective one of the plurality of logical fields directly to a physical entity, (ii) a filtered access method which identifies a physical entity and provides rules used to define a subset of items within the physical entities, and (iii) a composed access method which computes a value for a respective one of the plurality of logical fields from one or more physical entities using an expression supplied as part of a composed access method definition; wherein each of the different access methods types defines a different manner of exposing the respective physical entity of the data; and wherein at least a portion of the multiplicity of logical fields include lock attributes referenced in order to lock the respective logical field; providing a lock object for each logical field of a plurality of logical fields forming a subset of the multiplicity of logical fields, the respective lock object being identified by the respective lock attributes of the respective logical field; receiving an abstract query from a requesting entity comprising at least one logical field of the multiplicity of logical fields; and upon determining that executing the abstract query against the database requires the lock on the at least one logical field; determining the lock object of the at least one logical field; locking the lock object for the requesting entity for locking the at least one logical field before executing the abstract query; and unlocking the lock object for the requesting entity after executing the abstract query. | 6. A computer-implemented method of preventing alterations of physical entities of data in a database when a query is executed against the database, comprising: providing a logical representation of the data defining a multiplicity of logical fields, each logical field abstractly describing a manner of accessing and exposing, via a user interface, an associated physical entity of the data; wherein each of the multiplicity of logical fields include a reference to an access method selected from at least two different access method types; wherein the at least two different access method types are selected from the group comprising: (i) a simple access method which maps a respective one of the plurality of logical fields directly to a physical entity, (ii) a filtered access method which identifies a physical entity and provides rules used to define a subset of items within the physical entities, and (iii) a composed access method which computes a value for a respective one of the plurality of logical fields from one or more physical entities using an expression supplied as part of a composed access method definition; wherein each of the different access methods types defines a different manner of exposing the respective physical entity of the data; and wherein at least a portion of the multiplicity of logical fields include lock attributes referenced in order to lock the respective logical field; providing a lock object for each logical field of a plurality of logical fields forming a subset of the multiplicity of logical fields, the respective lock object being identified by the respective lock attributes of the respective logical field; receiving an abstract query from a requesting entity comprising at least one logical field of the multiplicity of logical fields; and upon determining that executing the abstract query against the database requires the lock on the at least one logical field; determining the lock object of the at least one logical field; locking the lock object for the requesting entity for locking the at least one logical field before executing the abstract query; and unlocking the lock object for the requesting entity after executing the abstract query. 10. The method of claim 6 , wherein receiving an abstract query comprises receiving a plurality of abstract queries associated with a plurality of requesting entities, and wherein locking the at least one logical field comprises locking a corresponding lock object for each requesting entity of the plurality of requesting entities. | 0.600971 |
12. A computer system, comprising at least one processor, wherein the at least one processor is configured to perform the operations of: receiving, on a computer host, an electronic document representing a pharmaceutical prescription; identifying constituent regions that include at least a first portion and a second portion within the electronic document; identifying first spatial frequencies for the first portion within the electronic document; identifying second spatial frequencies for the second portion within the electronic document; identifying a header based upon the first spatial frequencies, wherein identifying the first and second spatial frequencies includes performing a fast Fourier Transform on a portion of a document and translating spatial information into frequency information such that (i) the header identifying the prescriber is identified from the first spatial frequencies; and (ii) the second spatial frequencies are analyzed using the profile of the identified prescriber; using the header to identify a prescriber; retrieving a profile specific for the prescriber; analyzing the second spatial frequencies using the profile specific for the prescriber such that the second spatial frequencies are compared to spatial frequency domain information from the profile specific for the prescriber, the prescriber-specific profile constructed from the prescriber's past records and including isolated handwriting of the prescriber in a spatial frequency domain; and creating, based upon results from analyzing the second spatial frequencies using the profile for the prescriber, a transaction record on the computer host for a medical transaction associated with the pharmaceutical prescription. | 12. A computer system, comprising at least one processor, wherein the at least one processor is configured to perform the operations of: receiving, on a computer host, an electronic document representing a pharmaceutical prescription; identifying constituent regions that include at least a first portion and a second portion within the electronic document; identifying first spatial frequencies for the first portion within the electronic document; identifying second spatial frequencies for the second portion within the electronic document; identifying a header based upon the first spatial frequencies, wherein identifying the first and second spatial frequencies includes performing a fast Fourier Transform on a portion of a document and translating spatial information into frequency information such that (i) the header identifying the prescriber is identified from the first spatial frequencies; and (ii) the second spatial frequencies are analyzed using the profile of the identified prescriber; using the header to identify a prescriber; retrieving a profile specific for the prescriber; analyzing the second spatial frequencies using the profile specific for the prescriber such that the second spatial frequencies are compared to spatial frequency domain information from the profile specific for the prescriber, the prescriber-specific profile constructed from the prescriber's past records and including isolated handwriting of the prescriber in a spatial frequency domain; and creating, based upon results from analyzing the second spatial frequencies using the profile for the prescriber, a transaction record on the computer host for a medical transaction associated with the pharmaceutical prescription. 15. The computer system of claim 12 , wherein the operation of identifying the constituent regions includes performing a preliminary degree of processing to identify a document format and using the document format to specify the first and second regions. | 0.670341 |
1. A computerized method of determining relevancies of multiple objects to a search query, comprising: associating one or more of the multiple objects with user-entered tags as a result of user input, thereby defining one or more corresponding tag-object pairs, wherein each tag comprises one or more tag terms, each tag term comprising text, and wherein each association of an object with a tag comprises a tag object pair; associating an object with each tag term from the one or more tag terms, thereby defining one or more corresponding tag term object pairs, wherein at least one of the one or more tags comprises a string of multiple terms entered by a user; determining for each tag term object pair a tag term score indicating a degree of relevance between the tag term and the object, wherein a tag term score for an object X and a term A is a function of a combination comprising a total number of different terms in a tag database storing the tags, a total number of tags present in the tag database, a frequency with which the term A is present in the tag database, a number of different terms with which the object X has been tagged, a total number of tags associated with the object X, and a number of different objects that have been tagged with the term A; determining for one or more objects a term relevance score comprising combining the tag term scores from the tag term object pairs for each tag associated with each object; and determining a relevance score for each of the multiple objects for the search query, wherein the relevance score is influenced by tags associated with objects as a result of user input. | 1. A computerized method of determining relevancies of multiple objects to a search query, comprising: associating one or more of the multiple objects with user-entered tags as a result of user input, thereby defining one or more corresponding tag-object pairs, wherein each tag comprises one or more tag terms, each tag term comprising text, and wherein each association of an object with a tag comprises a tag object pair; associating an object with each tag term from the one or more tag terms, thereby defining one or more corresponding tag term object pairs, wherein at least one of the one or more tags comprises a string of multiple terms entered by a user; determining for each tag term object pair a tag term score indicating a degree of relevance between the tag term and the object, wherein a tag term score for an object X and a term A is a function of a combination comprising a total number of different terms in a tag database storing the tags, a total number of tags present in the tag database, a frequency with which the term A is present in the tag database, a number of different terms with which the object X has been tagged, a total number of tags associated with the object X, and a number of different objects that have been tagged with the term A; determining for one or more objects a term relevance score comprising combining the tag term scores from the tag term object pairs for each tag associated with each object; and determining a relevance score for each of the multiple objects for the search query, wherein the relevance score is influenced by tags associated with objects as a result of user input. 3. The method of claim 1 , wherein combining the tag term scores comprises weighing each tag term score with a weight and summing the weighted tag term scores. | 0.629103 |
47. A method for processing voice commands, the method comprising: at a electronic device: receiving user input; in response to receiving user input, recording at least a portion of a voice command; storing contextual information of the electronic device, the contextual information related to a state of the electronic device at a time the at least a portion of the voice command is recorded; after recording the at least a portion of the voice command and storing the contextual information, transmitting the at least a portion of the recorded voice command and the stored contextual information from the electronic device to remote computing equipment; and receiving, from the remote computing equipment, data related to processing the voice command. | 47. A method for processing voice commands, the method comprising: at a electronic device: receiving user input; in response to receiving user input, recording at least a portion of a voice command; storing contextual information of the electronic device, the contextual information related to a state of the electronic device at a time the at least a portion of the voice command is recorded; after recording the at least a portion of the voice command and storing the contextual information, transmitting the at least a portion of the recorded voice command and the stored contextual information from the electronic device to remote computing equipment; and receiving, from the remote computing equipment, data related to processing the voice command. 73. The method of claim 47 , wherein the contextual information comprises information from a business productivity application of the electronic device. | 0.652655 |
1. A speech recognition method based on recognizing words, comprising the steps of: defining, for each word, a probabilistic model including (i) a plurality of states, (ii) at least one transition, each transition extending from a state to a state, (iii) a plurality of generated labels indicative of time between states, and (iv) probabilities of outputting each label in each of said transitions; generating a first label string of said labels for each of said words from initial data thereof; for each of said words, iteratively updating the probabilities of the corresponding probabilistic model, comprising the steps of: (a) inputting a first label string into a corresponding probabilistic model; (b) obtaining a first frequency of each of said labels being output at each of said transitions over the time in which the corresponding first label string is input into the corresponding probabilistic model; (c) obtaining a second frequency of each of said states occurring over the time in which the corresponding first label string is inputted into the corresponding probabilistic model; and (d) obtaining each of a plurality of new probabilities of said corresponding probabilistic model by dividing the corresponding first frequency by the corresponding second frequency; storing the first and second frequencies obtained in the last step of said iterative updating; determining which of said words require adaptation to recognize different speakers or the same speaker at different times; generating, for each of said words requiring adaptation, a second label string from adaptation data comprising the probabilistic model of the word to be adapted; obtaining, for each of said words requiring adaptation, a third frequency of each of said labels being outputted at each of said transitions over the time in which the corresponding second label string is inputted into the corresponding probabilistic model; obtaining, for each of said words requiring adaptation, a fourth frequency of each of said states occurring over the time in which the corresponding second label string is outputted into the corresponding probabilistic model; obtaining fifth frequencies by interpolation of the corresponding first and third frequencies; obtaining sixth frequencies by interpolation of the corresponding second and third frequencies; and obtaining adapted probabilities for said adaptation data by dividing the corresponding fifth frequency by the corresponding sixth frequency. | 1. A speech recognition method based on recognizing words, comprising the steps of: defining, for each word, a probabilistic model including (i) a plurality of states, (ii) at least one transition, each transition extending from a state to a state, (iii) a plurality of generated labels indicative of time between states, and (iv) probabilities of outputting each label in each of said transitions; generating a first label string of said labels for each of said words from initial data thereof; for each of said words, iteratively updating the probabilities of the corresponding probabilistic model, comprising the steps of: (a) inputting a first label string into a corresponding probabilistic model; (b) obtaining a first frequency of each of said labels being output at each of said transitions over the time in which the corresponding first label string is input into the corresponding probabilistic model; (c) obtaining a second frequency of each of said states occurring over the time in which the corresponding first label string is inputted into the corresponding probabilistic model; and (d) obtaining each of a plurality of new probabilities of said corresponding probabilistic model by dividing the corresponding first frequency by the corresponding second frequency; storing the first and second frequencies obtained in the last step of said iterative updating; determining which of said words require adaptation to recognize different speakers or the same speaker at different times; generating, for each of said words requiring adaptation, a second label string from adaptation data comprising the probabilistic model of the word to be adapted; obtaining, for each of said words requiring adaptation, a third frequency of each of said labels being outputted at each of said transitions over the time in which the corresponding second label string is inputted into the corresponding probabilistic model; obtaining, for each of said words requiring adaptation, a fourth frequency of each of said states occurring over the time in which the corresponding second label string is outputted into the corresponding probabilistic model; obtaining fifth frequencies by interpolation of the corresponding first and third frequencies; obtaining sixth frequencies by interpolation of the corresponding second and third frequencies; and obtaining adapted probabilities for said adaptation data by dividing the corresponding fifth frequency by the corresponding sixth frequency. 4. The method in accordance with claim 1 wherein each of probabilities of the said probabilistic model into which adaptation data is to be inputted have been subjected to a smoothing operation. | 0.502016 |
1. A method of identifying web pages of a world wide web having relevance to a first file, comprising: identifying a plurality of web pages within the world wide web, wherein the plurality of web pages each have a relationship with the first file, wherein the world wide web provides a platform for sharing web pages, and wherein each web page includes a document or information resource that is suitable for the world wide web and is accessible through a web browser; generating, by a system server, a list of inquiries based on the plurality of web pages; providing, by the system server, the list of inquiries to at least one first author of the first file; receiving from the at least one first author at least one response to the list of inquiries; selecting a subset of the plurality of web pages based on the at least one response; storing information related to the selected subset of the plurality of web pages for access if the first file is selected; generating, by the system server, a second list of inquiries based on the plurality of web pages; providing, by the system server, the second list of inquiries to at least one second author of the plurality of web pages; receiving from the at least one second author of the plurality of web pages at least one second response to the second list of inquiries; re-selecting the subset of the plurality of web pages based on the at least one response and the at least one second response; and storing information related to the re-selected subset of the plurality of web pages for access if the first file is selected; providing, by the system server, the re-selected subset of the plurality of web pages or the selected subset of the plurality of web pages to a user that selects the first file; and identifying the at least one second author or the at least one first author to the user. | 1. A method of identifying web pages of a world wide web having relevance to a first file, comprising: identifying a plurality of web pages within the world wide web, wherein the plurality of web pages each have a relationship with the first file, wherein the world wide web provides a platform for sharing web pages, and wherein each web page includes a document or information resource that is suitable for the world wide web and is accessible through a web browser; generating, by a system server, a list of inquiries based on the plurality of web pages; providing, by the system server, the list of inquiries to at least one first author of the first file; receiving from the at least one first author at least one response to the list of inquiries; selecting a subset of the plurality of web pages based on the at least one response; storing information related to the selected subset of the plurality of web pages for access if the first file is selected; generating, by the system server, a second list of inquiries based on the plurality of web pages; providing, by the system server, the second list of inquiries to at least one second author of the plurality of web pages; receiving from the at least one second author of the plurality of web pages at least one second response to the second list of inquiries; re-selecting the subset of the plurality of web pages based on the at least one response and the at least one second response; and storing information related to the re-selected subset of the plurality of web pages for access if the first file is selected; providing, by the system server, the re-selected subset of the plurality of web pages or the selected subset of the plurality of web pages to a user that selects the first file; and identifying the at least one second author or the at least one first author to the user. 16. The method of claim 1 , wherein a plurality of lists of inquiries are provided to a plurality of authors, and responses received from each of the plurality of authors are compiled for selecting the subset of the plurality of web pages. | 0.55117 |
12. The method of claim 8 , further comprising: categorizing the unstructured data into category topics. | 12. The method of claim 8 , further comprising: categorizing the unstructured data into category topics. 19. The method of claim 12 , further comprising: computing a sentiment on the unstructured text data; and analyzing an aggregation of category topics to provide a measure of sentiment. | 0.964177 |
9. A computer readable medium including program instructions implemented by a computer, the program instructions for searching for data in a database, the program instructions implementing steps comprising: receiving a query that is a request for data in the database, wherein the query includes at least one uneven non-Boolean term condition including an OR condition that spans at least two tables of the database, wherein the OR condition includes two predicates; splitting the at least one uneven non-Boolean term condition into a plurality of separate query portions that each provide a Boolean term satisfied by accessing a different particular one of the at least two tables, wherein each predicate is provided to a different one of the separate query portions; executing the separate query portions independently of each other to find at least one data result in each of the at least two tables that satisfies the Boolean term of each separate query portion; identifying at least one bridge table, wherein the at least one bridge table does not satisfy the at least one uneven non-Boolean term condition and has at least one column from each of the at least two tables; and combining the data results from each separate query portion into a final result that satisfies the query, wherein the at least one bridge table is used to join each of the at least two tables to combine the data results. | 9. A computer readable medium including program instructions implemented by a computer, the program instructions for searching for data in a database, the program instructions implementing steps comprising: receiving a query that is a request for data in the database, wherein the query includes at least one uneven non-Boolean term condition including an OR condition that spans at least two tables of the database, wherein the OR condition includes two predicates; splitting the at least one uneven non-Boolean term condition into a plurality of separate query portions that each provide a Boolean term satisfied by accessing a different particular one of the at least two tables, wherein each predicate is provided to a different one of the separate query portions; executing the separate query portions independently of each other to find at least one data result in each of the at least two tables that satisfies the Boolean term of each separate query portion; identifying at least one bridge table, wherein the at least one bridge table does not satisfy the at least one uneven non-Boolean term condition and has at least one column from each of the at least two tables; and combining the data results from each separate query portion into a final result that satisfies the query, wherein the at least one bridge table is used to join each of the at least two tables to combine the data results. 12. The computer readable medium of claim 9 wherein the separate query portions are separate tasks, each task being executed independently at runtime to find the data results for the Boolean term associated with that task, and wherein a duplication of table accesses is minimized. | 0.543938 |
12. The system according to claim 10 , wherein the decision mechanism comprises: a random determiner that decides whether a confirmation is to be performed randomly; and a deterministic determiner that decides that a confirmation decision is to be performed deterministically. | 12. The system according to claim 10 , wherein the decision mechanism comprises: a random determiner that decides whether a confirmation is to be performed randomly; and a deterministic determiner that decides that a confirmation decision is to be performed deterministically. 13. The system according to claim 12 , wherein the random determiner comprises: a random number generator capable of generating a random number; a random decision mechanism in communication with the random number generator, that determines whether a confirmation is to be performed based on the random number generated. | 0.83663 |
1. A method of operating on database queries, comprising: identifying a parameterized input query in a first database query language, wherein the parameterized input query includes one or more parameter placeholders, each parameter placeholder defining a parameter name and a declared parameter type; generating, for each parameter placeholder in the parameterized input query in the first database query language, a random value of the declared parameter type; constructing a concrete instance of the parameterized input query in the first database query language, where the concrete instance of the parameterized input query replaces each parameter placeholder with the corresponding generated random value of the declared parameter type; generating, from the concrete instance of the parameterized input query in the first database query language, a translated output query in a second database query language different from the first query language, the translated output query including the generated random value of the declared parameter type; and replacing the generated random values within the translated output query in the second database query language with a placeholder value associated with the second database query language. | 1. A method of operating on database queries, comprising: identifying a parameterized input query in a first database query language, wherein the parameterized input query includes one or more parameter placeholders, each parameter placeholder defining a parameter name and a declared parameter type; generating, for each parameter placeholder in the parameterized input query in the first database query language, a random value of the declared parameter type; constructing a concrete instance of the parameterized input query in the first database query language, where the concrete instance of the parameterized input query replaces each parameter placeholder with the corresponding generated random value of the declared parameter type; generating, from the concrete instance of the parameterized input query in the first database query language, a translated output query in a second database query language different from the first query language, the translated output query including the generated random value of the declared parameter type; and replacing the generated random values within the translated output query in the second database query language with a placeholder value associated with the second database query language. 2. The method of claim 1 , wherein the first database query language is a Domain Specific Language (DSL) and the second database query language is a Structured Query Language (SQL). | 0.730017 |
1. A process for performing computerized employment authorization queries with a federal governmental entity, the process comprising: providing a first database for storing a record for the person; providing an electronic form having at least one variable to be entered; storing the at least one variable in the record in the first database; transmitting the at least one variable to a remote federal government system having a federal government database and employment eligibility information; receiving an indication, from the remote federal government system, that the person corresponding to the at least one variable is legally eligible for employment, the indication based on: the at least one variable sent to the remote federal government system determined to be valid by the remote federal government system; and the at least one variable sent to the remote federal government system subsequently determined to indicate the person is authorized by the remote federal government for employment; providing a first authorization interface for receiving the person's electronic signature, the first authorization interface comprising: a first user interface element for obtaining the person's electronic signature; and a second user interface element for enabling the person to withdraw a certified electronic signature previously entered by the person; receiving data transmitted by a signature server, said data confirming verification by the signature server of the person's electronic signature; displaying an electronic signature authentication receipt of said verification; providing a second authorization interface for receiving a preparer's electronic signature, the second authorization interface comprising: a first preparer interface element for obtaining the preparer's electronic signature via username and password; a second preparer interface element for obtaining an electronic instant signature from the preparer; and a third preparer interface element for calling an account management interface having a first account management interface element for creating an electronic signature account, and a second account management interface element for managing the electronic signature account; providing a third authorization interface for receiving an employer's electronic signature, the third authorization interface comprising: a first employer interface element for obtaining the employer's electronic signature via username and password; a second employer interface element for obtaining an instant signature from the employer; and a third employer interface element for calling the account management interface; and determining an expiration date for legal eligibility for employment of the person based on at least some information stored in the record in the first database. | 1. A process for performing computerized employment authorization queries with a federal governmental entity, the process comprising: providing a first database for storing a record for the person; providing an electronic form having at least one variable to be entered; storing the at least one variable in the record in the first database; transmitting the at least one variable to a remote federal government system having a federal government database and employment eligibility information; receiving an indication, from the remote federal government system, that the person corresponding to the at least one variable is legally eligible for employment, the indication based on: the at least one variable sent to the remote federal government system determined to be valid by the remote federal government system; and the at least one variable sent to the remote federal government system subsequently determined to indicate the person is authorized by the remote federal government for employment; providing a first authorization interface for receiving the person's electronic signature, the first authorization interface comprising: a first user interface element for obtaining the person's electronic signature; and a second user interface element for enabling the person to withdraw a certified electronic signature previously entered by the person; receiving data transmitted by a signature server, said data confirming verification by the signature server of the person's electronic signature; displaying an electronic signature authentication receipt of said verification; providing a second authorization interface for receiving a preparer's electronic signature, the second authorization interface comprising: a first preparer interface element for obtaining the preparer's electronic signature via username and password; a second preparer interface element for obtaining an electronic instant signature from the preparer; and a third preparer interface element for calling an account management interface having a first account management interface element for creating an electronic signature account, and a second account management interface element for managing the electronic signature account; providing a third authorization interface for receiving an employer's electronic signature, the third authorization interface comprising: a first employer interface element for obtaining the employer's electronic signature via username and password; a second employer interface element for obtaining an instant signature from the employer; and a third employer interface element for calling the account management interface; and determining an expiration date for legal eligibility for employment of the person based on at least some information stored in the record in the first database. 14. The process of claim 1 further comprising: receiving an image file of a document; and associating the image file of the document with a record for a person stored in the first database. | 0.531179 |
1. A method for representing call content of a call in a searchable database, comprising the steps of: transcribing call content to text; projecting the call content to vector space, by creating a vector by: indexing the call based on the call content; and determining a similarity of the call content to an atomic-class dictionary to provide a similarity measure; and classifying the call content in a content knowledge based relational database in accordance with the similarity measure. | 1. A method for representing call content of a call in a searchable database, comprising the steps of: transcribing call content to text; projecting the call content to vector space, by creating a vector by: indexing the call based on the call content; and determining a similarity of the call content to an atomic-class dictionary to provide a similarity measure; and classifying the call content in a content knowledge based relational database in accordance with the similarity measure. 10. A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform method steps for representing call content in a searchable database as recited in claim 1 . | 0.575083 |
1. A method of generating a response to a text-based natural language message, comprising: identifying a sentence in the text-based natural language message; identifying an input clause in the sentence; comparing the input clause to a previously received clause, the previously received clause being correlated with a previously generated response message; and generating an output response message based on the previously generated response message, the output response message being derived from a plurality of previously generated response clauses. | 1. A method of generating a response to a text-based natural language message, comprising: identifying a sentence in the text-based natural language message; identifying an input clause in the sentence; comparing the input clause to a previously received clause, the previously received clause being correlated with a previously generated response message; and generating an output response message based on the previously generated response message, the output response message being derived from a plurality of previously generated response clauses. 6. A method according to claim 1 , further comprises correlating the previously received clause with a one of the plurality of previously generated response clauses. | 0.738912 |
4. The apparatus according to claim 3 , further comprising: a search result displaying unit that displays search results obtained by the searching unit in proximity to the selected desired word. | 4. The apparatus according to claim 3 , further comprising: a search result displaying unit that displays search results obtained by the searching unit in proximity to the selected desired word. 5. The apparatus according to claim 4 , wherein the search result displaying unit displays the search results as a pop-up screen. | 0.954986 |
1. A method implemented by a computerized machine learning system, said method comprising: receiving, at the computerized machine learning system, a plurality of examples, separable by feature into at least two classes, for distribution to a plurality of workers in a mapreduce process, each worker only receiving examples associated with a first class or a second class, wherein the first class is a positive class and the second class is a negative class, and wherein a worker is selected from the group consisting of a mapper and a reducer; determining whether each example is either associated with the first class or associated with the second class; distributing an example associated with the first class to a first worker of the plurality of workers in the machine learning system, the first worker receiving only examples associated with the first class; and distributing an example associated with the second class to a second worker of the plurality of workers in the machine learning system, the second worker receiving only examples associated with the second class. | 1. A method implemented by a computerized machine learning system, said method comprising: receiving, at the computerized machine learning system, a plurality of examples, separable by feature into at least two classes, for distribution to a plurality of workers in a mapreduce process, each worker only receiving examples associated with a first class or a second class, wherein the first class is a positive class and the second class is a negative class, and wherein a worker is selected from the group consisting of a mapper and a reducer; determining whether each example is either associated with the first class or associated with the second class; distributing an example associated with the first class to a first worker of the plurality of workers in the machine learning system, the first worker receiving only examples associated with the first class; and distributing an example associated with the second class to a second worker of the plurality of workers in the machine learning system, the second worker receiving only examples associated with the second class. 8. The method of claim 1 , further comprising: determining that a threshold number of examples from the plurality of examples has been distributed; and removing one or more workers from the plurality of workers, based on the determination. | 0.590288 |
1. A computer-implemented system for identifying relevant documents for display, comprising: themes for a set of documents; an extraction module to extract noun phrases from the documents as concepts; a theme generator to group two or more of the concepts as one such theme; a frequency table that identifies each of the concepts and a frequency of occurrence of each concept within each of the documents in the set; a graph generator to generate a graph of the concepts, comprising: an x-axis of the graph defining the concepts; a y-axis of the graph defining a number of the documents that reference each concept; and a mapping module to map the concepts on the graph in order of descending number of referring documents; a cluster module to cluster the documents based on the themes; a matrix for the documents comprising an inner product of document frequency occurrences and cluster concept weightings for each theme; an identification module to identify from the matrix, documents most relevant to a particular theme; and a display to present the relevant documents. | 1. A computer-implemented system for identifying relevant documents for display, comprising: themes for a set of documents; an extraction module to extract noun phrases from the documents as concepts; a theme generator to group two or more of the concepts as one such theme; a frequency table that identifies each of the concepts and a frequency of occurrence of each concept within each of the documents in the set; a graph generator to generate a graph of the concepts, comprising: an x-axis of the graph defining the concepts; a y-axis of the graph defining a number of the documents that reference each concept; and a mapping module to map the concepts on the graph in order of descending number of referring documents; a cluster module to cluster the documents based on the themes; a matrix for the documents comprising an inner product of document frequency occurrences and cluster concept weightings for each theme; an identification module to identify from the matrix, documents most relevant to a particular theme; and a display to present the relevant documents. 7. A system according to claim 1 , further comprising: a removal module to remove duplicates of the relevant documents prior to display. | 0.607656 |
12. A method for assisting an author, comprising: receiving an author's review of an item which includes text and an associated author's rating of the item on a predefined scale; parsing the text of the author's review of the item to identify opinion expressions in the input text; with a processor, generating an analysis of the text, based on the identified opinion expressions including computing an effective opinion of the text as a function of a measure of polarity associated with each of the identified opinion expressions, the measure of polarity being is based on the polarity measure associated with respective adjectival terms from a polar vocabulary that are in the opinion expressions, the polar vocabulary associating a polarity measure with each of a set of adjectival terms, the polarity measure being based on ratings of reviews in a corpus of reviews from which the respective adjectival term was extracted; comparing the effective opinion with the author's rating to determine whether the text and the author's rating are coherent; and generating a representation of the analysis for display on a user interface, the representation of the analysis including a representation of the effective opinion. | 12. A method for assisting an author, comprising: receiving an author's review of an item which includes text and an associated author's rating of the item on a predefined scale; parsing the text of the author's review of the item to identify opinion expressions in the input text; with a processor, generating an analysis of the text, based on the identified opinion expressions including computing an effective opinion of the text as a function of a measure of polarity associated with each of the identified opinion expressions, the measure of polarity being is based on the polarity measure associated with respective adjectival terms from a polar vocabulary that are in the opinion expressions, the polar vocabulary associating a polarity measure with each of a set of adjectival terms, the polarity measure being based on ratings of reviews in a corpus of reviews from which the respective adjectival term was extracted; comparing the effective opinion with the author's rating to determine whether the text and the author's rating are coherent; and generating a representation of the analysis for display on a user interface, the representation of the analysis including a representation of the effective opinion. 26. A computer program product comprising a non-transitory recording medium encoding instructions, which when executed on a computer causes the computer to perform the method of claim 12 . | 0.645672 |
4. The method of claim 1 wherein transparently monitoring user interactions with data comprises monitoring multiple distinct modes of user interaction with network data. | 4. The method of claim 1 wherein transparently monitoring user interactions with data comprises monitoring multiple distinct modes of user interaction with network data. 5. The method of claim 4 wherein the multiple distinct modes of user interaction comprise a mode selected from the group consisting of a network searching mode, a network navigation mode, a network browsing mode, an email reading mode, an email writing mode, a document writing mode, a viewing “pushed” information mode, a finding expert advice mode, and a product purchasing mode. | 0.927624 |
26. A computing system in a network, the system comprising a knowledge repository comprising first knowledge represented in a structured, machine-readable format that is distinct from natural language and is operable to store information about any entity that can be denoted in natural language, the structured, machine-readable format primarily comprising assertions of named relationships between pairs of named entities, the system further comprising at least one computing device operable to facilitate addition of second knowledge to the knowledge repository by collecting input from a plurality of untrained, general internet users via the network using natural language requests, and translating the input to the machine-readable format using a plurality of translation templates, each of the translation templates including a respective predetermined pattern for matching against one or more natural language strings included in the input, wherein addition of the second knowledge to the knowledge base includes determining whether the second knowledge is semantically contradicted by the first knowledge to promote consistency of the first and second knowledge across the knowledge base. | 26. A computing system in a network, the system comprising a knowledge repository comprising first knowledge represented in a structured, machine-readable format that is distinct from natural language and is operable to store information about any entity that can be denoted in natural language, the structured, machine-readable format primarily comprising assertions of named relationships between pairs of named entities, the system further comprising at least one computing device operable to facilitate addition of second knowledge to the knowledge repository by collecting input from a plurality of untrained, general internet users via the network using natural language requests, and translating the input to the machine-readable format using a plurality of translation templates, each of the translation templates including a respective predetermined pattern for matching against one or more natural language strings included in the input, wherein addition of the second knowledge to the knowledge base includes determining whether the second knowledge is semantically contradicted by the first knowledge to promote consistency of the first and second knowledge across the knowledge base. 27. The system of claim 26 wherein the second knowledge comprises a plurality of assertions, and wherein the at least one computing device is further operable to inhibit use of selected ones of the assertions in the knowledge repository. | 0.666832 |
1. A method comprising: at one or more processors: receiving a name; mapping the name to one or more sets of monosyllabic components that represent alternative phonetic pronunciations for at least a portion of the name, wherein monosyllabic components from the one or more sets of monosyllabic components are combinable to construct a phonetic pronunciation of the name; displaying the one or more sets of monosyllabic components; receiving a user selection of a monosyllabic component from each of the one or more sets of monosyllabic components; and combining the selected monosyllabic component from each of the one or more sets of monosyllabic components to construct the phonetic pronunciation of the name; wherein displaying the one or more sets of monosyllabic components comprises displaying a first portion of the one or more sets of monosyllabic components via a user interface, and further displaying a second portion of the one or more sets of monosyllabic components in response to a user selection of one of the first portion of the one or more sets of monosyllabic components. | 1. A method comprising: at one or more processors: receiving a name; mapping the name to one or more sets of monosyllabic components that represent alternative phonetic pronunciations for at least a portion of the name, wherein monosyllabic components from the one or more sets of monosyllabic components are combinable to construct a phonetic pronunciation of the name; displaying the one or more sets of monosyllabic components; receiving a user selection of a monosyllabic component from each of the one or more sets of monosyllabic components; and combining the selected monosyllabic component from each of the one or more sets of monosyllabic components to construct the phonetic pronunciation of the name; wherein displaying the one or more sets of monosyllabic components comprises displaying a first portion of the one or more sets of monosyllabic components via a user interface, and further displaying a second portion of the one or more sets of monosyllabic components in response to a user selection of one of the first portion of the one or more sets of monosyllabic components. 2. The method of claim 1 comprising outputting the phonetic pronunciation via a user interface. | 0.605187 |
8. A system comprising: a processor; and a memory containing instructions that, when executed, cause the processor to: present, alongside a computer-generated puzzle: primary information describing a primary subject related to a selected clue or solution of the computer-generated puzzle; secondary information describing a secondary subject related to the primary subject; and wherein the primary information and secondary information have been received over a communications network from a first computing device; receive, from a second computing device, input indicating selection of the secondary information; replace the primary information with the secondary information; and designate the secondary subject matter as the primary subject. | 8. A system comprising: a processor; and a memory containing instructions that, when executed, cause the processor to: present, alongside a computer-generated puzzle: primary information describing a primary subject related to a selected clue or solution of the computer-generated puzzle; secondary information describing a secondary subject related to the primary subject; and wherein the primary information and secondary information have been received over a communications network from a first computing device; receive, from a second computing device, input indicating selection of the secondary information; replace the primary information with the secondary information; and designate the secondary subject matter as the primary subject. 9. The system of claim 8 , wherein the primary information is presented larger than the secondary information. | 0.65998 |
41. The method of claim 36 , wherein the order in which the web pages are initially presented is influenced by relevance feedback. | 41. The method of claim 36 , wherein the order in which the web pages are initially presented is influenced by relevance feedback. 43. The method of claim 41 , wherein the order in which the web pages are to be initially presented in the results list in response to the search query initiated by the user is influenced by relevance feedback received in a context other than a previous search query. | 0.91535 |
1. A text analysis method comprising: using processing circuitry, generating a first representation of a text item using a first measurement basis; using the processing circuitry, generating a second representation of the text item using a second measurement basis different than the first measurement basis, wherein the second representation is different than the first representation; using the processing circuitry, analyzing the text item using the first representation and the second representation; using the processing circuitry, steering the generating of at least one of the first and second representations according to a perspective of interest of a user; using the processing circuitry, accessing least one text pattern of interest to the user; using the processing circuitry, generating one of the first measurement basis and the second measurement basis using the at least one text pattern of interest to the user; and wherein the generating the one of the first measurement basis and the second measurement basis comprises generating the one of the first measurement basis and the second measurement basis to comprise associations of a plurality of measurement features in the form of text patterns with a plurality of dimension anchors which comprise different topics of textual content. | 1. A text analysis method comprising: using processing circuitry, generating a first representation of a text item using a first measurement basis; using the processing circuitry, generating a second representation of the text item using a second measurement basis different than the first measurement basis, wherein the second representation is different than the first representation; using the processing circuitry, analyzing the text item using the first representation and the second representation; using the processing circuitry, steering the generating of at least one of the first and second representations according to a perspective of interest of a user; using the processing circuitry, accessing least one text pattern of interest to the user; using the processing circuitry, generating one of the first measurement basis and the second measurement basis using the at least one text pattern of interest to the user; and wherein the generating the one of the first measurement basis and the second measurement basis comprises generating the one of the first measurement basis and the second measurement basis to comprise associations of a plurality of measurement features in the form of text patterns with a plurality of dimension anchors which comprise different topics of textual content. 3. The method of claim 1 wherein the first and second representations comprise vectors. | 0.604369 |
15. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with one or more processors and memory, cause the device to: generate a user interface for display on a display device, wherein the user interface includes a candidate character region; while the user interface is displayed on the display device, receive an indication of a first input that includes movement of a contact detected on a touch-sensitive surface of a device; in response to detecting the movement of the contact, identify a first candidate character that corresponds to the movement, and update the user interface to include the first candidate character in the candidate character region; receive a request to delete the first candidate character; and in response to receiving the request to delete the first candidate character and prior to receiving an input to replace the first candidate character with a different candidate character from a first plurality of other candidate characters, update the user interface by: deleting the first candidate character in the candidate character region; and displaying a first plurality of other candidate characters that correspond to the movement of the contact in place of the first candidate character. | 15. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with one or more processors and memory, cause the device to: generate a user interface for display on a display device, wherein the user interface includes a candidate character region; while the user interface is displayed on the display device, receive an indication of a first input that includes movement of a contact detected on a touch-sensitive surface of a device; in response to detecting the movement of the contact, identify a first candidate character that corresponds to the movement, and update the user interface to include the first candidate character in the candidate character region; receive a request to delete the first candidate character; and in response to receiving the request to delete the first candidate character and prior to receiving an input to replace the first candidate character with a different candidate character from a first plurality of other candidate characters, update the user interface by: deleting the first candidate character in the candidate character region; and displaying a first plurality of other candidate characters that correspond to the movement of the contact in place of the first candidate character. 18. The non-transitory computer readable storage medium of claim 15 , wherein the request to delete the first candidate character comprises a first swipe detected on the touch-sensitive surface of the device, and receiving the input to replace the first candidate character with a different candidate character from the first plurality of other candidate characters comprises receiving an indication of a second input that corresponds to selection of a respective one of the first plurality of other candidate characters; and the one or more programs further comprise instructions that cause the device to: in response to the second input, update the user interface to include the respective one of the first plurality of other candidate characters in the candidate character region. | 0.596988 |
5. A computer-implemented method for generating summaries for a plurality of documents comprising text, the method comprising: a) for each document in the plurality of documents, generating text structure tags for the document including generating text structure tags in accordance with Text Encoding Initiative (TEI), the text structure tags identifying a plurality of argumentative text types, wherein a text type comprises a type of argumentative content for an associated portion of a document, the types of argumentative content comprising an argument premise giving support, evidence, or reasoning for or against a conclusion or the conclusion comprising a resulting determination made using one or more argument premises; b) for each document in the plurality of documents, encoding the document to generate a tree structure comprising a plurality of nodes, wherein the nodes correspond with the text types and hierarchical relationships among the nodes reflect argumentative relationships among the text types, and wherein encoding the document comprises mapping a base hierarchical structure, utilizing DTD of the eXtensible Markup Language (“XML”), to reflect said hierarchical relationships; and processing the document to generate the tree structure in accordance with the base hierarchical structure; c) selecting a plurality of tree structures for the plurality of documents; d) combing, as a single logical tree structure, the plurality of tree structures; and e) generating a summary for the plurality of documents by: i) receiving from a user a selection of one or more particular text types for summarization, the one or more particular text types comprising the argument premise text type; and ii) identifying, based upon the text type tags, a set of nodes from the plurality of tree structures corresponding to the one or more selected text types including one or more nodes corresponding to the argument premise text type; and iii) extracting portions of text from the plurality of documents that correspond to the identified set of nodes selected to form the summary of the plurality of documents. | 5. A computer-implemented method for generating summaries for a plurality of documents comprising text, the method comprising: a) for each document in the plurality of documents, generating text structure tags for the document including generating text structure tags in accordance with Text Encoding Initiative (TEI), the text structure tags identifying a plurality of argumentative text types, wherein a text type comprises a type of argumentative content for an associated portion of a document, the types of argumentative content comprising an argument premise giving support, evidence, or reasoning for or against a conclusion or the conclusion comprising a resulting determination made using one or more argument premises; b) for each document in the plurality of documents, encoding the document to generate a tree structure comprising a plurality of nodes, wherein the nodes correspond with the text types and hierarchical relationships among the nodes reflect argumentative relationships among the text types, and wherein encoding the document comprises mapping a base hierarchical structure, utilizing DTD of the eXtensible Markup Language (“XML”), to reflect said hierarchical relationships; and processing the document to generate the tree structure in accordance with the base hierarchical structure; c) selecting a plurality of tree structures for the plurality of documents; d) combing, as a single logical tree structure, the plurality of tree structures; and e) generating a summary for the plurality of documents by: i) receiving from a user a selection of one or more particular text types for summarization, the one or more particular text types comprising the argument premise text type; and ii) identifying, based upon the text type tags, a set of nodes from the plurality of tree structures corresponding to the one or more selected text types including one or more nodes corresponding to the argument premise text type; and iii) extracting portions of text from the plurality of documents that correspond to the identified set of nodes selected to form the summary of the plurality of documents. 9. The method as set forth in claim 5 , further comprising: providing a visual hierarchy of the single logical tree structure; providing a user interface for receiving user selection of one or more particular nodes of the single logical tree structure; and extracting portions of text from the plurality of documents that correspond to said one or more selected nodes. | 0.647228 |
10. The system of claim 1 , the data store includes information relating to at least one of a device, system, process, and sub-process within the industrial automation environment. | 10. The system of claim 1 , the data store includes information relating to at least one of a device, system, process, and sub-process within the industrial automation environment. 13. The system of claim 10 , further comprising an updating component that automatically updates devices and their associated content in the data store based upon detecting the addition or removal of a device from a network, process or system. | 0.915201 |
1. A computer processor-implemented method for accessing environmental information, comprising the steps of: (a) receiving first environmental information regarding a proposed environment-modifying project, including information about project information, setting information, impact information, or mitigation information, wherein project information comprises information about an environment-modifying natural event or construction project; wherein setting information comprises information about a natural, constructed or socioeconomic feature in the area of the project; wherein impact information comprises information about a change to the setting brought about by the project; and wherein mitigation information comprises information about a feature designed to ameliorate a potential environmental impact of the project; (b) automatically associating at least some of the first environmental information within a source of information with metadata, including some interrelated project information, setting information, impact information, and mitigation information, wherein the metadata is selected from a controlled vocabulary or a user-defined vocabulary to characterize the first environmental information, at least some of the terms of metadata existing in an electronic thesaurus, wherein the electronic thesaurus comprises equivalent terms; (c) receiving a request from a computer for requested environmental information in the form of a search term, specific value or other user-specified indicator, the requested information being the first environmental information or any information associated with metadata or other information derived at least in part from the first environmental information; (d) relating the search term, specific value or other user-specified indicator to the metadata in the electronic thesaurus to facilitate identification of responsive sources of information corresponding to the requested environmental information; (e) identifying the responsive sources of information corresponding to the requested environmental information; and (f) displaying a listing of a plurality of responsive sources of information indicators, with the order of the responsive sources of information indicators corresponding to a weighting of metadata terms associated with the responsive sources of information. | 1. A computer processor-implemented method for accessing environmental information, comprising the steps of: (a) receiving first environmental information regarding a proposed environment-modifying project, including information about project information, setting information, impact information, or mitigation information, wherein project information comprises information about an environment-modifying natural event or construction project; wherein setting information comprises information about a natural, constructed or socioeconomic feature in the area of the project; wherein impact information comprises information about a change to the setting brought about by the project; and wherein mitigation information comprises information about a feature designed to ameliorate a potential environmental impact of the project; (b) automatically associating at least some of the first environmental information within a source of information with metadata, including some interrelated project information, setting information, impact information, and mitigation information, wherein the metadata is selected from a controlled vocabulary or a user-defined vocabulary to characterize the first environmental information, at least some of the terms of metadata existing in an electronic thesaurus, wherein the electronic thesaurus comprises equivalent terms; (c) receiving a request from a computer for requested environmental information in the form of a search term, specific value or other user-specified indicator, the requested information being the first environmental information or any information associated with metadata or other information derived at least in part from the first environmental information; (d) relating the search term, specific value or other user-specified indicator to the metadata in the electronic thesaurus to facilitate identification of responsive sources of information corresponding to the requested environmental information; (e) identifying the responsive sources of information corresponding to the requested environmental information; and (f) displaying a listing of a plurality of responsive sources of information indicators, with the order of the responsive sources of information indicators corresponding to a weighting of metadata terms associated with the responsive sources of information. 6. The method of claim 1 wherein the electronic thesaurus contains place names related to latitude and longitude, or other geographic identifier. | 0.519531 |
2. The method of claim 1 , further comprising: determining whether the computer has an already-installed text-to-speech engine that is compatible with a routine for performing the method; and if the computer does not have an already-installed text-to-speech engine that is compatible with the routine, installing on the computer a newly-installed compatible text-to-speech engine that is compatible with the routine. | 2. The method of claim 1 , further comprising: determining whether the computer has an already-installed text-to-speech engine that is compatible with a routine for performing the method; and if the computer does not have an already-installed text-to-speech engine that is compatible with the routine, installing on the computer a newly-installed compatible text-to-speech engine that is compatible with the routine. 3. The method of claim 2 , wherein: the at least one input comprises an indication that the user would not like to use auditory prompts for the installation; and if the computer does not have the already-installed text-to-speech engine, conducting the installation in accordance with the at least one input comprises removing the newly-installed compatible text-to-speech engine from the computer responsive to the indication that the user would not like to use auditory prompts for the installation of the application program. | 0.617284 |
8. A method comprising: recognizing, by use of a processor, two or more logogram radicals; and generating one or more logogram phrases for the two or more logogram radicals, wherein each logogram phrase comprises a first logogram embodying a first logogram radical of the two or more logogram radicals and a second logogram embodying a second logogram radical of the two or more logogram radicals. | 8. A method comprising: recognizing, by use of a processor, two or more logogram radicals; and generating one or more logogram phrases for the two or more logogram radicals, wherein each logogram phrase comprises a first logogram embodying a first logogram radical of the two or more logogram radicals and a second logogram embodying a second logogram radical of the two or more logogram radicals. 13. The method of claim 8 , the method further comprising: displaying a first logogram list of logograms embodying the first logogram radical of the two or more logogram radicals based on a usage history; and receiving a selection of a first logogram from the first logogram list, wherein the one or more logogram phrases are generated in response to the first logogram and the second logogram radical of the two or more logogram radicals. | 0.60307 |
1. A search system, comprising: a relevance model stored on a computer readable medium; a computer processor that applies the relevance model to a query so as to identify a query result and generate a relevance score indicative of relevancy of the query result to the query; a co-occurrence model, stored on the computer readable medium, for determining textual co-occurrences within a predefined portion of the query result, that comprises less than all of the query result, wherein the computer processor: identifies, from the query result, a plurality of persons related to a subject matter of the query; and applies the co-occurrence model to the query result to generate a co-occurrence score based on a number of textual co-occurrences of both the subject matter of the query and a name of the plurality of persons within the predefined portion of the query result; and a ranking component that generates a ranked list of the plurality of persons based at least in part on the relevance score for the query result and the co-occurrence score. | 1. A search system, comprising: a relevance model stored on a computer readable medium; a computer processor that applies the relevance model to a query so as to identify a query result and generate a relevance score indicative of relevancy of the query result to the query; a co-occurrence model, stored on the computer readable medium, for determining textual co-occurrences within a predefined portion of the query result, that comprises less than all of the query result, wherein the computer processor: identifies, from the query result, a plurality of persons related to a subject matter of the query; and applies the co-occurrence model to the query result to generate a co-occurrence score based on a number of textual co-occurrences of both the subject matter of the query and a name of the plurality of persons within the predefined portion of the query result; and a ranking component that generates a ranked list of the plurality of persons based at least in part on the relevance score for the query result and the co-occurrence score. 6. The system of claim 1 , wherein the predefined portion of the query result comprises one of: a body portion of the query result; a body portion and a title of the query result; a body portion and an author section of the query result; an anchor text portion and a body portion of the query result; and a title and author section of the query result. | 0.777168 |
1. A computer-based method for searching a data set for one or more data values, comprising: obtaining a data block of the data set; traversing a graph rule set based at least in part upon a current state of said graph rule set and said data block, wherein a value of said data block falls within a predefined range of values of said graph rule set, and wherein said graph rule set is a graph representation of a set of rules; identifying a rule of said set of rules as a function of traversal of said graph rule set for the data set, wherein said set of rules describes the one or more data values; wherein traversing a link of said graph rule set comprises comparing said data block with a value range not specified in said identified rule; and modifying said data set by attaching a flag to said data set. | 1. A computer-based method for searching a data set for one or more data values, comprising: obtaining a data block of the data set; traversing a graph rule set based at least in part upon a current state of said graph rule set and said data block, wherein a value of said data block falls within a predefined range of values of said graph rule set, and wherein said graph rule set is a graph representation of a set of rules; identifying a rule of said set of rules as a function of traversal of said graph rule set for the data set, wherein said set of rules describes the one or more data values; wherein traversing a link of said graph rule set comprises comparing said data block with a value range not specified in said identified rule; and modifying said data set by attaching a flag to said data set. 10. The method of claim 1 , wherein said one or more data values are indicative of undesired data. | 0.752163 |
8. A method for automatically presenting a search interface facility on a display comprising: receiving a search criteria; determining that a first plurality of files within a first file location of a computer system satisfy the search criteria; selecting a second file location of a computer system that is outside of the first file location to search for files that satisfy the search criteria; determining that the second file location includes a second plurality of files that satisfy the search criteria; and outputting for display a search interface that communicates search results based on the first plurality of files and indicates additional files are in the second file location that match the search criteria; wherein determining that a first plurality of files within a first file location of a computer system satisfy the search criteria comprises performing deep file searching or searching on file attributes. | 8. A method for automatically presenting a search interface facility on a display comprising: receiving a search criteria; determining that a first plurality of files within a first file location of a computer system satisfy the search criteria; selecting a second file location of a computer system that is outside of the first file location to search for files that satisfy the search criteria; determining that the second file location includes a second plurality of files that satisfy the search criteria; and outputting for display a search interface that communicates search results based on the first plurality of files and indicates additional files are in the second file location that match the search criteria; wherein determining that a first plurality of files within a first file location of a computer system satisfy the search criteria comprises performing deep file searching or searching on file attributes. 9. The method of claim 8 , wherein the second file location is searched regardless an amount of files in the first plurality of files. | 0.573423 |
8. A system for linking items into a matter comprising: a computing device that comprises a memory component that stores at least the following: content master that causes the computing device to retrieve an electronic document from a source; a linking component that causes the computing device to perform at least the following: determine whether the electronic document is associated with a predetermined first matter; in response to determining that the electronic document is associated with the predetermined first matter, link the electronic document to the predetermined first matter, such that accessing the electronic document will provide access to other documents linked to the predetermined first matter; and in response to determining that the electronic document is not associated with the predetermined first matter, create a second matter and link the electronic document to the second matter, such that accessing the electronic document will provide other documents linked to the second matter; and search logic that causes the computing device to receive a request for the electronic document and, in response to receiving the request for the electronic document, provide a user option to provide access to the other documents linked to the predetermined first matter. | 8. A system for linking items into a matter comprising: a computing device that comprises a memory component that stores at least the following: content master that causes the computing device to retrieve an electronic document from a source; a linking component that causes the computing device to perform at least the following: determine whether the electronic document is associated with a predetermined first matter; in response to determining that the electronic document is associated with the predetermined first matter, link the electronic document to the predetermined first matter, such that accessing the electronic document will provide access to other documents linked to the predetermined first matter; and in response to determining that the electronic document is not associated with the predetermined first matter, create a second matter and link the electronic document to the second matter, such that accessing the electronic document will provide other documents linked to the second matter; and search logic that causes the computing device to receive a request for the electronic document and, in response to receiving the request for the electronic document, provide a user option to provide access to the other documents linked to the predetermined first matter. 12. The system of claim 8 , wherein the computing device further stores a data acquisition component that causes the computing device to determine the source from which to retrieve the electronic document, the source being determined from a plurality of sources, wherein retrieving the electronic document includes requesting content, based on the source that was determined. | 0.5 |
9. A computer-implemented method to generate an index for a closest match search, the method comprising: receiving a corpus of information including a plurality of member information, the plurality of member information including first member information that describes a first member and other member information that describes a plurality of other members; using a data processor to generate a plurality of candidate signatures based on the corpus of information, the plurality of candidate signatures including a first plurality of candidate signatures and a second plurality of candidate signatures, the generating of the first plurality of candidate signatures based on the first member information and the generating of the second plurality of candidate signatures based on the other member information; identifying a plurality of index signatures based on the plurality of candidate signatures, the plurality of index signatures including a first plurality of index signatures, the first plurality of index signatures further included in the first plurality of candidate signatures and not included in the second plurality of candidate signatures to signify the first member and not any of the plurality of other members; storing the plurality of index signatures in the index in association with the first member to enable a closest match of input information to at least one of the plurality of index signatures to identify a closest match of the input information to the first member over the plurality of other members; and generating a first plurality of candidate signature scores respectively associated with the first plurality of candidate signatures, the first plurality of candidate signatures including a first candidate signature and a first candidate signature score that is associated with the first candidate signature, the first candidate signature score represents a percentage of coverage of the first signature over the first member information. | 9. A computer-implemented method to generate an index for a closest match search, the method comprising: receiving a corpus of information including a plurality of member information, the plurality of member information including first member information that describes a first member and other member information that describes a plurality of other members; using a data processor to generate a plurality of candidate signatures based on the corpus of information, the plurality of candidate signatures including a first plurality of candidate signatures and a second plurality of candidate signatures, the generating of the first plurality of candidate signatures based on the first member information and the generating of the second plurality of candidate signatures based on the other member information; identifying a plurality of index signatures based on the plurality of candidate signatures, the plurality of index signatures including a first plurality of index signatures, the first plurality of index signatures further included in the first plurality of candidate signatures and not included in the second plurality of candidate signatures to signify the first member and not any of the plurality of other members; storing the plurality of index signatures in the index in association with the first member to enable a closest match of input information to at least one of the plurality of index signatures to identify a closest match of the input information to the first member over the plurality of other members; and generating a first plurality of candidate signature scores respectively associated with the first plurality of candidate signatures, the first plurality of candidate signatures including a first candidate signature and a first candidate signature score that is associated with the first candidate signature, the first candidate signature score represents a percentage of coverage of the first signature over the first member information. 11. The method of claim 9 , wherein the first plurality of index signatures includes a plurality of features, wherein the plurality of features includes a first feature of the first member. | 0.594789 |
6. A method for discovering association rules using item constraints, the method comprising: generating a set of selected items from a database based on predefined constraints, the predefined constraints involving one or more items of a mining input expression; determining a support value for an itemset based upon the number of times the itemset appears in the database; entering the itemset into a set of large itemsets if the support value of the itemset is greater than a minimum support value and the itemset contains at least one of the selected items; and outputting an association rule when the number of times the entered itemset appears in the database bears a predetermined relationship to a number of times an associated itemset appears in the database and thereby satisfies a minimum confidence constraint. | 6. A method for discovering association rules using item constraints, the method comprising: generating a set of selected items from a database based on predefined constraints, the predefined constraints involving one or more items of a mining input expression; determining a support value for an itemset based upon the number of times the itemset appears in the database; entering the itemset into a set of large itemsets if the support value of the itemset is greater than a minimum support value and the itemset contains at least one of the selected items; and outputting an association rule when the number of times the entered itemset appears in the database bears a predetermined relationship to a number of times an associated itemset appears in the database and thereby satisfies a minimum confidence constraint. 8. The method recited in claim 6, further comprising: determining whether sets contained in the large itemsets satisfy the predefined constraints; generating a set of candidate itemsets including large itemsets which satisfy the predefined constraints; and using the set of candidate itemsets to output the association rules. | 0.722822 |
1. A method, implemented at a computer system that includes one or more processors, for solving in the context of a model that includes a plurality of model variables, the method comprising: an act of the computer system displaying a user interface, the user interface including: an equation edit area that displays a plurality of equations that represent analytical relationships between a plurality of model variables; and an output variable edit area that is distinct from and visually distinguished from the equation edit area in the user interface and that is configured to receive user input that specifies a subset of the plurality of model variables as output model variables that are to be solved for within the model using the plurality of equations, wherein the output variable edit area is also configured to allow a user to input different sets of model variables that are to be solved for using the plurality of equations without modifying the plurality of equations in the equation edit area; an act of the computer system receiving first user input at the output variable edit area that specifies a first subset of one or more of the plurality of model variables as output model variables that are to be solved for using the plurality of equations; based on receiving the first user input, an act of the computer system formulating an output variable data structure that identifies the first subset of output model variables; an act of the computer system formulating an equation data structure that represents the analytical relationships between the plurality of model variables of the plurality of equations; based on receiving the first user input, an act of the computer system automatically solving the plurality of equations for the first subset of output model variables using a solver framework; subsequent to solving the plurality of equations, an act of the computer system receiving second user input at the output variable edit area that specifies a second subset of one or more of the plurality of model variables as output model variables, wherein the second subset is different than the first subset; based on receiving the second user input, an act of the computer system modifying the output variable data structure to identify the second subset of output model variables; and based on receiving the second user input, an act of the computer system using the solver framework to automatically solve the plurality of equations for the second subset of output model variables, without modifying the plurality of equations in the equation edit area, wherein the solver framework does not change depending on the identity of the subset of output model variables identified in the output variable data structure. | 1. A method, implemented at a computer system that includes one or more processors, for solving in the context of a model that includes a plurality of model variables, the method comprising: an act of the computer system displaying a user interface, the user interface including: an equation edit area that displays a plurality of equations that represent analytical relationships between a plurality of model variables; and an output variable edit area that is distinct from and visually distinguished from the equation edit area in the user interface and that is configured to receive user input that specifies a subset of the plurality of model variables as output model variables that are to be solved for within the model using the plurality of equations, wherein the output variable edit area is also configured to allow a user to input different sets of model variables that are to be solved for using the plurality of equations without modifying the plurality of equations in the equation edit area; an act of the computer system receiving first user input at the output variable edit area that specifies a first subset of one or more of the plurality of model variables as output model variables that are to be solved for using the plurality of equations; based on receiving the first user input, an act of the computer system formulating an output variable data structure that identifies the first subset of output model variables; an act of the computer system formulating an equation data structure that represents the analytical relationships between the plurality of model variables of the plurality of equations; based on receiving the first user input, an act of the computer system automatically solving the plurality of equations for the first subset of output model variables using a solver framework; subsequent to solving the plurality of equations, an act of the computer system receiving second user input at the output variable edit area that specifies a second subset of one or more of the plurality of model variables as output model variables, wherein the second subset is different than the first subset; based on receiving the second user input, an act of the computer system modifying the output variable data structure to identify the second subset of output model variables; and based on receiving the second user input, an act of the computer system using the solver framework to automatically solve the plurality of equations for the second subset of output model variables, without modifying the plurality of equations in the equation edit area, wherein the solver framework does not change depending on the identity of the subset of output model variables identified in the output variable data structure. 9. The method in accordance with claim 1 , wherein the act of automatically solving for the first subset of output model variables comprises at act of solving for at least one of the one or more output model variables using a symbolic solve. | 0.585427 |
1. A method comprising: receiving a code sequence from an input interface including a processor, along with a hardware resource count specifying a number of hardware resources that are to be allocated for the code sequence, in a high-level language program; generating hardware acceleration logic for implementing the code sequence using the number of hardware resources specified by the hardware resource count, wherein the number of hardware resources is associated with an amount of logic used to implement the code sequence on a programmable device; and implementing the hardware acceleration logic on the programmable device. | 1. A method comprising: receiving a code sequence from an input interface including a processor, along with a hardware resource count specifying a number of hardware resources that are to be allocated for the code sequence, in a high-level language program; generating hardware acceleration logic for implementing the code sequence using the number of hardware resources specified by the hardware resource count, wherein the number of hardware resources is associated with an amount of logic used to implement the code sequence on a programmable device; and implementing the hardware acceleration logic on the programmable device. 5. The method of claim 1 , wherein the number of hardware resources corresponds to a number of functional blocks used to implement the code sequence. | 0.524759 |
20. A non-transitory computer-readable medium storing a set of programmable instructions configured for being executed by at least one processor for performing a method for counting and recording a document set, and generating a summary report corresponding to the document set, the method comprising: performing a document scanning procedure whereby a document set is scanned by a scanning assembly of a multi-function machine of the type having the capability of performing at least the functions of scanning, copying, and electronically transmitting documents; enabling a user to select whether to count the number of documents in the document set and/or whether to count the number of images in the document set; receiving at least one input and determining whether the user selected to count the number of documents in the document set and/or whether the user selected to count the number of images in the document set; counting the number of documents in the document set scanned during the document scanning procedure if the user selected to count the number of documents in the document set; counting the number of images in the document set scanned during the document scanning procedure if the user selected to count the number of images in the document set; generating a summary report corresponding to the document set; and dispatching the summary report to at least one destination. | 20. A non-transitory computer-readable medium storing a set of programmable instructions configured for being executed by at least one processor for performing a method for counting and recording a document set, and generating a summary report corresponding to the document set, the method comprising: performing a document scanning procedure whereby a document set is scanned by a scanning assembly of a multi-function machine of the type having the capability of performing at least the functions of scanning, copying, and electronically transmitting documents; enabling a user to select whether to count the number of documents in the document set and/or whether to count the number of images in the document set; receiving at least one input and determining whether the user selected to count the number of documents in the document set and/or whether the user selected to count the number of images in the document set; counting the number of documents in the document set scanned during the document scanning procedure if the user selected to count the number of documents in the document set; counting the number of images in the document set scanned during the document scanning procedure if the user selected to count the number of images in the document set; generating a summary report corresponding to the document set; and dispatching the summary report to at least one destination. 22. The non-transitory computer-readable medium according to claim 20 , wherein the generating step further comprises setting forth in the summary report the number of images in the document set. | 0.573027 |
14. The device according to claim 9 , wherein the adjusting component comprises: a first determining element, configured to determine a caption sequence number of the caption content according to the found caption content; a second determining element, configured to acquire a playback time period corresponding to the found caption content according to the caption sequence number, and determine initial playback time point corresponding to the found caption content within the playback time period; and an adjusting element, configured to adjust the playback progress according to the playback time point. | 14. The device according to claim 9 , wherein the adjusting component comprises: a first determining element, configured to determine a caption sequence number of the caption content according to the found caption content; a second determining element, configured to acquire a playback time period corresponding to the found caption content according to the caption sequence number, and determine initial playback time point corresponding to the found caption content within the playback time period; and an adjusting element, configured to adjust the playback progress according to the playback time point. 15. The device according to claim 14 , wherein the receiving component comprises: a first receiving element, configured to receive input text information; and a second receiving component, configured to receive audio data, and convert the audio data into the text information. | 0.777066 |
15. The computer-implemented method of claim 1 , wherein identifying multiple sets of weighting values for the plurality of language models comprises identifying multiple sets of weighting values that bias selection of language models, each of the multiple sets of weighting values biasing selection of language models for recognizing utterances in audio input when a key phrase associated with the set of weighting values is recognized in the audio input. | 15. The computer-implemented method of claim 1 , wherein identifying multiple sets of weighting values for the plurality of language models comprises identifying multiple sets of weighting values that bias selection of language models, each of the multiple sets of weighting values biasing selection of language models for recognizing utterances in audio input when a key phrase associated with the set of weighting values is recognized in the audio input. 16. The computer-implemented method of claim 15 , wherein selecting, from among the multiple sets of weighting values, the set of weighting values associated with the first key phrase comprises selecting the first set of multiple weighting values based on determining that the first docking context indicates docking of the client device with the first docking station of the first type, without recognizing the first key phrase associated with the first set of multiple weighting values. | 0.914927 |
1. A method comprising: a speech-analysis platform receiving speech data representing at least part of a speech session; the speech-analysis platform comparing the speech data with each of at least one stored speech-characteristics profile in an automated manner, wherein each such profile is associated with a person that is a target of surveillance, wherein the comparing step comprises using natural-language-processing (NLP) to compare the speech data with the at least one stored speech-characteristics profile on each of a lexical level, a syntactic level, a semantic level, and a discourse level, wherein said using of NLP does not comprise conducting voiceprint analysis; the speech-analysis platform determining in an automated manner from said using of NLP whether the speech data matches any of the profiles; and if the speech-analysis platform determines from said using of NLP that the speech data matches at least one of the profiles on each of the lexical level, the syntactic level, the semantic level, and the discourse level, the speech-analysis platform responsively storing an indication that the speech data matches at least one of the profiles. | 1. A method comprising: a speech-analysis platform receiving speech data representing at least part of a speech session; the speech-analysis platform comparing the speech data with each of at least one stored speech-characteristics profile in an automated manner, wherein each such profile is associated with a person that is a target of surveillance, wherein the comparing step comprises using natural-language-processing (NLP) to compare the speech data with the at least one stored speech-characteristics profile on each of a lexical level, a syntactic level, a semantic level, and a discourse level, wherein said using of NLP does not comprise conducting voiceprint analysis; the speech-analysis platform determining in an automated manner from said using of NLP whether the speech data matches any of the profiles; and if the speech-analysis platform determines from said using of NLP that the speech data matches at least one of the profiles on each of the lexical level, the syntactic level, the semantic level, and the discourse level, the speech-analysis platform responsively storing an indication that the speech data matches at least one of the profiles. 12. The method of claim 1 , further comprising: if the speech-analysis platform determines that the speech data matches at least one of the profiles on each of the lexical level, the syntactic level, the semantic level, and the discourse level, the speech-analysis platform responsively further carrying out at least one of recording the speech session, alerting a monitoring entity of the match between the speech data and the at least one matching profile, and forwarding a copy of the speech session to a monitoring entity. | 0.5 |
1. A computer-implemented method comprising: associating external query data having one or more query field values with a record in a linked hierarchical database, the linked hierarchical database comprising a plurality of records, each record having a record identifier and representing an entity in a hierarchy, each record associated with a hierarchy level, each record comprising one or more fields, each field configured to contain a field value, the associating comprising: receiving the external query data, wherein the external query data comprises one or more search values; and identifying, from the plurality of records in the linked hierarchical database, one or more matched fields having field values that at least partially match the one or more search values; scoring, with zero or more match weights, each of the one or more matched fields; determining an aggregate weight for each matched field based at least in part on the scoring with the zero or more match weights; merging, based at least in part on determining the aggregate weights, the one or more matched fields to form a merged table having records with matched fields; scoring the merged table based at least in part on the aggregate weights; identifying, based at least in part on the scoring, a grouping comprising one or more of the plurality of entities within a same branch of the hierarchy and corresponding to different hierarchy levels; and outputting, based at least in part on the scoring and identifying, a record identifier corresponding to a matching entity in the hierarchy. | 1. A computer-implemented method comprising: associating external query data having one or more query field values with a record in a linked hierarchical database, the linked hierarchical database comprising a plurality of records, each record having a record identifier and representing an entity in a hierarchy, each record associated with a hierarchy level, each record comprising one or more fields, each field configured to contain a field value, the associating comprising: receiving the external query data, wherein the external query data comprises one or more search values; and identifying, from the plurality of records in the linked hierarchical database, one or more matched fields having field values that at least partially match the one or more search values; scoring, with zero or more match weights, each of the one or more matched fields; determining an aggregate weight for each matched field based at least in part on the scoring with the zero or more match weights; merging, based at least in part on determining the aggregate weights, the one or more matched fields to form a merged table having records with matched fields; scoring the merged table based at least in part on the aggregate weights; identifying, based at least in part on the scoring, a grouping comprising one or more of the plurality of entities within a same branch of the hierarchy and corresponding to different hierarchy levels; and outputting, based at least in part on the scoring and identifying, a record identifier corresponding to a matching entity in the hierarchy. 3. The method of claim 1 , further comprising: sorting the one or more matched fields according to the determined aggregate weights; at least partially forming one or more search tables corresponding to the one or more search values; and at least partially forming one or more base tables corresponding to the one or more fields of the plurality of records of the linked hierarchical database; and wherein the merging, based at least in part on determining the aggregate weights, comprises combining at least a portion of the one or more search tables and the one or more base tables to form the merged table. | 0.662505 |
6. A keyboard, as in claim 2, for the Spanish language comprising letter and control keys arranged as follows: on the left hand side of the keyboard as viewed by the operator: on the thumb key row: U assigned to the first thumb key and space key is assigned to the second thumb key; on the home row: O assigned to the second home key, I assigned to the third home key, A assigned to the fourth home key, and E assigned to the fifth home key; and on the lower letter row: case shift assigned to the third lower letter key; and on the right hand side of the keyboard as viewed by the operator: on the thumb key row: L assigned to the fourth thumb key and R assigned to the fifth thumb key; on the home key row: S assigned to the eighth home key, T assigned to the ninth home key, N assigned to the tenth home key, and D assigned to the eleventh home key; and on the lower letter key row; G assigned to the fifth lower letter key, V assigned to the sixth lower letter key, M assigned to the seventh lower letter key, and C assigned to the eighth lower letter key. | 6. A keyboard, as in claim 2, for the Spanish language comprising letter and control keys arranged as follows: on the left hand side of the keyboard as viewed by the operator: on the thumb key row: U assigned to the first thumb key and space key is assigned to the second thumb key; on the home row: O assigned to the second home key, I assigned to the third home key, A assigned to the fourth home key, and E assigned to the fifth home key; and on the lower letter row: case shift assigned to the third lower letter key; and on the right hand side of the keyboard as viewed by the operator: on the thumb key row: L assigned to the fourth thumb key and R assigned to the fifth thumb key; on the home key row: S assigned to the eighth home key, T assigned to the ninth home key, N assigned to the tenth home key, and D assigned to the eleventh home key; and on the lower letter key row; G assigned to the fifth lower letter key, V assigned to the sixth lower letter key, M assigned to the seventh lower letter key, and C assigned to the eighth lower letter key. 11. A keyboard, as in claim 6, for the Spanish language comprising character and control keys arranged in serial order along key rows as viewed by the operator from the outer edge of the keyboard to the center of the keyboard as follows: on the left hand sides of the keyboard as viewed by the operator: along the thumb key row: U assigned to the first thumb key, space key is assigned to the second thumb key, and the carriage return assigned to the third thumb key; along the home key row: O assigned to the second home key, I assigned to the third home key, A assigned to the fourth home key, E assigned to the fifth home key, and (lower case: hyphen; upper case: underline) assigned to the sixth home key; along the lower letter key row: (lower case: period; upper case: period) assigned to the first lower letter key, (lower case: comma; upper case: comma) assigned to the second lower letter key, case shift assigned to the third lower letter key, and (lower case: accent acute; upper case: accent acute) assigned to the fourth lower letter key; and along the upper letter key: (lower case: inverted exclamation point; upper case: exclamation point) assigned to the third upper letter key, and (lower case: inverted question mark; upper case: question mark) assigned to the fifth upper letter key; on the right hand side of the keyboard as viewed by the operator: along the thumb key row: L assigned to the fourth thumb key, R assigned to the fifth thumb key, and H assigned to the sixth thumb key; along the home key row: Y assigned to the seventh home key, S assigned to the eighth home key, T assigned to the ninth home key, N assigned to the tenth home key, D assigned to the eleventh home key, and P assigned to the twelfth home key; along the lower letter key row: G assigned to the fifth lower letter key, V assigned to the sixth lower letter key, M assigned to the seventh lower letter key, C assigned to the eighth lower letter key; and along the upper letter key row: N assigned to the seventh upper letter key, Z assigned to the eighth upper letter key, F assigned to the ninth upper letter key, Q assigned to the tenth upper letter key, B assigned to the eleventh upper letter key, and J assigned to the twelfth upper letter key; and in the center of the keyboard as viewed by the operator; the code key and function keys. | 0.741185 |
6. The method of claim 5 , wherein the greed agglomerative search process further includes: calculating each clustering's probability by evaluating it within the Bayesian belief network. | 6. The method of claim 5 , wherein the greed agglomerative search process further includes: calculating each clustering's probability by evaluating it within the Bayesian belief network. 7. The method of claim 6 , wherein the greedy agglomerative search process further includes: selecting a clustering with a highest probability. | 0.955898 |
1. A method of transforming data into computer executable rules for mining and constructing situation categories that are applied to information technology resource messages or events comprising: receiving computer readable data by a computer processing device from at least one of: a raw log and a catalog, where the received data is at least one of: initial seed data and knowledge data, to derive the computer executable rules for mining and constructing situation categories; transforming the received data into a predetermined standard format if the received data is not already in the predetermined standard format; parsing the predetermined standard formatted data; performing an outer, iterative loop until at least one predetermined stopping criterion is met, comprising: utilizing a keyword rule classifier by the computer processing device to automatically pre-classify at least a portion of the parsed data; performing an inner iterative loop within the outer iterative loop, comprising: selecting a subset of the parsed data for expert review; using at least one of keyword rules, features, and classifications to find, within data available to the computer processing device, a corresponding previously labeled subset of data that has similar semantics to semantics of the selected subset of data; labeling the selected subset of data with the label associated with the corresponding previously labeled subset of data; and repeating the inner iterative loop if another subset of data is to be processed; storing each labeled subset of data on a data storage device; generating new computer executable rules for mining and constructing situation categories from the stored labeled subsets of data; transforming keyword list classifiers using the stored labeled subsets of data; and repeating the outer iterative loop if the predetermined stopping criterion is not met. | 1. A method of transforming data into computer executable rules for mining and constructing situation categories that are applied to information technology resource messages or events comprising: receiving computer readable data by a computer processing device from at least one of: a raw log and a catalog, where the received data is at least one of: initial seed data and knowledge data, to derive the computer executable rules for mining and constructing situation categories; transforming the received data into a predetermined standard format if the received data is not already in the predetermined standard format; parsing the predetermined standard formatted data; performing an outer, iterative loop until at least one predetermined stopping criterion is met, comprising: utilizing a keyword rule classifier by the computer processing device to automatically pre-classify at least a portion of the parsed data; performing an inner iterative loop within the outer iterative loop, comprising: selecting a subset of the parsed data for expert review; using at least one of keyword rules, features, and classifications to find, within data available to the computer processing device, a corresponding previously labeled subset of data that has similar semantics to semantics of the selected subset of data; labeling the selected subset of data with the label associated with the corresponding previously labeled subset of data; and repeating the inner iterative loop if another subset of data is to be processed; storing each labeled subset of data on a data storage device; generating new computer executable rules for mining and constructing situation categories from the stored labeled subsets of data; transforming keyword list classifiers using the stored labeled subsets of data; and repeating the outer iterative loop if the predetermined stopping criterion is not met. 3. The method of claim 1 , further comprising: creating an event to situation catalog if the source of the received computer readable data is from a catalog. | 0.777667 |
8. A method for finding phrases in a corpus of documents using a data processor, wherein the words in the corpus of documents include a set of stopwords, comprising: storing an index structure on a medium readable by the data processor, the index structure mapping entries in the index structure to documents in the corpus, the index structure including entries representing words found in the corpus of documents associated with locations of the words in the documents, and entries representing marks which identify a characteristic of corresponding marked words associated with locations of the marked words in the documents, and wherein one or more entries representing marks include fewer, if any, than all of the characters of the corresponding marked words; modifying an input phrase query provided to the data processor to form a modified query by adding a mark corresponding to a word in a subject phrase; and executing the modified query using said index structure and the data processor; wherein at least one entry representing a mark in the index structure comprises a token representing a type of mark coalesced with a prefix of a corresponding marked word, the prefix comprising one or more leading characters of the corresponding marked word. | 8. A method for finding phrases in a corpus of documents using a data processor, wherein the words in the corpus of documents include a set of stopwords, comprising: storing an index structure on a medium readable by the data processor, the index structure mapping entries in the index structure to documents in the corpus, the index structure including entries representing words found in the corpus of documents associated with locations of the words in the documents, and entries representing marks which identify a characteristic of corresponding marked words associated with locations of the marked words in the documents, and wherein one or more entries representing marks include fewer, if any, than all of the characters of the corresponding marked words; modifying an input phrase query provided to the data processor to form a modified query by adding a mark corresponding to a word in a subject phrase; and executing the modified query using said index structure and the data processor; wherein at least one entry representing a mark in the index structure comprises a token representing a type of mark coalesced with a prefix of a corresponding marked word, the prefix comprising one or more leading characters of the corresponding marked word. 9. The method of claim 8 , wherein the prefix comprises N leading characters of the marked word, and N is 3 or less. | 0.802852 |
3. The computerized system of claim 1 , wherein the first tuple stored in association with the user comprises a personal triple. | 3. The computerized system of claim 1 , wherein the first tuple stored in association with the user comprises a personal triple. 4. The computerized system of claim 3 , wherein: the personal triple includes three segments; and at least one of the three segments is associated with the user profile. | 0.953399 |
15. The method of claim 13 , wherein making the determination to erase the scribble input further comprises detecting a passing of a predetermined amount of time after receiving the scribble input without receiving additional input. | 15. The method of claim 13 , wherein making the determination to erase the scribble input further comprises detecting a passing of a predetermined amount of time after receiving the scribble input without receiving additional input. 16. The method of claim 15 , further comprising receiving an indication to cancel erasing the scribble input and cancelling erasing the scribble input. | 0.916904 |
1. A system for linking information from at least two data sources, the system comprising: a first data source comprising a plurality of documents comprising text pertaining to at least one object; a second data source comprising a plurality of structured records comprising at least one characteristic of the at least one object, each characteristic comprising one property name and an associated property value corresponding to the property name for the at least one object; a processor for determining one or more traits for each object and for associating at least one record in the second data source with the at least one document from the first data source that refers to each object, wherein each trait is instance-based and comprises at least one characteristic that serves as a proxy for identifying each object from all other objects in the plurality of documents, and wherein at least one of the one or more traits has a different number of characteristics than another trait; and wherein the system determines that an association of a first trait to a first record is correct if a first text from a first document pertains to either the first record or to an accessory of the product represented by the first record. | 1. A system for linking information from at least two data sources, the system comprising: a first data source comprising a plurality of documents comprising text pertaining to at least one object; a second data source comprising a plurality of structured records comprising at least one characteristic of the at least one object, each characteristic comprising one property name and an associated property value corresponding to the property name for the at least one object; a processor for determining one or more traits for each object and for associating at least one record in the second data source with the at least one document from the first data source that refers to each object, wherein each trait is instance-based and comprises at least one characteristic that serves as a proxy for identifying each object from all other objects in the plurality of documents, and wherein at least one of the one or more traits has a different number of characteristics than another trait; and wherein the system determines that an association of a first trait to a first record is correct if a first text from a first document pertains to either the first record or to an accessory of the product represented by the first record. 6. The system of claim 1 , wherein the processor further computes an N-gram computation derived from a corpus in order to identify at least one invalid trait, and wherein the processor further prunes at least one instance-based trait based on the N-gram computation. | 0.5 |
1. An instrument for the analysis of rhythmic measures of speech comprising at least one input device having means for manual input solely of a series of discrete input signals representing an input rhythm corresponding to a spoken sequence of syllables, and an output device responsive to the discrete input signals to provide a representation of the input rhythm of a group of the discrete input signals and an indication of a correspondence of said group to a known or predetermined rhythmic group of rhythmic measures of speech stored in the instrument, thus to provide an analysis of the relationship between the spoken sequence of syllables and the known or predetermined rhythmic group. | 1. An instrument for the analysis of rhythmic measures of speech comprising at least one input device having means for manual input solely of a series of discrete input signals representing an input rhythm corresponding to a spoken sequence of syllables, and an output device responsive to the discrete input signals to provide a representation of the input rhythm of a group of the discrete input signals and an indication of a correspondence of said group to a known or predetermined rhythmic group of rhythmic measures of speech stored in the instrument, thus to provide an analysis of the relationship between the spoken sequence of syllables and the known or predetermined rhythmic group. 16. The instrument of claim 1, wherein said means for manual input comprises at least one input key. | 0.695247 |
5. A method of operating a speech recognition system, said method comprising the steps of: identifying a speaker by text-independent comparison of an input speech signal with a stored representation of speech signals corresponding to one of a plurality of speakers, said input speech signal including a plurality of words, providing a speech processing model to said speech recognition system in accordance with results of said identifying step, and recognizing said plurality of words within said input speech signal with said speech processing model, said stored representation of speech signals and said speech processing model being loaded into said system only once for recognition of said speaker and said plurality of words in said input speech signal so that said system performs continues speech recognition for said plurality of words, determining whether to perform speech recognition in one of a speaker-independent mode or a speaker-dependent mode; and selecting said speech processing model to be a speaker-dependent model or a speaker-independent model based on said determining step. | 5. A method of operating a speech recognition system, said method comprising the steps of: identifying a speaker by text-independent comparison of an input speech signal with a stored representation of speech signals corresponding to one of a plurality of speakers, said input speech signal including a plurality of words, providing a speech processing model to said speech recognition system in accordance with results of said identifying step, and recognizing said plurality of words within said input speech signal with said speech processing model, said stored representation of speech signals and said speech processing model being loaded into said system only once for recognition of said speaker and said plurality of words in said input speech signal so that said system performs continues speech recognition for said plurality of words, determining whether to perform speech recognition in one of a speaker-independent mode or a speaker-dependent mode; and selecting said speech processing model to be a speaker-dependent model or a speaker-independent model based on said determining step. 15. A method as recited in claim 5, including the further step of processing said speech signal in accordance with a speaker dependent model subsequent to completion of said identifying step. | 0.667041 |
1. A system for delivering a page including a plurality of widgets comprising: a processor configured to: receive a query; determine one or more subject type concepts associated with the query by computing an expected cooccurrence between the query and each selected one of the one or more subject type concepts and determining if the expected cooccurrence exceeds, by a threshold amount, an observed cooccurrence between the query and the selected one of the one or more subject type concepts, wherein a subject type concept is a concept included in a concept hierarchy; find candidate widgets that correspond to the one or more associated subject type concepts, wherein at least one candidate widget comprises an atomic unit of content; select a template that is mapped to the one or more associated subject type concepts; select a plurality of widgets based at least in part on the template; rank the plurality of widgets by determining a module to concept affinity score for each of the plurality of widgets; and generate a page to be delivered in response to the received query, wherein generating the page comprises placing the selected plurality of widgets in the generated page according to the template and the module to concept affinity score for each of the plurality of widgets; and a memory coupled to the processor and configured to provide the processor with instructions. | 1. A system for delivering a page including a plurality of widgets comprising: a processor configured to: receive a query; determine one or more subject type concepts associated with the query by computing an expected cooccurrence between the query and each selected one of the one or more subject type concepts and determining if the expected cooccurrence exceeds, by a threshold amount, an observed cooccurrence between the query and the selected one of the one or more subject type concepts, wherein a subject type concept is a concept included in a concept hierarchy; find candidate widgets that correspond to the one or more associated subject type concepts, wherein at least one candidate widget comprises an atomic unit of content; select a template that is mapped to the one or more associated subject type concepts; select a plurality of widgets based at least in part on the template; rank the plurality of widgets by determining a module to concept affinity score for each of the plurality of widgets; and generate a page to be delivered in response to the received query, wherein generating the page comprises placing the selected plurality of widgets in the generated page according to the template and the module to concept affinity score for each of the plurality of widgets; and a memory coupled to the processor and configured to provide the processor with instructions. 14. The system of claim 1 wherein the processor is further configured to determine an expected monetization of the page. | 0.688144 |
1. A method for mentally investing a reader in a story comprising: providing the reader with a hybrid book comprising the story, the hybrid book including: pages of text embodying a text portion of the story, a computer readable medium with stored spoken presentation data corresponding to an audible portion of the story, the audible portion being wholly distinct from the text portion of the story, and an audio device configured to make audible the spoken presentation data; providing the reader with a summary document which summarizes aspects of the story, the summary document including at least a partial list of people, animals, or creatures discussed in the story; and making audible the stored spoken presentation date, with the audio device after the reader has received the summary document and prior to the reader reading the pages of text embodying the text portion of the story, wherein the audible portion represents a beginning portion of the story and corresponds to a given number of pages of text omitted from the text portion of the story. | 1. A method for mentally investing a reader in a story comprising: providing the reader with a hybrid book comprising the story, the hybrid book including: pages of text embodying a text portion of the story, a computer readable medium with stored spoken presentation data corresponding to an audible portion of the story, the audible portion being wholly distinct from the text portion of the story, and an audio device configured to make audible the spoken presentation data; providing the reader with a summary document which summarizes aspects of the story, the summary document including at least a partial list of people, animals, or creatures discussed in the story; and making audible the stored spoken presentation date, with the audio device after the reader has received the summary document and prior to the reader reading the pages of text embodying the text portion of the story, wherein the audible portion represents a beginning portion of the story and corresponds to a given number of pages of text omitted from the text portion of the story. 10. The method of claim 1 , wherein the story, includes a narrator and the summary document identifies the narrator. | 0.66772 |
1. A computer-implemented method comprising: in response to a first user specifying an attribute set including at least one rule attribute, performing a first search in a rule category database to retrieve rule categories corresponding to the attribute set; performing a second search in a rule provision database to retrieve rule provisions corresponding to the attribute set; identifying rules related to the rule categories retrieved from the rule category database and the rule provisions retrieved from the rule provision database, wherein identifying rules relating to the rule categories and the rule provisions comprises executing a pre-data collection sub-process that filters each retrieved rule to remove rules that are not applicable and stores surviving rules; performing a third search using the identified rules to retrieve, for each identified rule, fares corresponding to the identified rule from a fares database, wherein the third search is performed as N search processes that are executed in parallel; building a list of eligible fares that are not invalidated by the attribute set using the fares retrieved from the fares database, wherein the list of eligible fares is a merged list obtained from a list output from each of the N search processes; creating a functional index including one or more entries, each entry associating one of the rule categories to one or more of the eligible fares based on the corresponding attribute defined by the entry; associating the functional index with the attribute set; and in response to a second user specifying the attribute set, retrieving the fares from the fares database using the functional index. | 1. A computer-implemented method comprising: in response to a first user specifying an attribute set including at least one rule attribute, performing a first search in a rule category database to retrieve rule categories corresponding to the attribute set; performing a second search in a rule provision database to retrieve rule provisions corresponding to the attribute set; identifying rules related to the rule categories retrieved from the rule category database and the rule provisions retrieved from the rule provision database, wherein identifying rules relating to the rule categories and the rule provisions comprises executing a pre-data collection sub-process that filters each retrieved rule to remove rules that are not applicable and stores surviving rules; performing a third search using the identified rules to retrieve, for each identified rule, fares corresponding to the identified rule from a fares database, wherein the third search is performed as N search processes that are executed in parallel; building a list of eligible fares that are not invalidated by the attribute set using the fares retrieved from the fares database, wherein the list of eligible fares is a merged list obtained from a list output from each of the N search processes; creating a functional index including one or more entries, each entry associating one of the rule categories to one or more of the eligible fares based on the corresponding attribute defined by the entry; associating the functional index with the attribute set; and in response to a second user specifying the attribute set, retrieving the fares from the fares database using the functional index. 2. The method of claim 1 , wherein a value of N is determined based on a number of rules identified and on a set of predetermined thresholds, and N is an integer equal to one or greater than one. | 0.674803 |
23. A computer-implemented method, comprising: receiving, at a server computing device having one or more processors, a signal from a first client computing device to initiate a communication session, the signal identifying a digital content item being output at the first client computing device; responsive to receiving the signal, initiating, at the server computing device, the communication session, wherein the communication session enables communication between the first client computing device and one or more other client computing devices; determining, by the server computing device, a context for a topic of discussion associated with the communication session based on the digital content item; based on the context of the communication session, selecting, by the server computing device, a subset of the one or more other client computing devices to invite to participate in the communication session, wherein each one of the one or more other client computing devices is selected when its user has interacted with the digital content item; sending, by the server computing device, an invitation to each other client computing device of the subset of the one or more other client computing devices to join the communication session, wherein the invitation identifies the context; receiving, at the server computing device, a response signal from a particular other client computing device of the subset of the one or more other client computing devices, the response signal indicating that the particular other client computing device desires to join the communication session; responsive to receiving the response signal, sending, by the server computing device and to the first client computing device, a notification that the particular other client computing device desires to join the communication session; responsive to receiving an approval of the particular other client computing device from the first client computing device, connecting, at the server computing device, the particular other client computing device to the communication session. | 23. A computer-implemented method, comprising: receiving, at a server computing device having one or more processors, a signal from a first client computing device to initiate a communication session, the signal identifying a digital content item being output at the first client computing device; responsive to receiving the signal, initiating, at the server computing device, the communication session, wherein the communication session enables communication between the first client computing device and one or more other client computing devices; determining, by the server computing device, a context for a topic of discussion associated with the communication session based on the digital content item; based on the context of the communication session, selecting, by the server computing device, a subset of the one or more other client computing devices to invite to participate in the communication session, wherein each one of the one or more other client computing devices is selected when its user has interacted with the digital content item; sending, by the server computing device, an invitation to each other client computing device of the subset of the one or more other client computing devices to join the communication session, wherein the invitation identifies the context; receiving, at the server computing device, a response signal from a particular other client computing device of the subset of the one or more other client computing devices, the response signal indicating that the particular other client computing device desires to join the communication session; responsive to receiving the response signal, sending, by the server computing device and to the first client computing device, a notification that the particular other client computing device desires to join the communication session; responsive to receiving an approval of the particular other client computing device from the first client computing device, connecting, at the server computing device, the particular other client computing device to the communication session. 24. The computer-implemented method of claim 23 , wherein interaction with the digital content item comprises at least one of: displaying the digital content item; playing the digital content item; providing a comment upon the digital content item; and being tagged in association with the digital content item. | 0.587709 |
15. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with a display and a touch-sensitive surface, cause the device to: concurrently display on the display a first text entry area, and an integrated input area, the integrated input area including: a left portion with a left side of a split keyboard with a first set of characters; a right portion with a right side of the split keyboard with a second set of characters; and a center portion in between the left portion and the right portion; detect a first input on the touch-sensitive surface; in response to detecting the first input, enter a reconfiguration mode for the integrated input area; and, while in the reconfiguration mode for the integrated input area: detect a second input by a first thumb and/or a second thumb; in response to detecting the second input, adjust the size of at least one of the left side and the right side of the split keyboard in the integrated input area, maintain the first set of characters in the left side of the split keyboard, and maintain the second set of characters in the right side of the split keyboard; detect a third input; and, in response to detecting the third input, exit the reconfiguration mode for the integrated input area. | 15. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with a display and a touch-sensitive surface, cause the device to: concurrently display on the display a first text entry area, and an integrated input area, the integrated input area including: a left portion with a left side of a split keyboard with a first set of characters; a right portion with a right side of the split keyboard with a second set of characters; and a center portion in between the left portion and the right portion; detect a first input on the touch-sensitive surface; in response to detecting the first input, enter a reconfiguration mode for the integrated input area; and, while in the reconfiguration mode for the integrated input area: detect a second input by a first thumb and/or a second thumb; in response to detecting the second input, adjust the size of at least one of the left side and the right side of the split keyboard in the integrated input area, maintain the first set of characters in the left side of the split keyboard, and maintain the second set of characters in the right side of the split keyboard; detect a third input; and, in response to detecting the third input, exit the reconfiguration mode for the integrated input area. 21. The computer readable storage medium of claim 15 , wherein the second input includes a horizontal movement of the first thumb away from a vertical side of the display closest to the first thumb; and the one or more programs include instructions that cause the device to: in response to detecting the horizontal movement of the first thumb away from the vertical side of the display closest to the first thumb, increase the size of the left side and the right side of the split keyboard. | 0.530581 |
1. A method executed by a computing device, comprising: parsing a set of one or more web pages of a website; generating a first plurality of n-grams based on at least content that is included on the set of one or more web pages, wherein n is at least two; determining a relevancy value for each of the first plurality of n-grams; generating a second plurality of n-grams based on at least removing any of the first plurality of n-grams whose corresponding relevancy value is below a relevancy value threshold; for each one of the second plurality of n-grams, determining whether that one of the second plurality of n-grams is similar to another one of the second plurality of n-grams, generating a third plurality of n-grams based on at least removing any of those second plurality of n-grams that have been determined as being similar to another one of the second plurality of n-grams; for at least one of the third plurality of n-grams, determining whether there is at least one of the set of web pages of the website that that is directed at content regarding that n-gram; and responsive to determining that there is not at least one of the set of web pages of the website that is directed at content regarding the at least one of the third plurality of n-grams, performing the following: automatically creating a web page with content directed at the at least one of the third plurality of n-grams, wherein automatically creating the web page includes, using a same template of the website for the created web page, inserting content into the created web page with existing content of the website that is related to the at least one of the third plurality of n-grams, and adding a title for the created web page based on the at least one of the third plurality of n-grams; providing the created web page in a graphical editor for a user to review the created web page; and creating a set of one or more links to the reviewed and created web page on one or more of the set of web pages of the website so that the created web page is not an orphan web page. | 1. A method executed by a computing device, comprising: parsing a set of one or more web pages of a website; generating a first plurality of n-grams based on at least content that is included on the set of one or more web pages, wherein n is at least two; determining a relevancy value for each of the first plurality of n-grams; generating a second plurality of n-grams based on at least removing any of the first plurality of n-grams whose corresponding relevancy value is below a relevancy value threshold; for each one of the second plurality of n-grams, determining whether that one of the second plurality of n-grams is similar to another one of the second plurality of n-grams, generating a third plurality of n-grams based on at least removing any of those second plurality of n-grams that have been determined as being similar to another one of the second plurality of n-grams; for at least one of the third plurality of n-grams, determining whether there is at least one of the set of web pages of the website that that is directed at content regarding that n-gram; and responsive to determining that there is not at least one of the set of web pages of the website that is directed at content regarding the at least one of the third plurality of n-grams, performing the following: automatically creating a web page with content directed at the at least one of the third plurality of n-grams, wherein automatically creating the web page includes, using a same template of the website for the created web page, inserting content into the created web page with existing content of the website that is related to the at least one of the third plurality of n-grams, and adding a title for the created web page based on the at least one of the third plurality of n-grams; providing the created web page in a graphical editor for a user to review the created web page; and creating a set of one or more links to the reviewed and created web page on one or more of the set of web pages of the website so that the created web page is not an orphan web page. 2. The method of claim 1 , wherein generating the first plurality of n-grams further is based on content that is included on a set of one or more web pages of one or more competitors of the website. | 0.919433 |
1. An SGML type document managing apparatus for allowing users to create, edit and use an SGML type document collaboratively, comprising: means for automatically creating a partial editing document type definition corresponding to a partial editing request that may cause a partial structure of the document to be changed, the partial editing document type definition being formed by modifying the original document type definition of the entire document so that it represents a restriction against partial editing due to the editing state, which is determined based on the existing document structure and influence of other editing processes executing in parallel at the time when the partial editing request is issued; and means for partially editing the document on the condition that the consistency of the document can be maintained with the partial editing document type definition. | 1. An SGML type document managing apparatus for allowing users to create, edit and use an SGML type document collaboratively, comprising: means for automatically creating a partial editing document type definition corresponding to a partial editing request that may cause a partial structure of the document to be changed, the partial editing document type definition being formed by modifying the original document type definition of the entire document so that it represents a restriction against partial editing due to the editing state, which is determined based on the existing document structure and influence of other editing processes executing in parallel at the time when the partial editing request is issued; and means for partially editing the document on the condition that the consistency of the document can be maintained with the partial editing document type definition. 3. The SGML type document managing apparatus as set forth in claim 1, wherein the restriction due to the editing state is a possibility of which a document element before or after a portion to be edited can be deleted. | 0.678445 |
28. A computer system as recited in claim 26 further comprising a means for shading which shades said variant character styles with a shading in accordance with the desired probability setting. | 28. A computer system as recited in claim 26 further comprising a means for shading which shades said variant character styles with a shading in accordance with the desired probability setting. 29. A computer system as recited in claim 28 wherein said means for shading shades said variant character style with a high level of shading for a highest probability level, with a medium level of shading for a medium probability level, and with a low level of shading for a probability level at a lowest level. | 0.830372 |
15. A computer program product for responding to natural language input, comprising one or more non-transitory computer-readable media having computer program instructions stored therein, the computer program instructions being configured such that, when executed, the computer program instructions cause one or more computing devices to: receive a natural language question comprising a sequence of words; identify a first translation template of a plurality of translation templates using at least a first word of the sequence of words, the first translation template including a sequence of known and unknown strings, a first query and a second query, a first known string of the known and unknown strings corresponding to the first word; identify a first object in a knowledge base using a second word of the sequence of words and the first query of the first translation template; and generate one or more results using the knowledge base, the first object, and the second query of the first translation template. | 15. A computer program product for responding to natural language input, comprising one or more non-transitory computer-readable media having computer program instructions stored therein, the computer program instructions being configured such that, when executed, the computer program instructions cause one or more computing devices to: receive a natural language question comprising a sequence of words; identify a first translation template of a plurality of translation templates using at least a first word of the sequence of words, the first translation template including a sequence of known and unknown strings, a first query and a second query, a first known string of the known and unknown strings corresponding to the first word; identify a first object in a knowledge base using a second word of the sequence of words and the first query of the first translation template; and generate one or more results using the knowledge base, the first object, and the second query of the first translation template. 20. The computer program product of claim 15 , wherein the computer program instructions are further configured such that, when executed, the computer program instructions cause the one or more computing devices to generate an explanation representing how the one or more results were generated, the explanation including a natural language translation of the second query and one or more processing steps of the second query with reference to the knowledge base. | 0.564177 |
4. The method of claim 1 wherein translating the high-level intermediate representation further comprises: translating object type casting, including performing type checking, wherein types include virtual table types, type variables, runtime types, or existential types, or any combination thereof. | 4. The method of claim 1 wherein translating the high-level intermediate representation further comprises: translating object type casting, including performing type checking, wherein types include virtual table types, type variables, runtime types, or existential types, or any combination thereof. 6. The method of claim 4 wherein translating object type casting comprises: testing if an object can be cast to an interface, including opening the object, and searching an interface table of the object for the interface. | 0.91601 |
8. The method of claim 1 , wherein each cluster is a cluster of training questions used to train a QA system pipeline associated with the cluster. | 8. The method of claim 1 , wherein each cluster is a cluster of training questions used to train a QA system pipeline associated with the cluster. 9. The method of claim 8 , wherein each cluster is generated through a clustering process applied to questions selected from a pool of questions comprising both training questions and testing questions to thereby generate the one or more previously generated clusters, and wherein the one or more previously generated clusters comprise training questions selected from the pool of questions. | 0.879681 |
1. A machine implemented method comprising: receiving a first user input comprising a search query; displaying, by a data processing system, in a search interface accessible across a plurality of computer application programs, a plurality of results from a search performed across files and programs accessible by the data processing system, wherein the plurality of results matches the search query and are categorized into a plurality of categories, only a first subset of the plurality of results are displayed for each of the plurality of categories, and the results in the first subset are displayed grouped together in proximity to a displayed representation of a corresponding category; receiving a second user input comprising a selection of one of the displayed representations of the plurality of categories; and in response to the second user input, displaying, in the search interface, a second subset of the plurality of results, wherein the second subset matches the search query and is categorized into a plurality of subcategories of the selected category, and the results categorized into each subcategory is displayed grouped together in proximity to a displayed representation of a corresponding subcategory. | 1. A machine implemented method comprising: receiving a first user input comprising a search query; displaying, by a data processing system, in a search interface accessible across a plurality of computer application programs, a plurality of results from a search performed across files and programs accessible by the data processing system, wherein the plurality of results matches the search query and are categorized into a plurality of categories, only a first subset of the plurality of results are displayed for each of the plurality of categories, and the results in the first subset are displayed grouped together in proximity to a displayed representation of a corresponding category; receiving a second user input comprising a selection of one of the displayed representations of the plurality of categories; and in response to the second user input, displaying, in the search interface, a second subset of the plurality of results, wherein the second subset matches the search query and is categorized into a plurality of subcategories of the selected category, and the results categorized into each subcategory is displayed grouped together in proximity to a displayed representation of a corresponding subcategory. 8. The method of claim 1 , further comprising: receiving a fourth user input, the fourth user input comprising a removal of one of a selected category or subcategory; and in response to the fourth user input, updating the displayed results. | 0.708232 |
18. A device comprising: a memory to store a block of words that are generated as a result of an forward error correction operation, each word, of the block of words, including a plurality of samples, a particular one of the plurality of samples including encoded bits and reliability bits, the reliability bits identifying a level of reliability of the encoded bits; and one or more components to: obtain a word from the block of words within traffic, identify, in a random manner, a first segment of the word, the first segment including a first subset of samples of a plurality of samples associated with the word, select one or more first samples, from the first subset of samples, associated with one or more of first lowest reliability bits within the first subset of samples, identify a second segment associated with the word, the second segment including a second subset of samples of the plurality of samples associated with the word, select one or more second samples, from the second subset of samples, associated with one or more of second lowest reliability bits within the second subset of samples, identify a third segment associated with the word, the third segment including a third subset of samples of the plurality of samples associated with the word, select one or more third samples, from the third subset of samples, associated with one or more of third lowest reliability bits within the third subset of samples, identify lowest reliability bits within the one or more first lowest reliability bits, the one or more second lowest reliability bits, and the one or more third lowest reliability bits, create a merged subset of samples based on selected samples from the one or more first samples, the one or more second samples and the one or more third samples, the selected samples corresponding to the lowest reliability bits, select at least one sample from the merged subset, generate two or more candidate words based on the at least one sample, and process the word using the two or more candidate words. | 18. A device comprising: a memory to store a block of words that are generated as a result of an forward error correction operation, each word, of the block of words, including a plurality of samples, a particular one of the plurality of samples including encoded bits and reliability bits, the reliability bits identifying a level of reliability of the encoded bits; and one or more components to: obtain a word from the block of words within traffic, identify, in a random manner, a first segment of the word, the first segment including a first subset of samples of a plurality of samples associated with the word, select one or more first samples, from the first subset of samples, associated with one or more of first lowest reliability bits within the first subset of samples, identify a second segment associated with the word, the second segment including a second subset of samples of the plurality of samples associated with the word, select one or more second samples, from the second subset of samples, associated with one or more of second lowest reliability bits within the second subset of samples, identify a third segment associated with the word, the third segment including a third subset of samples of the plurality of samples associated with the word, select one or more third samples, from the third subset of samples, associated with one or more of third lowest reliability bits within the third subset of samples, identify lowest reliability bits within the one or more first lowest reliability bits, the one or more second lowest reliability bits, and the one or more third lowest reliability bits, create a merged subset of samples based on selected samples from the one or more first samples, the one or more second samples and the one or more third samples, the selected samples corresponding to the lowest reliability bits, select at least one sample from the merged subset, generate two or more candidate words based on the at least one sample, and process the word using the two or more candidate words. 26. The device of claim 18 , where, when selecting the at least one sample, the one or more components are to: determine that a first sample within the merged subset and a second sample, within the merged subset, are associated with a lowest level of reliability, randomly select, as the at least one sample, the first sample or the second sample when the first sample and the second sample are associated with the lowest level of reliability, the random selection permitting an equal probability that the at least one sample is associated with the first subset, the second subset, or the third subset. | 0.555442 |
3. The device according to claim 1 , wherein the first part of the input device comprises one or several feed rollers. | 3. The device according to claim 1 , wherein the first part of the input device comprises one or several feed rollers. 4. The device according to claim 3 , wherein the feed rollers are driven when said first part is in said first position and are not driven when said first part is in said second position. | 0.893303 |
11. The system according to claim 9 , wherein the first score signal is further based on the number of times the search has been performed. | 11. The system according to claim 9 , wherein the first score signal is further based on the number of times the search has been performed. 12. The system according to claim 11 , wherein the ranking signal further comprises a second score signal based on at least one popularity metric for at least one web page search result of the search. | 0.955071 |
11. A processor-implemented method for managing risk associated with earnings estimates for a company, the method comprising: receiving digital data descriptive of multiple earnings estimates into a computer storage; receiving digital data descriptive of one or more indications of a bank conducting business with the company into a computer storage; generating via a processor a first consensus estimate based upon the digital data descriptive of the multiple earnings estimates received and comprising the data descriptive of an earnings estimate generated by the bank conducting business with the company; generating a second consensus estimate based upon the digital data descriptive of the multiple earnings estimates received and excluding the data descriptive of earnings estimates generated by the bank conducting business with the company; transmitting, to the bank, data comprising a message that the bank's earnings estimate is excluded from the first consensus estimate; and generating an indication in human readable form of a suggested action based upon the first consensus estimate and the second consensus estimate. | 11. A processor-implemented method for managing risk associated with earnings estimates for a company, the method comprising: receiving digital data descriptive of multiple earnings estimates into a computer storage; receiving digital data descriptive of one or more indications of a bank conducting business with the company into a computer storage; generating via a processor a first consensus estimate based upon the digital data descriptive of the multiple earnings estimates received and comprising the data descriptive of an earnings estimate generated by the bank conducting business with the company; generating a second consensus estimate based upon the digital data descriptive of the multiple earnings estimates received and excluding the data descriptive of earnings estimates generated by the bank conducting business with the company; transmitting, to the bank, data comprising a message that the bank's earnings estimate is excluded from the first consensus estimate; and generating an indication in human readable form of a suggested action based upon the first consensus estimate and the second consensus estimate. 15. The processor-implemented method of claim 11 wherein the suggested action comprises acquiring a derivative which will be profitable if a price of a stock for the company declines within a predetermined period. | 0.566453 |
14. The method of claim 13 , wherein the first graphical characteristic is a font transparency and the second graphical dimension is a font size, for a display of each n-gram of the second selected list of n-grams. | 14. The method of claim 13 , wherein the first graphical characteristic is a font transparency and the second graphical dimension is a font size, for a display of each n-gram of the second selected list of n-grams. 15. The method of claim 14 , wherein the second selected list of n-grams is displayed as a word cloud. | 0.979521 |
1. A system for analyzing of a plurality of texts, the system comprising: A) a plurality of keywords stored in a non-transitory computer readable structure, each keyword of said plurality of keywords stored as a respective site of a plurality of sites, said structure including a plurality of branches, each branch having plurality of sub branches, a unique ordered combination of a branch and one or more sub branches leading to each said respective site; each branch of said plurality of branches and each sub branch of said plurality of sub branches being associated with one respective character string, each said keyword being the ordered combination of respective character strings associated with the unique ordered combination of branch and sub branches leading to said respective site and each branch of said plurality of branches being included in more than one said unique combination of a branch and one or more sub branches leading to more than one respective site; B) a plurality of databases including a respective database corresponding to each text of the plurality of texts; each said respective database including a plurality of counters including a respective incidence corresponding to each of said plurality of keywords; C) a computer configured for said analyzing text of said plurality of texts including a) reading a current character string from said one text starting at a start character and selecting from said plurality of branches a current branch associated with said character string, b) recursively navigating said structure according to said one text subsequent to said first character string; said recursively navigating including, i) further reading from said one text a sequential character string sequential to said current character string, ii) selecting from a plurality of sub branches of said current branch, a next branch associated with said sequential character string and iii) replacing said current character string with said sequential character string and replacing said current branch with said next branch and repeating said further reading and said selecting and said replacing until a current branch leads to an encountered site of said plurality of sites, c) incrementing in said respective database of said one text said respective incidence counter of a keyword when said keyword is found in said text starting at said start character by incrementing in said respective database of said one text said respective incidence counter of a keyword stored as said encountered site, e) designating a new start character in the one text and repeating said reading, said navigating, said incrementing and f) repeating said designating until for each of said plurality of keywords, said respective incidence counter indicates the number of times that said keyword appears in the one text; D) a plurality of score buffers including at least one respective score buffer for each said text; each said score buffer storing a computer modifiable value; and wherein said computer is further configured for updating said value stored in a respective score buffer for said one text dependent on a limitation on a value of said respective incidence counter of at least two of said plurality of keywords E) a rule counter and wherein said computer is further configured to set a value said rule counter dependent on at least two of said incidence counters, and wherein said updating is dependent on a value of said of rule counter. | 1. A system for analyzing of a plurality of texts, the system comprising: A) a plurality of keywords stored in a non-transitory computer readable structure, each keyword of said plurality of keywords stored as a respective site of a plurality of sites, said structure including a plurality of branches, each branch having plurality of sub branches, a unique ordered combination of a branch and one or more sub branches leading to each said respective site; each branch of said plurality of branches and each sub branch of said plurality of sub branches being associated with one respective character string, each said keyword being the ordered combination of respective character strings associated with the unique ordered combination of branch and sub branches leading to said respective site and each branch of said plurality of branches being included in more than one said unique combination of a branch and one or more sub branches leading to more than one respective site; B) a plurality of databases including a respective database corresponding to each text of the plurality of texts; each said respective database including a plurality of counters including a respective incidence corresponding to each of said plurality of keywords; C) a computer configured for said analyzing text of said plurality of texts including a) reading a current character string from said one text starting at a start character and selecting from said plurality of branches a current branch associated with said character string, b) recursively navigating said structure according to said one text subsequent to said first character string; said recursively navigating including, i) further reading from said one text a sequential character string sequential to said current character string, ii) selecting from a plurality of sub branches of said current branch, a next branch associated with said sequential character string and iii) replacing said current character string with said sequential character string and replacing said current branch with said next branch and repeating said further reading and said selecting and said replacing until a current branch leads to an encountered site of said plurality of sites, c) incrementing in said respective database of said one text said respective incidence counter of a keyword when said keyword is found in said text starting at said start character by incrementing in said respective database of said one text said respective incidence counter of a keyword stored as said encountered site, e) designating a new start character in the one text and repeating said reading, said navigating, said incrementing and f) repeating said designating until for each of said plurality of keywords, said respective incidence counter indicates the number of times that said keyword appears in the one text; D) a plurality of score buffers including at least one respective score buffer for each said text; each said score buffer storing a computer modifiable value; and wherein said computer is further configured for updating said value stored in a respective score buffer for said one text dependent on a limitation on a value of said respective incidence counter of at least two of said plurality of keywords E) a rule counter and wherein said computer is further configured to set a value said rule counter dependent on at least two of said incidence counters, and wherein said updating is dependent on a value of said of rule counter. 6. The system of claim 1 , further including a lookup table configured for looking up at least two letters of the text simultaneously during said navigating. | 0.511411 |
11. At a computer system, a method for automatically resolving semantic errors in a software routine using one or more known inputs and corresponding expected outputs for portions of the software routine that are known to have errors, the method comprising: an act of providing the software routine with one or more known inputs and corresponding one or more expected outputs for portions of a program fragment where an error has been localized; an act of learning a correctly functioning program fragment from pairs of input-output descriptions of the program fragment; an act of determining the program statements that can transform one or more given input states into one or more given output states after execution of those program statements; and an act of altering portions of the software routine with the learned program fragments. | 11. At a computer system, a method for automatically resolving semantic errors in a software routine using one or more known inputs and corresponding expected outputs for portions of the software routine that are known to have errors, the method comprising: an act of providing the software routine with one or more known inputs and corresponding one or more expected outputs for portions of a program fragment where an error has been localized; an act of learning a correctly functioning program fragment from pairs of input-output descriptions of the program fragment; an act of determining the program statements that can transform one or more given input states into one or more given output states after execution of those program statements; and an act of altering portions of the software routine with the learned program fragments. 16. The method of claim 11 , wherein the known inputs and expected outputs comprise source code modules and/or source code functions. | 0.576613 |
2. The method of claim 1 , further comprising building, by the computer, the language model. | 2. The method of claim 1 , further comprising building, by the computer, the language model. 3. The method of claim 2 , wherein the language model is built based upon geo-tagged text. | 0.958187 |
9. The method of claim 7 further comprises creating one or more lemmas from the set of constraints that represent the violation and conjoining the lemmas with the abstraction model for subsequent iterations. | 9. The method of claim 7 further comprises creating one or more lemmas from the set of constraints that represent the violation and conjoining the lemmas with the abstraction model for subsequent iterations. 11. The method of claim 9 further comprises extracting one or more subset of constraints from the set of constraints that represent the violation and creating the lemmas by negating the subsets of constraints. | 0.916774 |
5. The method according to claim 1 , wherein said selecting further comprises: selecting said dominant keyword based on a highest-ranked output value calculated for said each retrieved keyword; and retrieving said at least one category associated with said dominant keyword from said keyword database. | 5. The method according to claim 1 , wherein said selecting further comprises: selecting said dominant keyword based on a highest-ranked output value calculated for said each retrieved keyword; and retrieving said at least one category associated with said dominant keyword from said keyword database. 6. The method according to claim 5 , wherein said selecting further comprises: retrieving said set of statistical parameters corresponding to said each retrieved keyword; assembling a vector containing said set of statistical parameters for said each retrieved keyword; and calculating said output value for said each retrieved keyword based on said vector, said output value indicating a probability that a corresponding retrieved keyword is selected as said dominant keyword. | 0.8965 |
21. A method for servicing photon map queries, comprising: accepting photon queries from one or more code modules or shaders, each of the photon queries defining a spatially located volume and criteria for photons that are responsive to that photon query, at least some of the photon queries defining a locus and a number of photons (k) closest to the locus as the criteria, wherein k>=1; associating each of the accepted queries with a collection of photon queries that is associated with a node of an acceleration structure, the acceleration structure including nodes that respectively define surfaces that each spatially bound a respective selection of photons located in a 3-D scene, the selections of varying relative granularity, and the nodes arranged in a graph with edges connecting pairs of nodes; traversing the acceleration structure with collections of photon queries from the accepted photon queries, wherein the traversal is performed, collection-by-collection, by testing, in an acceleration structure resource comprising one or more processors, each of a plurality of child nodes of the node associated with a selected collection of photon queries for overlap with each of the spatially located volumes of the photon queries of that collection, and updating a status of collections maintained in a memory by referencing each photon query in a respective collection associated with each child node found to overlap with the spatially located volume of that photon query; and returning, for each of the photon queries, identifiers for photons satisfying the criteria specified for that photon query. | 21. A method for servicing photon map queries, comprising: accepting photon queries from one or more code modules or shaders, each of the photon queries defining a spatially located volume and criteria for photons that are responsive to that photon query, at least some of the photon queries defining a locus and a number of photons (k) closest to the locus as the criteria, wherein k>=1; associating each of the accepted queries with a collection of photon queries that is associated with a node of an acceleration structure, the acceleration structure including nodes that respectively define surfaces that each spatially bound a respective selection of photons located in a 3-D scene, the selections of varying relative granularity, and the nodes arranged in a graph with edges connecting pairs of nodes; traversing the acceleration structure with collections of photon queries from the accepted photon queries, wherein the traversal is performed, collection-by-collection, by testing, in an acceleration structure resource comprising one or more processors, each of a plurality of child nodes of the node associated with a selected collection of photon queries for overlap with each of the spatially located volumes of the photon queries of that collection, and updating a status of collections maintained in a memory by referencing each photon query in a respective collection associated with each child node found to overlap with the spatially located volume of that photon query; and returning, for each of the photon queries, identifiers for photons satisfying the criteria specified for that photon query. 23. The method of claim 21 for servicing photon map queries, further comprising accessing status information for collections of photon queries, the status information comprising an indication of a number of photon queries present in each collection, and selecting one or more of the collections to begin or to continue traversal. | 0.620824 |
1. A method comprising: receiving an answer from a user associated with an automated dialog with a spoken dialog system, wherein the answer indicates services to be associated with the user; determining, via a processor, a characteristic associated with an analysis of the answer, the characteristic comprising a mood associated with the user; and when the mood meets a termination criteria: terminating a line of questioning; continuing the automated dialog with the user by providing a spoken prompt from the spoken dialog system; and deferring obtaining of individual profile information associated with the user to a subsequent automated dialog. | 1. A method comprising: receiving an answer from a user associated with an automated dialog with a spoken dialog system, wherein the answer indicates services to be associated with the user; determining, via a processor, a characteristic associated with an analysis of the answer, the characteristic comprising a mood associated with the user; and when the mood meets a termination criteria: terminating a line of questioning; continuing the automated dialog with the user by providing a spoken prompt from the spoken dialog system; and deferring obtaining of individual profile information associated with the user to a subsequent automated dialog. 2. The method of claim 1 , wherein the analysis uses a user profile of the user. | 0.694549 |
9. An article of manufacture including a non-transitory computer-readable medium, having stored thereon program instructions that, if executed by a computing device, cause the computing device to perform operations comprising: receive an identification request from a displaying device, wherein the identification request specifies an address of the displaying device; in response to receiving the identification request, transmit a session identifier to the displaying device; receive a session initiation request from a scanning device, wherein the session initiation request contains the session identifier and a scanning device identifier, wherein the scanning device identifier is unique to the scanning device, and wherein the scanning device and the displaying device each communicate independently with the computing system; in response to receiving the session initiation request, create an association between the session identifier, the scanning device identifier, and the address of the displaying device; receive a digital media request from the scanning device, wherein the digital media request contains information scanned by the scanning device that identifies requested digital media; and based on the information scanned by the scanning device and the association between the session identifier, the scanning device identifier, and the address of the displaying device, transmit the requested digital media to the displaying device. | 9. An article of manufacture including a non-transitory computer-readable medium, having stored thereon program instructions that, if executed by a computing device, cause the computing device to perform operations comprising: receive an identification request from a displaying device, wherein the identification request specifies an address of the displaying device; in response to receiving the identification request, transmit a session identifier to the displaying device; receive a session initiation request from a scanning device, wherein the session initiation request contains the session identifier and a scanning device identifier, wherein the scanning device identifier is unique to the scanning device, and wherein the scanning device and the displaying device each communicate independently with the computing system; in response to receiving the session initiation request, create an association between the session identifier, the scanning device identifier, and the address of the displaying device; receive a digital media request from the scanning device, wherein the digital media request contains information scanned by the scanning device that identifies requested digital media; and based on the information scanned by the scanning device and the association between the session identifier, the scanning device identifier, and the address of the displaying device, transmit the requested digital media to the displaying device. 11. The article of manufacture of claim 9 , wherein the program instructions, if executed by the computing device, cause the computing device to perform operations further comprising: before transmitting the digital media to the displaying device, and based on the association between the session identifier, the scanning device identifier, and the address of the displaying device, determine that the displaying device is suitable for displaying the digital media. | 0.51318 |
23. A system for use of a medical ontology for computer assisted clinical decision support, the system comprising: a memory operable to store a probabilistic model having machine learned probabilities for relationships from a medical ontology, the probabilities machine learned from medical records representing patients; and a processor operable to apply the probabilistic model for computer assisted clinical decision support. | 23. A system for use of a medical ontology for computer assisted clinical decision support, the system comprising: a memory operable to store a probabilistic model having machine learned probabilities for relationships from a medical ontology, the probabilities machine learned from medical records representing patients; and a processor operable to apply the probabilistic model for computer assisted clinical decision support. 26. The system of claim 23 wherein the processor is operable to mine unstructured data of a medical record as a function of a knowledge base derived from the medical ontology, and wherein the processor is operable to apply the probabilistic model to results of the mining. | 0.573638 |
9. The system of claim 8 , wherein said one or more programmed processor devices performs extracting said one or more first, second, third and fourth features in parallel. | 9. The system of claim 8 , wherein said one or more programmed processor devices performs extracting said one or more first, second, third and fourth features in parallel. 11. The system of claim 9 , wherein said identifying grammatical relations amongst words comprises: traversing said parse tree. | 0.957362 |
1. A digital data processing method for enterprise application integration comprising: A. electronically downloading to one or more digital data processors functionality that effects information transfers between a first database and a second database and between the first database and a third database, B. executing the functionality on the one or more digital data processors to effect transferring information between the first database and the second database, the transferring step including at least: (i) receiving information from the second database using an application program interface (“API”) associated therewith, (ii) transforming at least some of the information received from the second database into resource definition format (“RDF”) triplets, and (iii) transmitting those RDF triplets to the first database; C. executing the functionality on the one or more digital data processors to effect transferring information between the first database and the third database, the transferring step including at least: (i) receiving the information from the third database using an application program interface (“API”) different than the API associated with the second database, (ii) transforming at least some of the information received from the third database into resource definition format (“RDF”) triplets, and (iii) transmitting those RDF triplets to the first database; D. wherein the first database stores the RDF triplets from the second and third databases for query, for coalescence, or for use in generating directed graphs that can be analyzed to discern answers to queries for information reflected by the RDF triplets and originating from any of the second and third databases. | 1. A digital data processing method for enterprise application integration comprising: A. electronically downloading to one or more digital data processors functionality that effects information transfers between a first database and a second database and between the first database and a third database, B. executing the functionality on the one or more digital data processors to effect transferring information between the first database and the second database, the transferring step including at least: (i) receiving information from the second database using an application program interface (“API”) associated therewith, (ii) transforming at least some of the information received from the second database into resource definition format (“RDF”) triplets, and (iii) transmitting those RDF triplets to the first database; C. executing the functionality on the one or more digital data processors to effect transferring information between the first database and the third database, the transferring step including at least: (i) receiving the information from the third database using an application program interface (“API”) different than the API associated with the second database, (ii) transforming at least some of the information received from the third database into resource definition format (“RDF”) triplets, and (iii) transmitting those RDF triplets to the first database; D. wherein the first database stores the RDF triplets from the second and third databases for query, for coalescence, or for use in generating directed graphs that can be analyzed to discern answers to queries for information reflected by the RDF triplets and originating from any of the second and third databases. 7. A method according to claim 1 , wherein the RDF triplets have objects that comprise any of a literal or an identifier. | 0.655287 |
13. A non-transitory computer-readable storage medium storing processor-executable instructions for controlling a computing device, comprising: program code to receive an audio signal; program code to perform speech recognition processing on the audio signal using a neural network to obtain speech recognition results; and program code to update the neural network during runtime based at least in part on the speech recognition results. | 13. A non-transitory computer-readable storage medium storing processor-executable instructions for controlling a computing device, comprising: program code to receive an audio signal; program code to perform speech recognition processing on the audio signal using a neural network to obtain speech recognition results; and program code to update the neural network during runtime based at least in part on the speech recognition results. 18. The non-transitory computer-readable storage medium of claim 13 , further comprising: program code to compute a feature vector from the audio signal; program code to determine a hidden Markov model state associated with the feature vector from the first result; and wherein the program code to update the neural network comprises program code to use the feature vector as an input to the neural network and the hidden Markov model state as an output to the neural network. | 0.799748 |
14. A computer program product for domain specific normalization of a corpus of text, the computer program product comprising: a non-transitory computer readable storage medium comprising a device having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code for loading a corpus of text in memory of a computer; computer readable program code for determining a domain for the corpus of text by recognizing a presence of words or phrases in the loaded corpus of text that had been previously correlated to the domain; computer readable program code for retrieving a lexicon of replacement words for the determined domain, the lexicon comprising a set of source terms, at least one of the source terms being mapped to one of multiple different replacement terms having a complexity value aligned with an average complexity value for the multiple different replacement terms; and, computer readable program code for text simplifying the corpus of text using the retrieved lexicon by replacing existing words in the corpus of text with the replacement words. | 14. A computer program product for domain specific normalization of a corpus of text, the computer program product comprising: a non-transitory computer readable storage medium comprising a device having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code for loading a corpus of text in memory of a computer; computer readable program code for determining a domain for the corpus of text by recognizing a presence of words or phrases in the loaded corpus of text that had been previously correlated to the domain; computer readable program code for retrieving a lexicon of replacement words for the determined domain, the lexicon comprising a set of source terms, at least one of the source terms being mapped to one of multiple different replacement terms having a complexity value aligned with an average complexity value for the multiple different replacement terms; and, computer readable program code for text simplifying the corpus of text using the retrieved lexicon by replacing existing words in the corpus of text with the replacement words. 16. The computer program product of claim 14 , wherein the domain is an organizational domain. | 0.656587 |
1. A computer-implemented method for asynchronous receipt and processing of electronic ink annotation of a document, comprising: generating a first analysis context object, the first analysis context object providing a translation layer for a document model of a current state of a relationship of elements in the document and comprising a tree data structure for storing document elements in a hierarchical relationship; staffing a first thread, wherein the first thread updates the first analysis context object based upon a user interaction with the document, the user interaction including electronic ink annotation; upon an event requiring analysis of new data in the document: suspending execution of the first thread so as to prevent changes to the first analysis context object; starting a second thread, wherein the second thread generates a second analysis context object corresponding to a portion of the first analysis context object, wherein the portion corresponds to a designated region of the document; upon completion of generation of the second analysis context object: suspending execution of the second thread; restarting the first thread; performing a first analysis of the second analysis context object to generate a third analysis context object from the second analysis context object, wherein the third analysis context object is generated by parsing the new data and modifying the second analysis context object based on the new data and further includes classification information for the new data; upon completion of the first analysis: suspending execution of the first thread so as to prevent any changes to the first analysis context object; starting a third thread, wherein the third thread reconciles the third analysis context object with the first analysis context object to generate first reconciled analysis results; upon completion of the reconciliation of the first analysis context object and the third analysis context object: updating the first analysis context object with the first reconciled analysis results; suspending execution of the third threat; and restarting the first thread. | 1. A computer-implemented method for asynchronous receipt and processing of electronic ink annotation of a document, comprising: generating a first analysis context object, the first analysis context object providing a translation layer for a document model of a current state of a relationship of elements in the document and comprising a tree data structure for storing document elements in a hierarchical relationship; staffing a first thread, wherein the first thread updates the first analysis context object based upon a user interaction with the document, the user interaction including electronic ink annotation; upon an event requiring analysis of new data in the document: suspending execution of the first thread so as to prevent changes to the first analysis context object; starting a second thread, wherein the second thread generates a second analysis context object corresponding to a portion of the first analysis context object, wherein the portion corresponds to a designated region of the document; upon completion of generation of the second analysis context object: suspending execution of the second thread; restarting the first thread; performing a first analysis of the second analysis context object to generate a third analysis context object from the second analysis context object, wherein the third analysis context object is generated by parsing the new data and modifying the second analysis context object based on the new data and further includes classification information for the new data; upon completion of the first analysis: suspending execution of the first thread so as to prevent any changes to the first analysis context object; starting a third thread, wherein the third thread reconciles the third analysis context object with the first analysis context object to generate first reconciled analysis results; upon completion of the reconciliation of the first analysis context object and the third analysis context object: updating the first analysis context object with the first reconciled analysis results; suspending execution of the third threat; and restarting the first thread. 16. The method according to claim 1 , further comprising: after suspending execution of the first thread starting a caching thread for receiving changes to the document based upon future user interaction; after suspending execution of the second thread, suspending execution of the caching thread; upon completion of the first analysis and after suspending execution of the first thread, restarting the caching thread; and after suspending execution of the third thread, suspending the execution of the caching thread. | 0.5 |
7. The method of claim 6 wherein the formula representing the set of characters is represented by a binary decision diagram, and wherein performing the random walk comprises traversing the binary decision diagram. | 7. The method of claim 6 wherein the formula representing the set of characters is represented by a binary decision diagram, and wherein performing the random walk comprises traversing the binary decision diagram. 8. The method of claim 7 further comprising, configuring the binary decision diagram with order zero corresponding to a most significant bit. | 0.820814 |
4. The method of claim 1 further comprising positioning at least one sound recording device in a substantially fixed location relative to a person. | 4. The method of claim 1 further comprising positioning at least one sound recording device in a substantially fixed location relative to a person. 5. The method of claim 4 wherein the act of positioning at least one sound recording device comprises placing the sound recording device within an article of clothing of the person. | 0.902045 |
1. A method comprising: accessing profile edit task information associated with a member of an online social network service, the profile edit task information identifying one or more candidate profile edit tasks to be performed to update a member profile page of the member; determining the member completed a profile edit task of the one or more candidate profile edit tasks, the profile edit task classified as a difficult task based on a response metric associated with other members of the online social network service completing the profile edit task, the difficult task classification indicating, at least in part, a heavyweight task; based on determining the member completed the profile edit task classified as the difficult task, inferring a mode of the member conducive to completing profile edit tasks classified as difficult tasks; responsive to inferring the mode of the member conducive to completing profile edit tasks classified as difficult tasks, identifying an additional profile edit task classified as a difficult task from the one or more candidate profile edit tasks; and prompting the member to perform the additional profile edit task. | 1. A method comprising: accessing profile edit task information associated with a member of an online social network service, the profile edit task information identifying one or more candidate profile edit tasks to be performed to update a member profile page of the member; determining the member completed a profile edit task of the one or more candidate profile edit tasks, the profile edit task classified as a difficult task based on a response metric associated with other members of the online social network service completing the profile edit task, the difficult task classification indicating, at least in part, a heavyweight task; based on determining the member completed the profile edit task classified as the difficult task, inferring a mode of the member conducive to completing profile edit tasks classified as difficult tasks; responsive to inferring the mode of the member conducive to completing profile edit tasks classified as difficult tasks, identifying an additional profile edit task classified as a difficult task from the one or more candidate profile edit tasks; and prompting the member to perform the additional profile edit task. 7. The method of claim 1 , wherein the prompting further comprises: transmitting a message to the member that invites the member to update their member profile page by performing the additional profile edit task. | 0.617182 |
5. A method of recording text subtitle data on a recording medium using a recording apparatus, the method comprising: recording at least one main AV data and a plurality of subtitle information segments on the recording medium using the recording apparatus, each one of the subtitle information segments being represented by each PES packet of transport packets and having a one-to-one correspondence with each PES packet, the PES packet including a packet identifier for identifying a type of the packet, wherein each one of the subtitle information segments includes a segment identifier identifying the subtitle information segment as one of text data and graphic data, wherein a first subtitle information segment identified as the text data includes at least one first style information and palette information, the palette information including a palette identifier identifying the corresponding palette information for controlling color attributes of the text data, wherein a second subtitle information segment identified as the text data includes at least two text subtitle regions, each of the text subtitle regions including second style information applied to the text data for managing reproduction of the text data by the reproducing device, each of the text subtitle regions being linked to the first style information defined in the first subtitle information segment by an identifier, each of the text subtitle regions including length information for indicating a length of a number of characters of a text string on the corresponding text subtitle region to be displayed, wherein the graphic data is multiplexed with the main AV data into a file while the text data is separate from the main AV data, wherein either one of the graphic data or the text data is displayed together with the main AV data. | 5. A method of recording text subtitle data on a recording medium using a recording apparatus, the method comprising: recording at least one main AV data and a plurality of subtitle information segments on the recording medium using the recording apparatus, each one of the subtitle information segments being represented by each PES packet of transport packets and having a one-to-one correspondence with each PES packet, the PES packet including a packet identifier for identifying a type of the packet, wherein each one of the subtitle information segments includes a segment identifier identifying the subtitle information segment as one of text data and graphic data, wherein a first subtitle information segment identified as the text data includes at least one first style information and palette information, the palette information including a palette identifier identifying the corresponding palette information for controlling color attributes of the text data, wherein a second subtitle information segment identified as the text data includes at least two text subtitle regions, each of the text subtitle regions including second style information applied to the text data for managing reproduction of the text data by the reproducing device, each of the text subtitle regions being linked to the first style information defined in the first subtitle information segment by an identifier, each of the text subtitle regions including length information for indicating a length of a number of characters of a text string on the corresponding text subtitle region to be displayed, wherein the graphic data is multiplexed with the main AV data into a file while the text data is separate from the main AV data, wherein either one of the graphic data or the text data is displayed together with the main AV data. 7. The method of claim 5 , wherein the text data is character code data. | 0.855159 |
25. The computer program product of claim 19 , the operations further comprising: identifying lesser order n-grams, the lesser order n-grams being derived from the first n-gram; and identifying a respective scaled probability of each of the lesser order n-grams identifying a word, the scaled probability for a particular lesser order n-gram composed of a particular number of atomic units identifying a word being determined by adjusting an initial probability of the lesser order n-gram identifying a word based at least in part on the particular number of atomic units. | 25. The computer program product of claim 19 , the operations further comprising: identifying lesser order n-grams, the lesser order n-grams being derived from the first n-gram; and identifying a respective scaled probability of each of the lesser order n-grams identifying a word, the scaled probability for a particular lesser order n-gram composed of a particular number of atomic units identifying a word being determined by adjusting an initial probability of the lesser order n-gram identifying a word based at least in part on the particular number of atomic units. 26. The computer program product of claim 25 , wherein segmenting the plurality of tokens into one or more words comprises: when a product of the respective scaled probabilities of the lesser order n-grams derived from the first n-gram identifying a word exceeds the scaled probability of the first n-gram identifying a word, segmenting the first n-gram such that each of the lesser order n-grams identifies a respective word. | 0.649939 |
14. A device, comprising: at least one processor and a memory; the at least one processor configured to: perform static type checking at compilation time on program source code based on an extended static interface type, the extended static interface type comprising an initial static type defined by an initial declaration provided in a first source code file merged with at least one extension declaration provided in at least one additional source code file for the initial static type, wherein the at least one extension declaration extends capabilities of a component of the program source code at runtime. | 14. A device, comprising: at least one processor and a memory; the at least one processor configured to: perform static type checking at compilation time on program source code based on an extended static interface type, the extended static interface type comprising an initial static type defined by an initial declaration provided in a first source code file merged with at least one extension declaration provided in at least one additional source code file for the initial static type, wherein the at least one extension declaration extends capabilities of a component of the program source code at runtime. 19. The device of claim 14 , wherein the at least one processor is further configured to: receive program source code written in TypeScript. | 0.698225 |
8. The method according to claim 1 , wherein the at least one monitor data element comprises at least one of a raw data element contained within the functional web service and a summary of raw data elements contained within the functional web service. | 8. The method according to claim 1 , wherein the at least one monitor data element comprises at least one of a raw data element contained within the functional web service and a summary of raw data elements contained within the functional web service. 9. The method according to claim 8 , wherein the summary of raw data elements comprises at least one of an average of a raw data element contained within the functional web service, a minimum value of a raw data element contained within the functional web service, a maximum value of a raw data element contained within the functional web service, a distribution of values of a raw data element contained within the functional web service, a periodically collected raw data element contained within the functional web service and a summary of a pre-defined number of raw values contained within the functional web service. | 0.806786 |
1. A computer-implemented method comprising: maintaining in a data store social information associated with a plurality of users of a social networking system, a plurality of actions performed by the users, and a plurality of social networking system objects associated with one or more of the actions; receiving, from a device associated with a viewing user, a request for a page, the request identifying two or more users of the social networking system, the requested page comprising one or more social networking system objects upon which, for each object, an action was performed by each of the identified social networking system users; and responsive to receiving the request for the page: identifying one or more social networking system objects wherein, for each identified object, an action was performed by each of the identified users with respect to the social networking system object; determining an order for the identified social networking system objects; identifying a set of images, each image from the set of images associated with each of the identified users; selecting an image from the set of images based on a relevancy of the image to all of the identified users, wherein the relevancy of the image decreases when the image is associated with additional users other than the identified users; generating the requested page, the generated page including information associated with the identified social networking system objects, the actions performed on each of the social networking system objects by each of the identified users, the information ordered within the generated page based on the determined order for the identified social networking system objects, and the selected image; and sending the generated page to the device associated with the viewing user for display. | 1. A computer-implemented method comprising: maintaining in a data store social information associated with a plurality of users of a social networking system, a plurality of actions performed by the users, and a plurality of social networking system objects associated with one or more of the actions; receiving, from a device associated with a viewing user, a request for a page, the request identifying two or more users of the social networking system, the requested page comprising one or more social networking system objects upon which, for each object, an action was performed by each of the identified social networking system users; and responsive to receiving the request for the page: identifying one or more social networking system objects wherein, for each identified object, an action was performed by each of the identified users with respect to the social networking system object; determining an order for the identified social networking system objects; identifying a set of images, each image from the set of images associated with each of the identified users; selecting an image from the set of images based on a relevancy of the image to all of the identified users, wherein the relevancy of the image decreases when the image is associated with additional users other than the identified users; generating the requested page, the generated page including information associated with the identified social networking system objects, the actions performed on each of the social networking system objects by each of the identified users, the information ordered within the generated page based on the determined order for the identified social networking system objects, and the selected image; and sending the generated page to the device associated with the viewing user for display. 11. The computer-implemented method of claim 1 , wherein the identified social networking system object comprises an event attended by all the identified users. | 0.537859 |
1. A method of recovering content information from a watermark in a target digital document to be carried out by a computer adapted to perform the steps of: locating the watermark in the target document based on a pre-determined template specification that describes a manner in which the watermark was merged into the target document, the template specification identifying at least one watermark specification and providing a mapping list indicating a manner in which at least one watermark associated with the at least one watermark specification is merged into a document; and obtaining the content information from the located watermark according to a watermark specification identified by the template specification, the watermark specification identifying a specific watermarking technology and a target object into which the watermark was placed. | 1. A method of recovering content information from a watermark in a target digital document to be carried out by a computer adapted to perform the steps of: locating the watermark in the target document based on a pre-determined template specification that describes a manner in which the watermark was merged into the target document, the template specification identifying at least one watermark specification and providing a mapping list indicating a manner in which at least one watermark associated with the at least one watermark specification is merged into a document; and obtaining the content information from the located watermark according to a watermark specification identified by the template specification, the watermark specification identifying a specific watermarking technology and a target object into which the watermark was placed. 7. The method of claim 1 , wherein the target document comprises audio or video content. | 0.865385 |
12. A system comprising: a computer having a computer input device and a display device connected thereto; and a plurality of distributed processors communicatively coupled to the computer, wherein the computer is configured to coordinate the activities of the distributed processors, wherein each of the distributed processors is configured as a separate domain-specific knowledgebase segment and is further configured to perform a method comprising the steps of: determining that a predictor case base containing predictor rules having predictor antecedents and associated predictor consequents does not contain a predictor rule having a predictor antecedent covered by an acquired predictor context; creating one or more least-generalized predictor antecedents that are covered by the acquired predictor context; creating a corrector context using the predictor consequents associated with the one or more least-generalized predictor antecedents; determining that a corrector case base containing corrector rules having corrector antecedents and associated corrector consequents contains a corrector rule having a corrector antecedent covered by the corrector context; and firing the corrector consequent associated with the corrector antecedent covered by the corrector context. | 12. A system comprising: a computer having a computer input device and a display device connected thereto; and a plurality of distributed processors communicatively coupled to the computer, wherein the computer is configured to coordinate the activities of the distributed processors, wherein each of the distributed processors is configured as a separate domain-specific knowledgebase segment and is further configured to perform a method comprising the steps of: determining that a predictor case base containing predictor rules having predictor antecedents and associated predictor consequents does not contain a predictor rule having a predictor antecedent covered by an acquired predictor context; creating one or more least-generalized predictor antecedents that are covered by the acquired predictor context; creating a corrector context using the predictor consequents associated with the one or more least-generalized predictor antecedents; determining that a corrector case base containing corrector rules having corrector antecedents and associated corrector consequents contains a corrector rule having a corrector antecedent covered by the corrector context; and firing the corrector consequent associated with the corrector antecedent covered by the corrector context. 15. The system of claim 12 , wherein each of the plurality of distributed processors are configured to create the corrector context by using the union of predictor consequents associated with the least-generalized predictor antecedents. | 0.6468 |
8. An apparatus comprising: at least one processor and a computer readable storage medium having program code stored thereon for identifying the focus of a document, in a natural language processing application, the natural language processing application comprising a hierarchical concept tree having a plurality of nodes, each node being associated with a term, by executing the following steps: mapping an input document to nodes in a concept tree to determine a number of occurrences of a term in the input document which also occur at each of the nodes in the concept tree, weighting each node in the concept tree, depending on the determined number of occurrences of the term in the input document and a determined value assigned to each node in the concept tree, wherein the determined value assigned to each node in the concept tree comprises a probability that, for a given one of the occurrences of the term in the input document, the node is a correct one of a plurality of nodes within the concept tree that are associated with the term, wherein the probability is based on a total number of the plurality of nodes within the concept tree that are associated with the term, and wherein the weighting of each node in the concept tree comprises multiplying the assigned determined value and the determined number of occurrences of the associated term in the input document, traversing the concept tree to identify a heaviest weighted path, in dependence of the weighting of each node in the concept tree, and determining the focus of the input document by identifying a node having the heaviest weight along the most heavily weighted path. | 8. An apparatus comprising: at least one processor and a computer readable storage medium having program code stored thereon for identifying the focus of a document, in a natural language processing application, the natural language processing application comprising a hierarchical concept tree having a plurality of nodes, each node being associated with a term, by executing the following steps: mapping an input document to nodes in a concept tree to determine a number of occurrences of a term in the input document which also occur at each of the nodes in the concept tree, weighting each node in the concept tree, depending on the determined number of occurrences of the term in the input document and a determined value assigned to each node in the concept tree, wherein the determined value assigned to each node in the concept tree comprises a probability that, for a given one of the occurrences of the term in the input document, the node is a correct one of a plurality of nodes within the concept tree that are associated with the term, wherein the probability is based on a total number of the plurality of nodes within the concept tree that are associated with the term, and wherein the weighting of each node in the concept tree comprises multiplying the assigned determined value and the determined number of occurrences of the associated term in the input document, traversing the concept tree to identify a heaviest weighted path, in dependence of the weighting of each node in the concept tree, and determining the focus of the input document by identifying a node having the heaviest weight along the most heavily weighted path. 14. The apparatus as claimed in claim 8 , the steps further comprising when traversal of the concept tree identifies the focus as a node which only has a weight of the sum of its child node, continuing to traverse the remainder of the node's path to find an alternative focus. | 0.70406 |
18. A system for reducing speech intelligibility while preserving environmental sounds, the system comprising: a receiving module for receiving an audio signal; a voicing detector for processing the audio signal to separate a vocalic region that comprises vowels; a computation module for computing a representation of at least the vocalic regions, the representation including at least a vocal tract transfer function and an excitation; a replacement module for replacing the vocal tract transfer function of the vocalic region with a replacement vocal tract transfer function of a replacement sound to create a modified vocal tract transfer function; and an audio synthesizer for synthesizing a modified audio signal of at least the vocalic region from the modified vocal tract transfer function and the excitation. | 18. A system for reducing speech intelligibility while preserving environmental sounds, the system comprising: a receiving module for receiving an audio signal; a voicing detector for processing the audio signal to separate a vocalic region that comprises vowels; a computation module for computing a representation of at least the vocalic regions, the representation including at least a vocal tract transfer function and an excitation; a replacement module for replacing the vocal tract transfer function of the vocalic region with a replacement vocal tract transfer function of a replacement sound to create a modified vocal tract transfer function; and an audio synthesizer for synthesizing a modified audio signal of at least the vocalic region from the modified vocal tract transfer function and the excitation. 24. The system of claim 18 , further comprising a vocalic syllable detector to identify the syllables within the vocalic region before computing the vocal tract transfer function. | 0.513001 |
16. A system of generating Frequently Asked Questions (FAQ) data from Community-based Question Answering (CQA) data, the system comprising: a non-transitory computer-readable storage medium storing executable computer program modules comprising a thematic hierarchy generation module configured to: receive a plurality of data sources, a data source having data associated with one or more topics, and a topic having one or more themes, and generate a thematic hierarchy of the plurality of data sources; a feature classifier configured to classify a plurality of CQA data into one or more themes based on the thematic hierarchy, where the CQA data containing a plurality of question-answer pairs; and a selection configured to: select a plurality of question-answer pairs from the CQA data based on the classification, the selecting comprising: for each theme of the CQA data, grouping a plurality of CQA data into a plurality of clusters, wherein the CQA data in a cluster share one or more features associated with the theme, and a cluster of CQA data has a centroid representing the theme of the cluster, and generate FAQ data using the selected question-answer pairs of the CQA data. | 16. A system of generating Frequently Asked Questions (FAQ) data from Community-based Question Answering (CQA) data, the system comprising: a non-transitory computer-readable storage medium storing executable computer program modules comprising a thematic hierarchy generation module configured to: receive a plurality of data sources, a data source having data associated with one or more topics, and a topic having one or more themes, and generate a thematic hierarchy of the plurality of data sources; a feature classifier configured to classify a plurality of CQA data into one or more themes based on the thematic hierarchy, where the CQA data containing a plurality of question-answer pairs; and a selection configured to: select a plurality of question-answer pairs from the CQA data based on the classification, the selecting comprising: for each theme of the CQA data, grouping a plurality of CQA data into a plurality of clusters, wherein the CQA data in a cluster share one or more features associated with the theme, and a cluster of CQA data has a centroid representing the theme of the cluster, and generate FAQ data using the selected question-answer pairs of the CQA data. 17. The system of claim 16 , wherein the selection module is further configured to, for each cluster of CQA data: select a plurality of representative data from the cluster; measure quality of the representative data; and generate a representative score for each question-answer pairs of the representative data. | 0.5 |
12. The method of claim 11 , wherein said recognizing of the type of the target topic comprises: selecting the type of the target topic as one of preset topic types; selecting a core property of the target topic depending on the selected topic type; and searching the topic templates to find related topics to the target topic based on the selected core property and the target topic. | 12. The method of claim 11 , wherein said recognizing of the type of the target topic comprises: selecting the type of the target topic as one of preset topic types; selecting a core property of the target topic depending on the selected topic type; and searching the topic templates to find related topics to the target topic based on the selected core property and the target topic. 13. The method of claim 12 , wherein said searching of the topic templates comprises: searching all topic templates having the same names as the target topic; eliminating topic templates whose core properties do not have property values; ranking the property values to select upper N-number of property values; eliminating topic templates except the topic templates having the upper N-number of property values; and grouping the topic templates based on the upper N-number of property values. | 0.829343 |
1. A method of modifying search results of a search engine comprising: (a) identifying a first target page, wherein said first target page has a first ranking used by the search engine in responding to queries directed to a target term; (b) identifying one or more spam pages; (c) automatically causing said one or more spam pages to create explicit links to said first target page with a computing system; wherein said explicit links are created by the computing system at a frequency rate sufficient to reduce said first ranking and are included as hypertext markup language (HTML) content in said one or more spam pages; (d) repeating any of steps (b) and/or (c) until said first ranking used by the search engine is reduced below a target threshold, without modifying how the search engine processes input queries. | 1. A method of modifying search results of a search engine comprising: (a) identifying a first target page, wherein said first target page has a first ranking used by the search engine in responding to queries directed to a target term; (b) identifying one or more spam pages; (c) automatically causing said one or more spam pages to create explicit links to said first target page with a computing system; wherein said explicit links are created by the computing system at a frequency rate sufficient to reduce said first ranking and are included as hypertext markup language (HTML) content in said one or more spam pages; (d) repeating any of steps (b) and/or (c) until said first ranking used by the search engine is reduced below a target threshold, without modifying how the search engine processes input queries. 5. The method of claim 1 , further comprising repeating steps (a) to (d) for a set of second target pages which appear in a set of search results presented by the search engine in response to a query to said target term. | 0.630435 |
1. A method, comprising: providing a document to a computer system, wherein the document comprises a payee field; assessing, using the computer system, whether writing in the payee field approximately matches a writing profile representation, wherein the matching writing profile representation is associated with a corresponding text representation of a payee name in a computer processable format in memory on the computer system; associating the payee field with the text representation corresponding to the matching writing profile representation; assessing, using the computer system, at least one cross field relationship between two fields of the document; and performing one or more fraud tests of the document based at least in part on information captured from the payee field of the document. | 1. A method, comprising: providing a document to a computer system, wherein the document comprises a payee field; assessing, using the computer system, whether writing in the payee field approximately matches a writing profile representation, wherein the matching writing profile representation is associated with a corresponding text representation of a payee name in a computer processable format in memory on the computer system; associating the payee field with the text representation corresponding to the matching writing profile representation; assessing, using the computer system, at least one cross field relationship between two fields of the document; and performing one or more fraud tests of the document based at least in part on information captured from the payee field of the document. 25. The method of claim 1 , wherein at least one writing profile representation comprises at least one variant of a syntax pattern. | 0.753731 |
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