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8,984,010 | 8 | 14 | 8. A system comprising: a storage device configured to store a database; and a processing device configured to receive a request from a request processor of a database connection pool to access the database, to determine whether a database connection from the database connection pool is available for the request, each database connection based on a first security assertion mark-up language (SAML) assertion, to generate a second SAML, assertion in response to determining that the database connection pool does not have an available database connection for the request, to build a new database connection to the database using the second SAML, assertion based on updated credentials from the first SAML assertion; and maintaining existing database connections that are based on the first SAML assertion open a life cycle of the new database connection independent from a life cycle of the second SAML assertion. | 8. A system comprising: a storage device configured to store a database; and a processing device configured to receive a request from a request processor of a database connection pool to access the database, to determine whether a database connection from the database connection pool is available for the request, each database connection based on a first security assertion mark-up language (SAML) assertion, to generate a second SAML, assertion in response to determining that the database connection pool does not have an available database connection for the request, to build a new database connection to the database using the second SAML, assertion based on updated credentials from the first SAML assertion; and maintaining existing database connections that are based on the first SAML assertion open a life cycle of the new database connection independent from a life cycle of the second SAML assertion. 14. The system of claim 8 , wherein the database connection pool comprises a plurality of request processors, each request processor having a corresponding database connection to the database based on their corresponding SAML assertion. | 0.558052 |
7,933,914 | 1 | 9 | 1. A task system, including a processor communicatively coupled to a memory, the memory having stored therein computer-executable instructions configured to implement the task system comprising: a browser that receives a query, and in response to receiving the query, further receives search results from a search engine for a search based at least in part on the query received, and further receives information related to at least one task object, wherein the at least one task object is selected from one or more sets of task objects stored in one or more memories, each task object comprises at least one modifiable parameter facilitating selection of the at least one task object based at least in part on the query received by the browser; a browser helper object that binds to the browser at runtime, the browser helper object provides information associated with a user's action with respect to the received search results or the received information related to at least one task object, the browser helper object creates an object model corresponding to a schema associated with a web page associated with the user's action, the browser helper object further inserts at least one of the at least one modifiable parameter into a form associated with a web page associated with the user's action, the browser helper object further provides click-through information when the user's action comprises selecting a Uniform Resource Locator (URL) from the received search results, the click-through information including the selected URL, the browser helper object further provides information regarding a website when the user's action comprises manually navigating to the website, the information regarding the website including the URL of the website; a task retrieval model that is updated when the search results are received, the task retrieval model updated based on the click-through information obtained from the browser helper object; and a slot-filling model that is updated when the search results are received, the slot-filling model having one or more slots that hold pieces of information about the at least one task object, the slot-filling model being updated with at least one new parameter representing one new piece of information not currently present in the slot-filling model when the search results include the new piece of information and the new piece of information is not present in the slot-filling model, the slot-filling model also learning one or more new patterns for filling slots based on the search results. | 1. A task system, including a processor communicatively coupled to a memory, the memory having stored therein computer-executable instructions configured to implement the task system comprising: a browser that receives a query, and in response to receiving the query, further receives search results from a search engine for a search based at least in part on the query received, and further receives information related to at least one task object, wherein the at least one task object is selected from one or more sets of task objects stored in one or more memories, each task object comprises at least one modifiable parameter facilitating selection of the at least one task object based at least in part on the query received by the browser; a browser helper object that binds to the browser at runtime, the browser helper object provides information associated with a user's action with respect to the received search results or the received information related to at least one task object, the browser helper object creates an object model corresponding to a schema associated with a web page associated with the user's action, the browser helper object further inserts at least one of the at least one modifiable parameter into a form associated with a web page associated with the user's action, the browser helper object further provides click-through information when the user's action comprises selecting a Uniform Resource Locator (URL) from the received search results, the click-through information including the selected URL, the browser helper object further provides information regarding a website when the user's action comprises manually navigating to the website, the information regarding the website including the URL of the website; a task retrieval model that is updated when the search results are received, the task retrieval model updated based on the click-through information obtained from the browser helper object; and a slot-filling model that is updated when the search results are received, the slot-filling model having one or more slots that hold pieces of information about the at least one task object, the slot-filling model being updated with at least one new parameter representing one new piece of information not currently present in the slot-filling model when the search results include the new piece of information and the new piece of information is not present in the slot-filling model, the slot-filling model also learning one or more new patterns for filling slots based on the search results. 9. The system of claim 1 , the information associated with the user's action comprising a clicked-through URL. | 0.660494 |
9,104,314 | 9 | 14 | 9. An apparatus for performing calculations in a character input mode of a electronic device, comprising: a display unit displaying input characters in a character input window in the character input mode; and a control unit determining whether a preset calculation enabling condition is satisfied, checking whether an arithmetic expression is present in the displayed input characters, evaluating the arithmetic expression when the preset calculation enabling condition is satisfied, and controlling the display unit to display a result of the evaluation. | 9. An apparatus for performing calculations in a character input mode of a electronic device, comprising: a display unit displaying input characters in a character input window in the character input mode; and a control unit determining whether a preset calculation enabling condition is satisfied, checking whether an arithmetic expression is present in the displayed input characters, evaluating the arithmetic expression when the preset calculation enabling condition is satisfied, and controlling the display unit to display a result of the evaluation. 14. The apparatus of claim 9 , wherein the control unit controls the display unit to display a pop-up window containing the evaluation result close to the arithmetic expression. | 0.592166 |
8,970,609 | 12 | 13 | 12. A system for generating a visual representation of a continuous computation language (CCL) document, comprising: one or more processors; one or more memories coupled to the one or more processors; the CCL document being stored in the one or more memories and comprising one or more CCL statements; a text-to-visual mapping module being stored in the one or more memories and executing on the one or more processors and configured to convert the CCL statements to visual objects as a representation of instruction logic of the CCL document graphically on a display device, wherein to convert the CCL statements the text-to-visual mapping module is further configured to: for each CCL statement generate a plurality of parent nodes based on CCL statement keywords; identify different connection types between the plurality of parent nodes, wherein the connection types are based on semantics between the plurality of parent nodes; and draw the different connections between the plurality of parent nodes based on the different connection types; and the text-to-visual mapping module is further configured to: determine a number of instructions in each CCL statement that generated a parent node in the plurality of parent nodes; and based on the number of instructions, generate child nodes for the parent node, one child node per instruction in each CCL statement. | 12. A system for generating a visual representation of a continuous computation language (CCL) document, comprising: one or more processors; one or more memories coupled to the one or more processors; the CCL document being stored in the one or more memories and comprising one or more CCL statements; a text-to-visual mapping module being stored in the one or more memories and executing on the one or more processors and configured to convert the CCL statements to visual objects as a representation of instruction logic of the CCL document graphically on a display device, wherein to convert the CCL statements the text-to-visual mapping module is further configured to: for each CCL statement generate a plurality of parent nodes based on CCL statement keywords; identify different connection types between the plurality of parent nodes, wherein the connection types are based on semantics between the plurality of parent nodes; and draw the different connections between the plurality of parent nodes based on the different connection types; and the text-to-visual mapping module is further configured to: determine a number of instructions in each CCL statement that generated a parent node in the plurality of parent nodes; and based on the number of instructions, generate child nodes for the parent node, one child node per instruction in each CCL statement. 13. The system of claim 12 , wherein the plurality of parent nodes and the different connections represent the instruction logic included in the CCL document. | 0.5 |
9,465,879 | 1 | 8 | 1. A method comprising: receiving, by at least one computer, crawling data from a crawler crawling a content preview source; extracting, by the at least one computer in connection with crawling the content preview source, data and a link from the content preview source, the link comprising a link to a target document, the data to be used to create a content preview document previewing the target document, the target document containing content being previewed by the content preview source; creating, by the at least one computer in connection with crawling the content preview source, the content preview document using the data extracted from the content preview source, the content preview document being different from the target document and the content preview source, the content preview document being created without using the target document; and making, by the at least one computer, the created content preview document available for searching by a search engine in an index prior to the target document being made available for searching by the search engine in the index. | 1. A method comprising: receiving, by at least one computer, crawling data from a crawler crawling a content preview source; extracting, by the at least one computer in connection with crawling the content preview source, data and a link from the content preview source, the link comprising a link to a target document, the data to be used to create a content preview document previewing the target document, the target document containing content being previewed by the content preview source; creating, by the at least one computer in connection with crawling the content preview source, the content preview document using the data extracted from the content preview source, the content preview document being different from the target document and the content preview source, the content preview document being created without using the target document; and making, by the at least one computer, the created content preview document available for searching by a search engine in an index prior to the target document being made available for searching by the search engine in the index. 8. The method of claim 1 , further comprising: fetching the target document using the extracted link; associating the data extracted from the content preview source and the fetched target document; and adding the target document to the index that is searchable by the search engine. | 0.5 |
8,046,683 | 7 | 8 | 7. The method according to claim 1 , wherein using the schema and the portions of the markup language fragment respectively corresponding to the child nodes for data entry with the data entry fields further comprises displaying an electronic form on a user interface (UI) for interactive data entry with the electronic form. | 7. The method according to claim 1 , wherein using the schema and the portions of the markup language fragment respectively corresponding to the child nodes for data entry with the data entry fields further comprises displaying an electronic form on a user interface (UI) for interactive data entry with the electronic form. 8. The method according to claim 7 , wherein the formed markup language fragment is formed when the electronic form is created. | 0.904798 |
8,396,712 | 5 | 8 | 5. A non-transitory computer-readable medium, having stored thereon a sequence of instructions, which when executed by a computer, cause the computer to perform a method for generating a finite state grammar, the method comprising: (a) receiving user input of a plurality of sample phrases each comprising a plurality of words; (b) representing each sample phrase as a node in a tree; (c) forming a mathematical expression for each pair of nodes in the tree to represent the sample phrases associated with the pair of nodes, the mathematical expression comprising a plurality of words found in the sample phrases of the pair of nodes and an indication of whether a word is a common word that occurs in each of the plurality of phrases or an optional word that occurs in some of the plurality of phrases for the pair of nodes; (d) generating a compact mathematical expression by comparing the mathematical expressions one pair at a time, wherein the compact mathematical expression includes each of the plurality of words found in the sample phrases and an indication of whether each of the plurality of words is a common word or an optional word; (e) displaying the compact mathematical expression to a user; (f) allowing the user to alter the compact mathematical expression; (g) generating a finite state grammar corresponding to the altered compact mathematical expression; and (h) displaying the finite state grammar to the user. | 5. A non-transitory computer-readable medium, having stored thereon a sequence of instructions, which when executed by a computer, cause the computer to perform a method for generating a finite state grammar, the method comprising: (a) receiving user input of a plurality of sample phrases each comprising a plurality of words; (b) representing each sample phrase as a node in a tree; (c) forming a mathematical expression for each pair of nodes in the tree to represent the sample phrases associated with the pair of nodes, the mathematical expression comprising a plurality of words found in the sample phrases of the pair of nodes and an indication of whether a word is a common word that occurs in each of the plurality of phrases or an optional word that occurs in some of the plurality of phrases for the pair of nodes; (d) generating a compact mathematical expression by comparing the mathematical expressions one pair at a time, wherein the compact mathematical expression includes each of the plurality of words found in the sample phrases and an indication of whether each of the plurality of words is a common word or an optional word; (e) displaying the compact mathematical expression to a user; (f) allowing the user to alter the compact mathematical expression; (g) generating a finite state grammar corresponding to the altered compact mathematical expression; and (h) displaying the finite state grammar to the user. 8. The non-transitory computer-readable medium of claim 5 , wherein the method further comprises receiving user input of further sample phrases and performing steps (b) to (h), at least once. | 0.771531 |
7,873,992 | 25 | 26 | 25. A system, comprising: an input operable to receive a stream of information, the stream being generated by one of a plurality of possible different telecommunication components, wherein each telecommunication component generates a stream corresponding to a unique input structure; and a processor executable parser operable to: (a) compare at least a portion of the stream with multiple different tokens to provide a subset of tokens identified in the at least a portion of the stream, each token corresponding to a unique input structure; (b) based on the subset of tokens, identify, from among at least one of a plurality of possible input structures and a plurality of possible telecommunication components, at least one of an input structure corresponding to the at least a portion of the stream and a telecommunication component for the at least a portion of the stream; and (c) parse the stream based on the identified at least one of an input structure and telecommunication component, wherein the processor executable parser is not provided with an input structure identifier, other than the corresponding input structure itself, either in or external to the at least a portion of the input stream to identify or assist in the identification of the at least one of the respective input structure corresponding to the at least a portion of the stream and a telecommunication component for the at least a portion of the stream. | 25. A system, comprising: an input operable to receive a stream of information, the stream being generated by one of a plurality of possible different telecommunication components, wherein each telecommunication component generates a stream corresponding to a unique input structure; and a processor executable parser operable to: (a) compare at least a portion of the stream with multiple different tokens to provide a subset of tokens identified in the at least a portion of the stream, each token corresponding to a unique input structure; (b) based on the subset of tokens, identify, from among at least one of a plurality of possible input structures and a plurality of possible telecommunication components, at least one of an input structure corresponding to the at least a portion of the stream and a telecommunication component for the at least a portion of the stream; and (c) parse the stream based on the identified at least one of an input structure and telecommunication component, wherein the processor executable parser is not provided with an input structure identifier, other than the corresponding input structure itself, either in or external to the at least a portion of the input stream to identify or assist in the identification of the at least one of the respective input structure corresponding to the at least a portion of the stream and a telecommunication component for the at least a portion of the stream. 26. The system of claim 25 , wherein each of the tokens has a corresponding parser expressing a set of syntactical and/or semantical relationships relating to the respective token and wherein the processor executable parser is further operable, for each token in the subset of tokens, to (d) to invoke a corresponding method. | 0.638085 |
9,660,869 | 1 | 3 | 1. A method for implementation by one or more data processors forming part of at least one computing system, the method comprising: obtaining, by at least one data processor, a plurality of records from a plurality of sources, the plurality of records comprising a plurality of types of data; assembling, by at least one data processor, a plurality of typed datasets based on the obtained records, the assembling comprising: extracting, from the plurality of records, typed data that corresponds to all data of a single type found in the obtained records; assembling, by at least one data processor, at least one network comprising: a plurality of nodes representing all instances of the typed data corresponding to a common event; and a plurality of edges representing a relationship between the plurality of nodes, the relationship defining a connection between two or more of the plurality of nodes, where the edges comprise a weighting attribute representing a similarity between the nodes connected by the connection, the plurality of nodes and the plurality of edges stored as accessible memory objects in the at least one computing system; assembling, by at least one data processor, a vector by using a network analyzer, the assembling comprising: determining a required input format for an analytic configured to operate on the vector; and generating, at the network analyzer, the vector comprising a subset of the typed data corresponding to the required input format; passing, by at least one data processor, the vector to the analytic; generating, by at least one data processor and the analytic, an output from the analytic based on at least the vector passed to the analytic, the output comprising electronic data corresponding to a result of the analytic operating on the vector; and providing, by at least one data processor, data comprising the output. | 1. A method for implementation by one or more data processors forming part of at least one computing system, the method comprising: obtaining, by at least one data processor, a plurality of records from a plurality of sources, the plurality of records comprising a plurality of types of data; assembling, by at least one data processor, a plurality of typed datasets based on the obtained records, the assembling comprising: extracting, from the plurality of records, typed data that corresponds to all data of a single type found in the obtained records; assembling, by at least one data processor, at least one network comprising: a plurality of nodes representing all instances of the typed data corresponding to a common event; and a plurality of edges representing a relationship between the plurality of nodes, the relationship defining a connection between two or more of the plurality of nodes, where the edges comprise a weighting attribute representing a similarity between the nodes connected by the connection, the plurality of nodes and the plurality of edges stored as accessible memory objects in the at least one computing system; assembling, by at least one data processor, a vector by using a network analyzer, the assembling comprising: determining a required input format for an analytic configured to operate on the vector; and generating, at the network analyzer, the vector comprising a subset of the typed data corresponding to the required input format; passing, by at least one data processor, the vector to the analytic; generating, by at least one data processor and the analytic, an output from the analytic based on at least the vector passed to the analytic, the output comprising electronic data corresponding to a result of the analytic operating on the vector; and providing, by at least one data processor, data comprising the output. 3. The method of claim 1 , wherein the analytic is a predictive analytic configured to generate electronic data corresponding to a predictive output based at least on a provided query and historical data for the typed data. | 0.735782 |
9,924,306 | 17 | 20 | 17. A portable processor-based device comprising: a global positioning system receiver; and one or more processors configured to: access geographic location information from the global positioning system receiver; provide the geographic location information to a computer-implemented matching system that determines a level of mutual interest in establishing contact between a first user of the portable processor-based device and a second user of a second processor-based device, wherein the level of mutual interest is inferred, at least in part, from the geographic location information; receive a recommendation comprising a representation of the second user, wherein the recommendation is generated based on the level of mutual interest; determine a first expression of interest based on one or more behaviors exhibited by the first user in response to receiving the recommendation; provide the determined first expression of interest to the computer-implemented matching system, which determines a bilateral expression of interest between the first user and the second user, wherein the bilateral expression of interest is determined the first expression of interest and a second expression of interest based on one or more behaviors exhibited by the second user in response to receiving a recommendation comprising a representation of the first user; receive, the computer-implemented matching system, an indication of the bilateral expression of interest between the first user and the second user; and reveal the indication of the bilateral expression of interest to the first user. | 17. A portable processor-based device comprising: a global positioning system receiver; and one or more processors configured to: access geographic location information from the global positioning system receiver; provide the geographic location information to a computer-implemented matching system that determines a level of mutual interest in establishing contact between a first user of the portable processor-based device and a second user of a second processor-based device, wherein the level of mutual interest is inferred, at least in part, from the geographic location information; receive a recommendation comprising a representation of the second user, wherein the recommendation is generated based on the level of mutual interest; determine a first expression of interest based on one or more behaviors exhibited by the first user in response to receiving the recommendation; provide the determined first expression of interest to the computer-implemented matching system, which determines a bilateral expression of interest between the first user and the second user, wherein the bilateral expression of interest is determined the first expression of interest and a second expression of interest based on one or more behaviors exhibited by the second user in response to receiving a recommendation comprising a representation of the first user; receive, the computer-implemented matching system, an indication of the bilateral expression of interest between the first user and the second user; and reveal the indication of the bilateral expression of interest to the first user. 20. The portable processor-based device of claim 17 , wherein the one or more processors are further configured to: monitor an involuntary physiological response associated with use of the portable processor-based device by the first user; wherein the one or more processors determine the first expression of interest exhibited by the first user based on the involuntary physiological response. | 0.51358 |
8,761,659 | 17 | 22 | 17. A method of enabling access to business intelligence elements comprising: associating electronic learning elements with a business intelligence system object; displaying available business intelligence system objects to users; and utilizing a web service to disable a business intelligence system object for a user based on information associated with the user and the business intelligence object related to the electronic learning element. | 17. A method of enabling access to business intelligence elements comprising: associating electronic learning elements with a business intelligence system object; displaying available business intelligence system objects to users; and utilizing a web service to disable a business intelligence system object for a user based on information associated with the user and the business intelligence object related to the electronic learning element. 22. The method of claim 17 wherein the one or more portions comprises a report definition element. | 0.791489 |
9,087,139 | 11 | 15 | 11. A system for processing a query, comprising: a processor; and storage coupled to the processor, wherein the storage stores a computer program, and wherein the processor is configured to execute the computer program to perform operations, and wherein the operations comprise: receiving the query, wherein the query is formed by one or more paths, and wherein each path includes one or more steps; receiving a hierarchical document including one or more document nodes; while processing the query and traversing the hierarchical document, constructing a structure, wherein the structure includes structure nodes, and wherein each of the structure nodes includes a next step in a path of the query, a level for a next step instance, a parent step instance identifier of a next step instance, and a matched step instance identifier when a match is found; constructing one or more extraction entries by traversing the structure bottom up, starting from a last structure node and continuing up to a root node of the structure while propagating up parent step instance identifier to form a step instance ancestor path, wherein each of the one or more extraction entries includes a step instance match candidate identifying a document node and the step instance ancestor path for the document node; and constructing one or more tuples using the one or more extraction entries by associating the step instance match candidate from one of the one or more extraction entries with the step instance match candidate from at least one of the one or more other extraction entries. | 11. A system for processing a query, comprising: a processor; and storage coupled to the processor, wherein the storage stores a computer program, and wherein the processor is configured to execute the computer program to perform operations, and wherein the operations comprise: receiving the query, wherein the query is formed by one or more paths, and wherein each path includes one or more steps; receiving a hierarchical document including one or more document nodes; while processing the query and traversing the hierarchical document, constructing a structure, wherein the structure includes structure nodes, and wherein each of the structure nodes includes a next step in a path of the query, a level for a next step instance, a parent step instance identifier of a next step instance, and a matched step instance identifier when a match is found; constructing one or more extraction entries by traversing the structure bottom up, starting from a last structure node and continuing up to a root node of the structure while propagating up parent step instance identifier to form a step instance ancestor path, wherein each of the one or more extraction entries includes a step instance match candidate identifying a document node and the step instance ancestor path for the document node; and constructing one or more tuples using the one or more extraction entries by associating the step instance match candidate from one of the one or more extraction entries with the step instance match candidate from at least one of the one or more other extraction entries. 15. The system of claim 11 , wherein each of the one or more extraction entries includes the level of a corresponding step instance match candidate. | 0.784884 |
9,832,646 | 1 | 3 | 1. A system for providing continuous automated verification of user identity and intent, comprising: at least one server for communicating with a network; at least one network interface card associated with the at least one server for providing access to data flow through the network; a processor within each of the at least one server, the processor implementing a first processing node and a second processing node for: monitoring, prior to granting at least one user access to the network, at the first processing node associated with the network, a mirrored live-data flow of a live-data flow passing through the first processing node in a non-intrusive manner that does not affect the live-data flow passing through the first processing node, wherein the live-data flow comprises data that is in active transmission between endpoints in the network and prior to storage of the data within the live-data flow in a database; detecting relevant network access and activity in the mirrored live data flow; dynamically generating a first set of verification criteria at the second processing node based on live data inputs from the mirrored live-data flow and external data sources to verify an identify and an activity of the at least one user attempting to access the network prior to access and performing an activity on the network, wherein the first set of verification criteria comprise a first set of dynamically generated dialogue of questions with associated answers to be provided by the at least one user; dynamically generating a second set of verification criteria at the second processing node based on the responses provided by the at least one user to the first set of dynamically generated dialogue of questions to verify the identity and the activity of the at least one user attempting to access the network, wherein the second set of verification criteria comprise a second set of dynamically generated dialogue of questions with associated answers to be provided by the at least one user; dynamically adjusting a required threshold level at which the first and second verification criteria must be met by the at least one user attempting the network access in order to allow or deny the network access and activity by the at least one user; denying the relevant network access and activity if the verification criteria are not met at the required threshold level, to preempt unverified and unwanted access to and activity on the network by the at least one user; allowing the relevant network access and activity if the verification criteria are met at the required threshold level; and continuing to monitor and verify the user identity and the user activity for a dynamic time period after access and activity on the network is granted, to ensure continued user identity and activity fidelity. | 1. A system for providing continuous automated verification of user identity and intent, comprising: at least one server for communicating with a network; at least one network interface card associated with the at least one server for providing access to data flow through the network; a processor within each of the at least one server, the processor implementing a first processing node and a second processing node for: monitoring, prior to granting at least one user access to the network, at the first processing node associated with the network, a mirrored live-data flow of a live-data flow passing through the first processing node in a non-intrusive manner that does not affect the live-data flow passing through the first processing node, wherein the live-data flow comprises data that is in active transmission between endpoints in the network and prior to storage of the data within the live-data flow in a database; detecting relevant network access and activity in the mirrored live data flow; dynamically generating a first set of verification criteria at the second processing node based on live data inputs from the mirrored live-data flow and external data sources to verify an identify and an activity of the at least one user attempting to access the network prior to access and performing an activity on the network, wherein the first set of verification criteria comprise a first set of dynamically generated dialogue of questions with associated answers to be provided by the at least one user; dynamically generating a second set of verification criteria at the second processing node based on the responses provided by the at least one user to the first set of dynamically generated dialogue of questions to verify the identity and the activity of the at least one user attempting to access the network, wherein the second set of verification criteria comprise a second set of dynamically generated dialogue of questions with associated answers to be provided by the at least one user; dynamically adjusting a required threshold level at which the first and second verification criteria must be met by the at least one user attempting the network access in order to allow or deny the network access and activity by the at least one user; denying the relevant network access and activity if the verification criteria are not met at the required threshold level, to preempt unverified and unwanted access to and activity on the network by the at least one user; allowing the relevant network access and activity if the verification criteria are met at the required threshold level; and continuing to monitor and verify the user identity and the user activity for a dynamic time period after access and activity on the network is granted, to ensure continued user identity and activity fidelity. 3. The system of claim 1 , wherein the unverified and unwanted access comprises at least one of fraudulent, abusive, intrusive or unverified access to the network. | 0.880499 |
7,577,739 | 2 | 3 | 2. The method of claim 1 , further comprising a software portion configured to prioritize the order in which regular expressions within a subject matter category are tested. | 2. The method of claim 1 , further comprising a software portion configured to prioritize the order in which regular expressions within a subject matter category are tested. 3. The method of claim 2 , wherein said prioritizing software portion reduces the likelihood of false hits. | 0.5 |
8,849,810 | 17 | 18 | 17. One or more devices comprising: one or more processors to: obtain search results that are relevant to a search query, the search query being: generated by the one or more processors, or received from a first user, the search query not being generated by the one or more processors when the search query is received from the first user; refine the search results based on a type of an application used by a first user to compose a message to a second user; provide the refined search results to the first user, the refined search results being provided via a first region of an interface when the search query is generated by the one or more processors, and the refined search results being provided via a second region of the interface when the search query is received from the first user, the second region being different from the first region, and the first region including a button that, when selected by the first user, causes the first region to be removed from the interface, the search query not being generated by the one or more processors when the button is selected, a selection of a particular one of the refined search results causing data associated with the particular one of the refined search results to be incorporated into a message to a second user, the data including: a link to a document associated with the particular one of the refined search results, and a snippet that includes a portion of text from the document, the portion, included in the snippet, being selected from the text included in the document based on a content of the message and a user profile associated with the first user, the user profile being determined based on at least one of a prior search associated with the first user, or information provided by the first user, and the particular one of the refined search results being associated with a geographic location; receive, from the second user, a request to access, via the link, information associated with the particular one of the refined search results; and provide, to the second user, the information associated with the particular one of the refined search results, the information including a web page presenting a map of the geographic location relative to a geographic location of the second user. | 17. One or more devices comprising: one or more processors to: obtain search results that are relevant to a search query, the search query being: generated by the one or more processors, or received from a first user, the search query not being generated by the one or more processors when the search query is received from the first user; refine the search results based on a type of an application used by a first user to compose a message to a second user; provide the refined search results to the first user, the refined search results being provided via a first region of an interface when the search query is generated by the one or more processors, and the refined search results being provided via a second region of the interface when the search query is received from the first user, the second region being different from the first region, and the first region including a button that, when selected by the first user, causes the first region to be removed from the interface, the search query not being generated by the one or more processors when the button is selected, a selection of a particular one of the refined search results causing data associated with the particular one of the refined search results to be incorporated into a message to a second user, the data including: a link to a document associated with the particular one of the refined search results, and a snippet that includes a portion of text from the document, the portion, included in the snippet, being selected from the text included in the document based on a content of the message and a user profile associated with the first user, the user profile being determined based on at least one of a prior search associated with the first user, or information provided by the first user, and the particular one of the refined search results being associated with a geographic location; receive, from the second user, a request to access, via the link, information associated with the particular one of the refined search results; and provide, to the second user, the information associated with the particular one of the refined search results, the information including a web page presenting a map of the geographic location relative to a geographic location of the second user. 18. The one or more devices of claim 17 , where the message is associated with a particular topic, and where the one or more processors are further to: adjust, based on the received request, a reputation score of the first user with respect to the particular topic. | 0.5 |
7,921,063 | 11 | 15 | 11. A data processing system, comprising: means for training a probabilistic filter using first properties of one or more first network resource identifiers obtained from a whitelist; wherein at least one of the first properties is obtained from any of: information obtained from DNS queries based, at least in part, on the one or more first work resource identifiers; server software information; or information obtained from “whois” queries based, at least in part, on information contained in the network resource identifier; means for training the probabilistic filter using second properties of one or more second network resource identifiers obtained from a blocklist; means for testing third properties of a third network resource identifier using the probabilistic filter, resulting in creating a probability output; means for adding the third network resource identifier to the blocklist when the probability output is greater than a specified threshold. | 11. A data processing system, comprising: means for training a probabilistic filter using first properties of one or more first network resource identifiers obtained from a whitelist; wherein at least one of the first properties is obtained from any of: information obtained from DNS queries based, at least in part, on the one or more first work resource identifiers; server software information; or information obtained from “whois” queries based, at least in part, on information contained in the network resource identifier; means for training the probabilistic filter using second properties of one or more second network resource identifiers obtained from a blocklist; means for testing third properties of a third network resource identifier using the probabilistic filter, resulting in creating a probability output; means for adding the third network resource identifier to the blocklist when the probability output is greater than a specified threshold. 15. The invention of claim 11 , further comprising: means for extracting a domain name portion of the third network resource identifier; means for retrieving one or more NS records for the domain name portion from a domain name system (DNS) server; means for retrieving network address records for each mail exchange that is identified in the one or more NS records; means for determining an average reputation score for the network address records; means for adding the third network resource identifier to the blocklist when the average reputation score is less than a specified threshold. | 0.524155 |
7,882,148 | 20 | 21 | 20. The computer-implemented method according to claim 18 , wherein modeling the context representation includes varying in a time dependent manner the value of the activation attribute of the at least one context entity. | 20. The computer-implemented method according to claim 18 , wherein modeling the context representation includes varying in a time dependent manner the value of the activation attribute of the at least one context entity. 21. The computer-implemented method according to claim 20 , wherein varying in a time dependent manner the value of the activation attribute includes decreasing over time the value of the activation attribute according to a predetermined fade curve. | 0.5 |
9,350,561 | 24 | 29 | 24. A network computer for generating a computer visualization of data, comprising: a transceiver that communicates over the network; a non-transitory memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: selecting a visualization model based on at least an allocation model, wherein the visualization model includes one or more visualization model items; mapping one or more allocation model items included in the allocation model to the one or more visualization model items; providing a resource value for each of the one or more visualization model items by at least aggregating an amount of resources corresponding to each of their one or more mapped allocation model items; storing the visualization model in the non-transitory memory of the computer, wherein the visualization model includes one or more resource values for the one or more visualization model items; displaying one or more portions of the visualization model that overlays the allocation model in a user interface of the network computer, wherein the allocation model underlies the visualization model; and when a visualization model item is selected using the user interface of the network computer perform further actions, including: traversing the underlying allocation model to identify one or more source allocation model items and one or more target allocation model items that are associated with the selected visualization model item; providing one or more source visualization model items that provide resources to the selected visualization model item based on the one or more identified source allocation model items; providing one or more target visualization model items that receive resources from the selected visualization model item based on the one or more identified target allocation model items; displaying on the user interface one or more input flow lines that start from the one or more source visualization model items and end at the selected visualization model item; and displaying on the user interface one or more output flow lines that start from the selected visualization model item and end at the one or more target visualization model items. | 24. A network computer for generating a computer visualization of data, comprising: a transceiver that communicates over the network; a non-transitory memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: selecting a visualization model based on at least an allocation model, wherein the visualization model includes one or more visualization model items; mapping one or more allocation model items included in the allocation model to the one or more visualization model items; providing a resource value for each of the one or more visualization model items by at least aggregating an amount of resources corresponding to each of their one or more mapped allocation model items; storing the visualization model in the non-transitory memory of the computer, wherein the visualization model includes one or more resource values for the one or more visualization model items; displaying one or more portions of the visualization model that overlays the allocation model in a user interface of the network computer, wherein the allocation model underlies the visualization model; and when a visualization model item is selected using the user interface of the network computer perform further actions, including: traversing the underlying allocation model to identify one or more source allocation model items and one or more target allocation model items that are associated with the selected visualization model item; providing one or more source visualization model items that provide resources to the selected visualization model item based on the one or more identified source allocation model items; providing one or more target visualization model items that receive resources from the selected visualization model item based on the one or more identified target allocation model items; displaying on the user interface one or more input flow lines that start from the one or more source visualization model items and end at the selected visualization model item; and displaying on the user interface one or more output flow lines that start from the selected visualization model item and end at the one or more target visualization model items. 29. The network computer claim 24 , wherein the one or more processor devices execute instructions that perform actions further comprising: providing a displayed flow line thickness at a beginning of a flow line originating from a source visualization model item based on a proportion of the source visualization model item's total resources and the amount of its resources that are provided to a target visualization model item; and providing a displayed another flow line thickness at an end of the flow line that terminates at the target visualization model item based on a proportion of the target visualization model item's total resources and the amount of resources provided by the source visualization model item. | 0.5 |
7,716,040 | 1 | 2 | 1. A computer-implemented method comprising: (A) identifying a document including a first coding having a first feature encoding a first concept, the first coding being associated with a first code and first data; (B) rendering, by a processor, the first data to have a visual characteristic that is based on the first feature, without rendering the first code; (C) receiving a first indication from a user of whether the rendering is accurate; (D) identifying, based on the first indication received from the user, a verification status of the first coding, wherein the verification status of the first coding indicates whether the first data represents the first concept, comprising: (D)(1) if the first indication that the rendering is accurate, then identifying a verification status of the first coding indicating that the first coding is accurate; and (D)(2) otherwise, identifying a verification status of the first coding indicating that the first coding is inaccurate; and (E) if the verification status of the first coding indicates that the first coding is inaccurate, then modifying the first feature of the first coding. | 1. A computer-implemented method comprising: (A) identifying a document including a first coding having a first feature encoding a first concept, the first coding being associated with a first code and first data; (B) rendering, by a processor, the first data to have a visual characteristic that is based on the first feature, without rendering the first code; (C) receiving a first indication from a user of whether the rendering is accurate; (D) identifying, based on the first indication received from the user, a verification status of the first coding, wherein the verification status of the first coding indicates whether the first data represents the first concept, comprising: (D)(1) if the first indication that the rendering is accurate, then identifying a verification status of the first coding indicating that the first coding is accurate; and (D)(2) otherwise, identifying a verification status of the first coding indicating that the first coding is inaccurate; and (E) if the verification status of the first coding indicates that the first coding is inaccurate, then modifying the first feature of the first coding. 2. The method of claim 1 , wherein the first feature comprises a specified relationship between the first coding and a second coding, and wherein (E) comprises modifying the relationship between the first coding and the second coding. | 0.561798 |
8,812,340 | 6 | 9 | 6. A workflow method comprising: using a processor device, performing: communicating with a database comprising a history of an evolving workflow; upon termination of a current task in the evolving workflow: receiving from the current task: a description of the evolving workflow comprising a goal, history, conditions, and rules associated with said evolving workflow; a task query comprising a request for a next appropriate task definition, wherein said next appropriate task definition describes a task in terms of attributes that are relevant to its characterization, and conditions/rules upon which said task is appropriate for progress of the workflow, wherein said attributes are not inherited from other tasks; and receiving from task definer units a plurality of task definitions as candidates for the next appropriate task definition; evaluating the plurality of the task definitions received from the task definer units against the task query based on at least one property associated with each task definition to select the next appropriate task definition; and providing at least one task definition as an offer based on the evaluation, wherein said at least one task definition matches the goal of said workflow, whereupon a next task matching the at least one task definition is selected and put into place, ready to be activated; basing the selection of the next task on a most up-to-date circumstance by deferring selection of the next task until termination of the current task; activating the next task only when the previously terminated activity transfers control of the workflow to said next task, whereupon the next task becomes the current task. | 6. A workflow method comprising: using a processor device, performing: communicating with a database comprising a history of an evolving workflow; upon termination of a current task in the evolving workflow: receiving from the current task: a description of the evolving workflow comprising a goal, history, conditions, and rules associated with said evolving workflow; a task query comprising a request for a next appropriate task definition, wherein said next appropriate task definition describes a task in terms of attributes that are relevant to its characterization, and conditions/rules upon which said task is appropriate for progress of the workflow, wherein said attributes are not inherited from other tasks; and receiving from task definer units a plurality of task definitions as candidates for the next appropriate task definition; evaluating the plurality of the task definitions received from the task definer units against the task query based on at least one property associated with each task definition to select the next appropriate task definition; and providing at least one task definition as an offer based on the evaluation, wherein said at least one task definition matches the goal of said workflow, whereupon a next task matching the at least one task definition is selected and put into place, ready to be activated; basing the selection of the next task on a most up-to-date circumstance by deferring selection of the next task until termination of the current task; activating the next task only when the previously terminated activity transfers control of the workflow to said next task, whereupon the next task becomes the current task. 9. The workflow method of claim 6 wherein at least one of properties associated with the task definitions is dynamic, and the method further comprises the step of utilizing at least one specific value of the dynamic properties based on properties of the workflow in the evaluation of the tasks. | 0.65814 |
7,536,448 | 12 | 14 | 12. A system for generating an Internetworking Operating System IOS Command Line Interface (CLI) configuration model using a processor, the system comprising: a formal specification tool for representing a structure of an IOS CLI configuration base in a formal specification format, the IOS CLI configuration base providing cross-CLI dependencies that specify an ordering of components in the IOS CLI configuration base, the formal specification tool being further for representing mapping rules in the formal specification format for mapping the represented structure of the IOS CLI configuration base to a user-defined format; a receiver for receiving an IOS user-defined configuration that is input by a user on the CLI for the IOS CLI configuration base; a dependency tree generator for generating a machine-readable IOS CLI Dependency Tree (ICDT) from the represented structure of the IOS CLI configuration base, the ICDT being a dependency graph representing the components and the ordering of the cross-CLI dependencies, the ICDT being generated in the user-defined format using the represented mapping rules; and a compiler for automatically generating a logical topology of the IOS CLI configuration model from the machine-readable ICDT and the IOS user-defined configuration by traversing the dependency graph to determine components in the dependency graph that are usable to configure the logical topology, wherein a logical connection between the determined components is based on the ordering in the dependency graph, the IOS CLI configuration model displaying the logical topology in the IOS user-defined configuration based on the mapping rules. | 12. A system for generating an Internetworking Operating System IOS Command Line Interface (CLI) configuration model using a processor, the system comprising: a formal specification tool for representing a structure of an IOS CLI configuration base in a formal specification format, the IOS CLI configuration base providing cross-CLI dependencies that specify an ordering of components in the IOS CLI configuration base, the formal specification tool being further for representing mapping rules in the formal specification format for mapping the represented structure of the IOS CLI configuration base to a user-defined format; a receiver for receiving an IOS user-defined configuration that is input by a user on the CLI for the IOS CLI configuration base; a dependency tree generator for generating a machine-readable IOS CLI Dependency Tree (ICDT) from the represented structure of the IOS CLI configuration base, the ICDT being a dependency graph representing the components and the ordering of the cross-CLI dependencies, the ICDT being generated in the user-defined format using the represented mapping rules; and a compiler for automatically generating a logical topology of the IOS CLI configuration model from the machine-readable ICDT and the IOS user-defined configuration by traversing the dependency graph to determine components in the dependency graph that are usable to configure the logical topology, wherein a logical connection between the determined components is based on the ordering in the dependency graph, the IOS CLI configuration model displaying the logical topology in the IOS user-defined configuration based on the mapping rules. 14. The system in accordance with claim 12 , wherein the formal specification format comprises Backus-Naur Form (BNF). | 0.691099 |
6,016,499 | 1 | 11 | 1. A system providing access to a directory services repository which is stored on a computer system, the claimed system comprising: a directory services application programming interface, also known as the API, which includes at least one callable element that is capable of accessing a component of the directory services repository in response to being called; and a driver which is capable of translating a relational database language statement into an executable API sequence that includes a call to the callable element and produces an API result, the driver also being capable of translating the API result into a relational database result, wherein the directory services repository component includes an effective class and an object having a context the relational database language statement identifies a table and a subset restriction, and the driver and the API together map the effective class to the table and also map the context to the subset restriction. | 1. A system providing access to a directory services repository which is stored on a computer system, the claimed system comprising: a directory services application programming interface, also known as the API, which includes at least one callable element that is capable of accessing a component of the directory services repository in response to being called; and a driver which is capable of translating a relational database language statement into an executable API sequence that includes a call to the callable element and produces an API result, the driver also being capable of translating the API result into a relational database result, wherein the directory services repository component includes an effective class and an object having a context the relational database language statement identifies a table and a subset restriction, and the driver and the API together map the effective class to the table and also map the context to the subset restriction. 11. The system of claim 1, wherein the directory services repository component includes an object that is an instance of the effective class, the relational database language statement identifies a row in the table, and the driver and the API together map the object to the row. | 0.666667 |
8,515,901 | 8 | 12 | 8. A computer-implemented people matching system, comprising one or more processor-based devices configured to execute: a relationship-altering function that enables a first person, who is a first user of a computer-implemented system, to explicitly alter a computer-implemented directionally distinct relationship between the first person and a second person, wherein the second person is a second user of the computer-implemented system; a people matching function that generates a match comprising a first person and a third person, wherein the match is generated based, at least in part, on an inference from a plurality of usage behaviors, wherein one of the plurality of usage behaviors is the first person using the relationship altering function to explicitly alter the computer-implemented directionally distinct relationship between the first person and the second person; and a computer implemented explanatory function that delivers a reason for the match to the first person, wherein the reason comprises one of the plurality of usage behaviors. | 8. A computer-implemented people matching system, comprising one or more processor-based devices configured to execute: a relationship-altering function that enables a first person, who is a first user of a computer-implemented system, to explicitly alter a computer-implemented directionally distinct relationship between the first person and a second person, wherein the second person is a second user of the computer-implemented system; a people matching function that generates a match comprising a first person and a third person, wherein the match is generated based, at least in part, on an inference from a plurality of usage behaviors, wherein one of the plurality of usage behaviors is the first person using the relationship altering function to explicitly alter the computer-implemented directionally distinct relationship between the first person and the second person; and a computer implemented explanatory function that delivers a reason for the match to the first person, wherein the reason comprises one of the plurality of usage behaviors. 12. The system of claim 8 , further comprising: the inference, wherein the inference is of a level of mutual interest, wherein the level of mutual interest is based on access behaviors by the first person with respect to computer-implemented objects that contain content authored by the second person. | 0.5 |
8,635,180 | 16 | 18 | 16. A dual hash method for use with a pattern search engine, comprising: using said pattern search engine comprising a programmable state machine comprising a balanced routing table search (BaRT)-based finite state machine (BFSM), said search engine comprising two engines: a transition side and a default side; said BFSM being implemented in hardware, or a combination of hardware and software; having an initial rule bank, a default rule bank and a transition rule bank, each said rule having a test portion to determine if there is a match to a current rule, and a result portion which defines the next state targeted by said rule to store default rules and dual hash rules that apply to a pattern context search in a said default rule bank; storing transition rules that apply to a pattern context search in a transition rule bank; and determining a winning rule by prioritizing between a dual hash rule read from said default rule bank and a transition rule read from said transition rule bank; said transition rules having a higher priority than the rules on said default side, which is used for said dual hash; and when there is no match on either one of said default rules or said transition rules, said search engine reverts to said initial state; said dual hash being used (1) for any state for which input values covered by said transition rules are a super-set of said input values covered by said default rules; (2) wherein previous coverage can also be enforced by adding the missing uncovered input values of one or more default rules to a given state; and (3) wherein dual hash can always be used for anchored matching after a first character. | 16. A dual hash method for use with a pattern search engine, comprising: using said pattern search engine comprising a programmable state machine comprising a balanced routing table search (BaRT)-based finite state machine (BFSM), said search engine comprising two engines: a transition side and a default side; said BFSM being implemented in hardware, or a combination of hardware and software; having an initial rule bank, a default rule bank and a transition rule bank, each said rule having a test portion to determine if there is a match to a current rule, and a result portion which defines the next state targeted by said rule to store default rules and dual hash rules that apply to a pattern context search in a said default rule bank; storing transition rules that apply to a pattern context search in a transition rule bank; and determining a winning rule by prioritizing between a dual hash rule read from said default rule bank and a transition rule read from said transition rule bank; said transition rules having a higher priority than the rules on said default side, which is used for said dual hash; and when there is no match on either one of said default rules or said transition rules, said search engine reverts to said initial state; said dual hash being used (1) for any state for which input values covered by said transition rules are a super-set of said input values covered by said default rules; (2) wherein previous coverage can also be enforced by adding the missing uncovered input values of one or more default rules to a given state; and (3) wherein dual hash can always be used for anchored matching after a first character. 18. The method according to claim 16 , wherein said dual hash lookup is utilized for any state for which input values covered by transition rules are a super-set of input values covered by default rules. | 0.702346 |
8,615,131 | 1 | 8 | 1. A method for online character recognition of Arabic text, the method comprising the procedures of: receiving handwritten Arabic text from a user in the form of handwriting strokes; sampling said handwriting strokes to acquire a sequence of two-dimensional point representations thereof, including associated temporal data; geometrically pre-processing and extracting features on said point representations; detecting delayed strokes and word-parts in said pre-processed point representations; projecting said delayed strokes onto the body of said word-parts; constructing feature vector representations for each said word-part, thereby generating an observation sequence; generating at least one word-part dictionary indexed in accordance with word features, wherein: said at least one word-part dictionary is a sub-dictionary of a dictionary that includes a set of valid words; and said at least one word-part dictionary contains words having a predetermined integer number of word-parts; and determining the word in part according to said at least one word-part dictionary with maximum probability given said observation sequence, resulting in a list of word probabilities; wherein each said word-part refers to an intra-connected portion of a word, which is bounded on each side by a minimal amount of space in the text. | 1. A method for online character recognition of Arabic text, the method comprising the procedures of: receiving handwritten Arabic text from a user in the form of handwriting strokes; sampling said handwriting strokes to acquire a sequence of two-dimensional point representations thereof, including associated temporal data; geometrically pre-processing and extracting features on said point representations; detecting delayed strokes and word-parts in said pre-processed point representations; projecting said delayed strokes onto the body of said word-parts; constructing feature vector representations for each said word-part, thereby generating an observation sequence; generating at least one word-part dictionary indexed in accordance with word features, wherein: said at least one word-part dictionary is a sub-dictionary of a dictionary that includes a set of valid words; and said at least one word-part dictionary contains words having a predetermined integer number of word-parts; and determining the word in part according to said at least one word-part dictionary with maximum probability given said observation sequence, resulting in a list of word probabilities; wherein each said word-part refers to an intra-connected portion of a word, which is bounded on each side by a minimal amount of space in the text. 8. The method according to claim 1 , wherein said procedure of detecting delayed strokes and word-parts includes: generating boundary lines around a word-part; searching for markings within the region encompassed by said boundary lines; detecting markings within said region; and determining if each of said markings is a delayed stroke associated with said word-part. | 0.734104 |
9,516,134 | 1 | 6 | 1. A method comprising: determining, by a computing device, potential members associated with a user based on an electronic mailbox associated with the user; determining a plurality of conversion rates respectively for a plurality of invitations based on a respective number of persons that joined a contact information sharing network after being sent a respective one of the plurality of invitations to join the contact information sharing network; determining, based on the plurality of conversion rates, a highest conversion rate invitation of the plurality of invitations; and sending, to at least a subset of the potential members, the highest conversion rate invitation. | 1. A method comprising: determining, by a computing device, potential members associated with a user based on an electronic mailbox associated with the user; determining a plurality of conversion rates respectively for a plurality of invitations based on a respective number of persons that joined a contact information sharing network after being sent a respective one of the plurality of invitations to join the contact information sharing network; determining, based on the plurality of conversion rates, a highest conversion rate invitation of the plurality of invitations; and sending, to at least a subset of the potential members, the highest conversion rate invitation. 6. The method of claim 1 , further comprising: designating, based on input received from the user, a set of contacts in a contact list of the user to be updated; sending, to members of the contact information sharing network associated with the set of contacts, a request to verify their respective contact information; and sending, to non-members of the contact information sharing network associated with the set of contacts, an electronic mail message asking the non-members to provide current contact information in a reply electronic mail message, wherein the electronic mail message comprises a fill-in-the-blank form. | 0.5 |
9,684,430 | 1 | 2 | 1. A method, comprising: receiving a message from a user, the message comprising linguistic content; performing a lexical analysis of the linguistic content to determine one or more tokens within the linguistic content, wherein a token comprises words or phrases of the linguistic content that are indicative of an emotion, and wherein the one or more tokens comprise either emote types or word types, the emote types triggering a higher priority emotion than emotions triggered by the presence of the word types; assigning a higher priority to any of the one or more tokens occurring at an end of the message; selecting one or more facial expressions of an avatar of the user based on the one or more tokens present in the linguistic content, the selection based on the assignment of the higher priority to any of the one or more tokens occurring at the end of the message; and displaying, on a user interface of a computing device, the avatar of the user, with the selected one or more facial expressions. | 1. A method, comprising: receiving a message from a user, the message comprising linguistic content; performing a lexical analysis of the linguistic content to determine one or more tokens within the linguistic content, wherein a token comprises words or phrases of the linguistic content that are indicative of an emotion, and wherein the one or more tokens comprise either emote types or word types, the emote types triggering a higher priority emotion than emotions triggered by the presence of the word types; assigning a higher priority to any of the one or more tokens occurring at an end of the message; selecting one or more facial expressions of an avatar of the user based on the one or more tokens present in the linguistic content, the selection based on the assignment of the higher priority to any of the one or more tokens occurring at the end of the message; and displaying, on a user interface of a computing device, the avatar of the user, with the selected one or more facial expressions. 2. The method according to claim 1 , wherein performing the lexical analysis of the linguistic content comprises determining one or more tokens that correspond to actions or gestures. | 0.639764 |
9,292,799 | 18 | 19 | 18. The system of claim 14 , wherein the system is further configured to apply a clustering algorithm comprising: collecting data representing artificial lift system failures having a common failure type into a first cluster; and determining one or more pre-failure signatures in the time-sampled data. | 18. The system of claim 14 , wherein the system is further configured to apply a clustering algorithm comprising: collecting data representing artificial lift system failures having a common failure type into a first cluster; and determining one or more pre-failure signatures in the time-sampled data. 19. The system of claim 18 , wherein the clustering algorithm further includes collecting data representing normal operation of an artificial lift system into a second cluster. | 0.5 |
8,121,838 | 12 | 18 | 12. A system for prioritizing speech recognition results from a plurality of speech recognition tasks performed by a speech recognition system, the system comprising at least one processor programmed to: access captured information captured during the plurality of speech recognition tasks, comprising accessing first captured information captured during a first speech recognition task and second captured information captured during a second speech recognition task, the first speech recognition task being performed on one or more first spoken utterances and producing a first recognized text, the second speech recognition task being performed on one or more second spoken utterances and producing a second recognized text different from the first recognized text; associate a first accuracy rating with at least one portion of the first recognized text based at least in part on the first captured information, wherein the at least one portion of the first recognized text comprises a recognized phrase output by the first speech recognition task based on the one or more first spoken utterances, and wherein the first accuracy rating associated with the at least one portion of the first recognized text is based at least in part on at least one item of information that relates to the recognized phrase but is independent of a confidence score associated with the recognized phrase and independent of confidence scores associated with a plurality of phrases in an N-best match output by the first speech recognition task, the plurality of phrases being different from the recognized phrase; associate a second accuracy rating with at least one portion of the second recognized text based at least in part on the second captured information; and display, on a display device, the at least one portion of the first recognized text and the at least one portion of the second recognized text, wherein the at least one portion of the first recognized text is presented in such a manner as to be dissociated from at least one other portion of the first recognized text and wherein at least one visual indication is provided to reflect a priority between the at least one portion of the first recognized text and the at least one portion of the second recognized text, the priority being determined based at least partially on the first and second accuracy ratings. | 12. A system for prioritizing speech recognition results from a plurality of speech recognition tasks performed by a speech recognition system, the system comprising at least one processor programmed to: access captured information captured during the plurality of speech recognition tasks, comprising accessing first captured information captured during a first speech recognition task and second captured information captured during a second speech recognition task, the first speech recognition task being performed on one or more first spoken utterances and producing a first recognized text, the second speech recognition task being performed on one or more second spoken utterances and producing a second recognized text different from the first recognized text; associate a first accuracy rating with at least one portion of the first recognized text based at least in part on the first captured information, wherein the at least one portion of the first recognized text comprises a recognized phrase output by the first speech recognition task based on the one or more first spoken utterances, and wherein the first accuracy rating associated with the at least one portion of the first recognized text is based at least in part on at least one item of information that relates to the recognized phrase but is independent of a confidence score associated with the recognized phrase and independent of confidence scores associated with a plurality of phrases in an N-best match output by the first speech recognition task, the plurality of phrases being different from the recognized phrase; associate a second accuracy rating with at least one portion of the second recognized text based at least in part on the second captured information; and display, on a display device, the at least one portion of the first recognized text and the at least one portion of the second recognized text, wherein the at least one portion of the first recognized text is presented in such a manner as to be dissociated from at least one other portion of the first recognized text and wherein at least one visual indication is provided to reflect a priority between the at least one portion of the first recognized text and the at least one portion of the second recognized text, the priority being determined based at least partially on the first and second accuracy ratings. 18. The system of claim 12 , wherein the at least one processor is further programmed to: capture the captured information during the plurality of speech recognition tasks. | 0.807175 |
7,917,457 | 14 | 15 | 14. The system of claim 10 , wherein the contextual pattern decoder engine is further configured to subdivide one of the plurality of knowledge elements using a second pattern matching at least a part of the abstract representation, to identify the subdivided knowledge element with context information in the abstract representation, and wherein the pattern classification engine is further configured to classify the subdivided knowledge element in the abstract representation as a business rule using the context information and a third pattern. | 14. The system of claim 10 , wherein the contextual pattern decoder engine is further configured to subdivide one of the plurality of knowledge elements using a second pattern matching at least a part of the abstract representation, to identify the subdivided knowledge element with context information in the abstract representation, and wherein the pattern classification engine is further configured to classify the subdivided knowledge element in the abstract representation as a business rule using the context information and a third pattern. 15. The system of claim 14 , wherein knowledge in the abstract representation can be presented in one of a plurality of formats, comprising: text, XML, graphic, one or more program language or pseudo program language. | 0.5 |
7,948,400 | 10 | 12 | 10. A method for determining utility of information for an arterial flow system, comprising: with at least one processor: receiving a request to generate valuations for the flow system; obtaining a set of segments that define the flow system; determining utility values of one or more segments of the set of segments, the utility values are a function of variances of sensor data associated with the one or more segments for monitoring the flow system, selecting sensor data to provide to a remote route planning system based on the determined utility values; receiving from the remote route planning system indications of limits on an amount of sensor data to provide to the remote route planning system; and selecting sensor data to provide to the remote route planning system comprises selecting sensor data in accordance with the limits. | 10. A method for determining utility of information for an arterial flow system, comprising: with at least one processor: receiving a request to generate valuations for the flow system; obtaining a set of segments that define the flow system; determining utility values of one or more segments of the set of segments, the utility values are a function of variances of sensor data associated with the one or more segments for monitoring the flow system, selecting sensor data to provide to a remote route planning system based on the determined utility values; receiving from the remote route planning system indications of limits on an amount of sensor data to provide to the remote route planning system; and selecting sensor data to provide to the remote route planning system comprises selecting sensor data in accordance with the limits. 12. The method of claim 10 , wherein: the method further comprises: receiving the sensor data collected by a plurality of sensors; identifying correspondence between the sensor data and the set of segments; and selecting sensor data to provide to a remote route planning system based on the determined utility values comprises filtering the sensor data based at least in part upon the relative utility values of the set of segments corresponding to the sensor data. | 0.548544 |
7,496,834 | 35 | 36 | 35. The method of claim 34 , wherein said invalid element is defined in said prescribed syntax. | 35. The method of claim 34 , wherein said invalid element is defined in said prescribed syntax. 36. The method of claim 35 , wherein said syntax is XML schema. | 0.5 |
8,972,434 | 14 | 24 | 14. A computer-implemented method for executing search requests, the method comprising: receiving from a user a search request for travel reservation information, the search request including at least one first constraint to be met by results returned by a search; selecting at least one additional constraint not included in the search request; constructing a first query based on the at least one first constraint and the at least one additional constraint such that fewer search results are obtained in response to executing the first query than would be obtained in response to executing a query constructed without the at least one additional constraint; constructing a second query based on the at least one first search constraint without the at least one additional constraint; wherein the select at least one additional constraint is performed based on an estimated execution time of the first query with the at least one additional constraint; and executing the first query to obtain first phase query results and the second query to obtain second phase query results, wherein the first phase query results and the second phase query results are non-intersecting. | 14. A computer-implemented method for executing search requests, the method comprising: receiving from a user a search request for travel reservation information, the search request including at least one first constraint to be met by results returned by a search; selecting at least one additional constraint not included in the search request; constructing a first query based on the at least one first constraint and the at least one additional constraint such that fewer search results are obtained in response to executing the first query than would be obtained in response to executing a query constructed without the at least one additional constraint; constructing a second query based on the at least one first search constraint without the at least one additional constraint; wherein the select at least one additional constraint is performed based on an estimated execution time of the first query with the at least one additional constraint; and executing the first query to obtain first phase query results and the second query to obtain second phase query results, wherein the first phase query results and the second phase query results are non-intersecting. 24. The computer-implemented method of claim 14 , further comprising presenting to the user a summary of the second phase query results without presenting the second phase query results. | 0.805846 |
9,414,022 | 10 | 11 | 10. A method, comprising: generating, by a computing device, first extensible markup language (XML) content based on first encoded video, the first encoded video comprising video data that is expected to be formatted according to a first version of a protocol or a multimedia format; validating the first XML content according to one or more constraints of the first version of the protocol or the multimedia format on the video data, resulting in validated content that adheres to the one or more constraints; generating second XML content based on second encoded video; and validating, based on the validated content, the second XML content. | 10. A method, comprising: generating, by a computing device, first extensible markup language (XML) content based on first encoded video, the first encoded video comprising video data that is expected to be formatted according to a first version of a protocol or a multimedia format; validating the first XML content according to one or more constraints of the first version of the protocol or the multimedia format on the video data, resulting in validated content that adheres to the one or more constraints; generating second XML content based on second encoded video; and validating, based on the validated content, the second XML content. 11. The method of claim 10 , wherein the one or more constraints comprise at least one of a data value constraint and a co-occurrence constraint. | 0.700413 |
9,881,036 | 1 | 4 | 1. A computer program product for avoiding double counting of mapped database data, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising instructions to: receive a report definition from a data management system, wherein the report definition comprises a request to obtain information from at least two datasets, and wherein the report definition specifies a field in the at least two datasets for deduplication; detect a fact-less fact table defining many-to-many relationships between at least two datasets; generate automatically, a query plan with layered sub-queries against the at least two datasets, wherein the query plan includes instructions to: join the at least two datasets with the fact-less fact table to provide tabular data, partition the tabular data using the fact-less fact table to provide partitioned tabular data, normalize the partitioned tabular data using a conditional selection operation to provide normalized tabular data, wherein the conditional selection operation removes duplicates in the field specified by the report definition, and group and summarize the normalized tabular data to provide summarized tabular data; and execute the query plan comprising the layered sub-queries to provide query results corresponding to the report definition. | 1. A computer program product for avoiding double counting of mapped database data, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising instructions to: receive a report definition from a data management system, wherein the report definition comprises a request to obtain information from at least two datasets, and wherein the report definition specifies a field in the at least two datasets for deduplication; detect a fact-less fact table defining many-to-many relationships between at least two datasets; generate automatically, a query plan with layered sub-queries against the at least two datasets, wherein the query plan includes instructions to: join the at least two datasets with the fact-less fact table to provide tabular data, partition the tabular data using the fact-less fact table to provide partitioned tabular data, normalize the partitioned tabular data using a conditional selection operation to provide normalized tabular data, wherein the conditional selection operation removes duplicates in the field specified by the report definition, and group and summarize the normalized tabular data to provide summarized tabular data; and execute the query plan comprising the layered sub-queries to provide query results corresponding to the report definition. 4. The computer program product of claim 1 , wherein the program instructions comprise instructions to independently accumulate a summarization item by aggregating a column in the normalized tabular data. | 0.662252 |
8,527,269 | 15 | 16 | 15. A computer program product for analyzing conversational data, the computer program product comprising a non-transitory computer-readable medium containing instructions, the instructions executable by one or more processors for: receiving first conversational data that is produced by an entity, the conversational data received from a source that is associated with the entity, the entity comprising a category of persons; identifying a first set of lexical features from the first conversational data, the first set of lexical features comprising groups of one or more words from the first conversational data; reducing the first set of lexical features based on a frequency of lexical features in the first conversational data and also based on overlaps between lexical features in the first set and lexical features in the corpus; generating a first language map based on the reduced set of lexical features; and storing the first language map into the corpus in association with the entity. | 15. A computer program product for analyzing conversational data, the computer program product comprising a non-transitory computer-readable medium containing instructions, the instructions executable by one or more processors for: receiving first conversational data that is produced by an entity, the conversational data received from a source that is associated with the entity, the entity comprising a category of persons; identifying a first set of lexical features from the first conversational data, the first set of lexical features comprising groups of one or more words from the first conversational data; reducing the first set of lexical features based on a frequency of lexical features in the first conversational data and also based on overlaps between lexical features in the first set and lexical features in the corpus; generating a first language map based on the reduced set of lexical features; and storing the first language map into the corpus in association with the entity. 16. The computer program product of claim 15 , the instructions further executable by the one or more processors for: receiving second conversational data that is produced by an unknown entity; identifying a second set of lexical features from the second conversational data; generating a second language map based on the second set of lexical features; computing confidence scores for a plurality of training language maps in the corpus by comparing the second language map to the corpus; and identifying the entity associated with the language map having the highest confidence score as the entity of the second conversational data. | 0.5 |
7,555,743 | 18 | 23 | 18. A method of developing one or more application programs in operative communication to manage a network including one or more servers, wherein at least one application program is associated with each server, the method including the steps: a) defining one or more managed objects associated with the network in an object-oriented resource definition language and storing the definition of the one or more managed objects in one or more resource definition language files, wherein the definition of the one or more managed objects is based on an existing design and hierarchical structure of the network, wherein parent-child relationships between the one or more managed objects are identified in the one or more resource definition language files using the object-oriented resource definition language to define the one or more managed objects in relation to the hierarchical structure of the network; b) providing one or more data models with information associated with the one or more managed objects; c) creating one or more network management forum definition files with mapping information between the one or more data models and the one or more managed objects; d) converting the one or more data models into the object-oriented resource definition language and storing the converted information in the one or more resource definition language files; e) parsing the one or more resource definition language files to ensure conformity with the object-oriented resource definition language and creating an intermediate representation of the network from the one or more conforming resource definition language files, wherein the intermediate representation of the network created in the parsing step includes a parse tree; f) processing the parse tree to form one or more programming language classes, wherein the one or more programming language classes formed include at least one of one or more system classes, one or more module classes, one or more managed object classes, and one or more composite attribute classes; g) providing a reusable asset center framework to facilitate development of the one or more application programs, the reusable asset center including an SNMP agent framework that provides SNMP interface functionality to at least one of the one or more application programs wherein the SNMP agent framework includes an SNMP table management object framework class that converts SNMP requests to managed object framework commands and an SNMP table class that includes procedures for accessing and changing data in tables; and h) building the one or more application programs from at least the one or more programming language classes and the reusable asset framework. | 18. A method of developing one or more application programs in operative communication to manage a network including one or more servers, wherein at least one application program is associated with each server, the method including the steps: a) defining one or more managed objects associated with the network in an object-oriented resource definition language and storing the definition of the one or more managed objects in one or more resource definition language files, wherein the definition of the one or more managed objects is based on an existing design and hierarchical structure of the network, wherein parent-child relationships between the one or more managed objects are identified in the one or more resource definition language files using the object-oriented resource definition language to define the one or more managed objects in relation to the hierarchical structure of the network; b) providing one or more data models with information associated with the one or more managed objects; c) creating one or more network management forum definition files with mapping information between the one or more data models and the one or more managed objects; d) converting the one or more data models into the object-oriented resource definition language and storing the converted information in the one or more resource definition language files; e) parsing the one or more resource definition language files to ensure conformity with the object-oriented resource definition language and creating an intermediate representation of the network from the one or more conforming resource definition language files, wherein the intermediate representation of the network created in the parsing step includes a parse tree; f) processing the parse tree to form one or more programming language classes, wherein the one or more programming language classes formed include at least one of one or more system classes, one or more module classes, one or more managed object classes, and one or more composite attribute classes; g) providing a reusable asset center framework to facilitate development of the one or more application programs, the reusable asset center including an SNMP agent framework that provides SNMP interface functionality to at least one of the one or more application programs wherein the SNMP agent framework includes an SNMP table management object framework class that converts SNMP requests to managed object framework commands and an SNMP table class that includes procedures for accessing and changing data in tables; and h) building the one or more application programs from at least the one or more programming language classes and the reusable asset framework. 23. The method as set forth in claim 18 wherein the resource definition language is managed object definition language. | 0.825 |
8,869,291 | 17 | 21 | 17. A method for generating and storing a Portable Document Format (PDF) document within a network, the network including a client, and a plurality of storage locations, the method comprising: generating a PDF document; acquiring policy information for the PDF document, wherein the policy information includes a content-filtering policy, a security policy and a storage location policy for the PDF document; determining a portion of the PDF document that is subject to security, based on the content-filtering policy included in the policy information; determining a storage location for storage of the PDF document from among the plurality of storage locations, based on the storage location policy included in the policy information; applying security to the determined portion of the PDF document based on the security policy included in the policy information; and storing the PDF document including the portion of the PDF document to which security is applied on the determined storage location. | 17. A method for generating and storing a Portable Document Format (PDF) document within a network, the network including a client, and a plurality of storage locations, the method comprising: generating a PDF document; acquiring policy information for the PDF document, wherein the policy information includes a content-filtering policy, a security policy and a storage location policy for the PDF document; determining a portion of the PDF document that is subject to security, based on the content-filtering policy included in the policy information; determining a storage location for storage of the PDF document from among the plurality of storage locations, based on the storage location policy included in the policy information; applying security to the determined portion of the PDF document based on the security policy included in the policy information; and storing the PDF document including the portion of the PDF document to which security is applied on the determined storage location. 21. A method according to claim 17 , wherein the policy information further includes authentication information for the PDF document, and the storing step stores the authentication information included in the policy information, together with the PDF document, on the identified storage location. | 0.5 |
9,639,696 | 2 | 3 | 2. The method of by claim 1 wherein the determining is performed by a trained classifier. | 2. The method of by claim 1 wherein the determining is performed by a trained classifier. 3. The method of claim 2 wherein the trained classifier is trained using the suspect terms from the provided database. | 0.5 |
9,997,085 | 1 | 4 | 1. A computer-implemented method, comprising: determining, by a processor, a cognitive load of a plurality of words comprised in a rapid serial visual presentation by using at least one metric, the cognitive load being determined on any of a word level and a word sequence level; calculating, by the processor, a variable presentation rate for the plurality of words based on the cognitive load; and controlling, by the processor, a displaying of the plurality of words on a display device in accordance with the calculated variable presentation rate based on a threshold by temporarily reducing the variable presentation rate responsive to the cognitive load being above the threshold. | 1. A computer-implemented method, comprising: determining, by a processor, a cognitive load of a plurality of words comprised in a rapid serial visual presentation by using at least one metric, the cognitive load being determined on any of a word level and a word sequence level; calculating, by the processor, a variable presentation rate for the plurality of words based on the cognitive load; and controlling, by the processor, a displaying of the plurality of words on a display device in accordance with the calculated variable presentation rate based on a threshold by temporarily reducing the variable presentation rate responsive to the cognitive load being above the threshold. 4. The computer-implemented method of claim 1 , wherein the at least one metric comprises a statistical-language-model-based metric for identifying any of the plurality of words and word sequences formed thereby having a respective low probability of occurrence responsive to a comparison of the plurality of words and the word sequences against a statistical language model. | 0.5 |
8,930,182 | 9 | 10 | 9. A method for reconstructing a voice transformation, comprising: receiving an output speech of a voice transformation system wherein the output speech is a source speech of a person which was transformed to sound as if the source speech were spoken by a different person, wherein the output speech comprises encoded information on the transformation parameters using steganography; extracting the information on the transformation parameters; and carrying out an inverse transformation of the output speech to obtain an approximation of the source speech, wherein at least one of the receiving, the extracting and the carrying out is performed by a processor. | 9. A method for reconstructing a voice transformation, comprising: receiving an output speech of a voice transformation system wherein the output speech is a source speech of a person which was transformed to sound as if the source speech were spoken by a different person, wherein the output speech comprises encoded information on the transformation parameters using steganography; extracting the information on the transformation parameters; and carrying out an inverse transformation of the output speech to obtain an approximation of the source speech, wherein at least one of the receiving, the extracting and the carrying out is performed by a processor. 10. The method as claimed in claim 9 , including: detecting the encoded information in the received output speech; and issuing an alert that the received output speech is transformed speech. | 0.63035 |
10,032,118 | 11 | 15 | 11. A media processor, comprising: a memory that stores instructions; and a processing system including a processor coupled to the memory, wherein execution of the instructions facilitates performance of operations, the operations comprising: receiving a selection to present a media program as a selected media program; submitting to a device a request for a subset of blogs from a plurality of blogs that are relevant to the selected media program, wherein the device identifies the subset of blogs by performing operations comprising: obtaining, through a search application programming interface, an initial set of annotated blogs, wherein the initial set of annotated blogs are annotated as being either relevant to a selected media program or not relevant to the selected media program; training a first classifier based on the initial set of annotated blogs to generate a trained first classifier; applying the trained first classifier to unannotated blogs from the plurality of blogs to generate a first set of features associating the selected media program with unannotated blogs; training a second classifier according to the first set of features generated by the trained first classifier to generate a trained second classifier; and applying the trained second classifier to the plurality of blogs to identify subsets of blogs relevant to the selected media program as selected blogs; performing a sentiment analysis on the selected blogs to determine a trend based on pattern recognition, wherein the trend is related to the selected media program; concurrently presenting a graphical user interface that presents the selected blogs, the trend, and the selected media program; subdividing the subset of blogs into blog subgroups comprising one of blogs favorable to the media program or blogs unfavorable to the media program; and selecting scheduled media programming according to the subset of blogs. | 11. A media processor, comprising: a memory that stores instructions; and a processing system including a processor coupled to the memory, wherein execution of the instructions facilitates performance of operations, the operations comprising: receiving a selection to present a media program as a selected media program; submitting to a device a request for a subset of blogs from a plurality of blogs that are relevant to the selected media program, wherein the device identifies the subset of blogs by performing operations comprising: obtaining, through a search application programming interface, an initial set of annotated blogs, wherein the initial set of annotated blogs are annotated as being either relevant to a selected media program or not relevant to the selected media program; training a first classifier based on the initial set of annotated blogs to generate a trained first classifier; applying the trained first classifier to unannotated blogs from the plurality of blogs to generate a first set of features associating the selected media program with unannotated blogs; training a second classifier according to the first set of features generated by the trained first classifier to generate a trained second classifier; and applying the trained second classifier to the plurality of blogs to identify subsets of blogs relevant to the selected media program as selected blogs; performing a sentiment analysis on the selected blogs to determine a trend based on pattern recognition, wherein the trend is related to the selected media program; concurrently presenting a graphical user interface that presents the selected blogs, the trend, and the selected media program; subdividing the subset of blogs into blog subgroups comprising one of blogs favorable to the media program or blogs unfavorable to the media program; and selecting scheduled media programming according to the subset of blogs. 15. The media processor of claim 11 , wherein the operations further comprise: receiving a blog message; and submitting the blog message for posting in a blog of social networks. | 0.66791 |
9,286,414 | 9 | 16 | 9. A computer-implemented data description and data delivery method, comprising: receiving, at a server computer via a network, an annotation of a data source, wherein the annotation comprises an association of a first global term with data for the data source; storing information on a data store, the information including descriptions of the data source, definitions of the first global term, and the annotation; receiving a client query to be run against the data store, the client query requesting an identification of data sources to which a respective vocabulary has been applied; determining, by the server computer, based on information stored in the data store, and in response to the client query, whether the respective vocabulary has been applied to the data source to annotate the data source in accordance with a set of global terms of the respective vocabulary; and providing, by the server computer, a second global term used for data source annotation in response to a query from a client device for global terms related to the first global term. | 9. A computer-implemented data description and data delivery method, comprising: receiving, at a server computer via a network, an annotation of a data source, wherein the annotation comprises an association of a first global term with data for the data source; storing information on a data store, the information including descriptions of the data source, definitions of the first global term, and the annotation; receiving a client query to be run against the data store, the client query requesting an identification of data sources to which a respective vocabulary has been applied; determining, by the server computer, based on information stored in the data store, and in response to the client query, whether the respective vocabulary has been applied to the data source to annotate the data source in accordance with a set of global terms of the respective vocabulary; and providing, by the server computer, a second global term used for data source annotation in response to a query from a client device for global terms related to the first global term. 16. The system of claim 9 , wherein the first global term conveys meanings about the data for the respective data source, wherein the meanings are recognized by at least two different clients. | 0.571429 |
7,640,037 | 32 | 33 | 32. The system of claim 31 , wherein the mobile handheld device comprises a cellular phone and the professional information comprises business related information with the menu listing the different types of business related information that can be captured as a digital image using the camera. | 32. The system of claim 31 , wherein the mobile handheld device comprises a cellular phone and the professional information comprises business related information with the menu listing the different types of business related information that can be captured as a digital image using the camera. 33. The system of claim 32 , wherein the business related information that is listed as entries on the menu includes a business card, a receipt, a form, a printed document, handwritten information, a whiteboard, and graphic indicia. | 0.5 |
7,991,799 | 19 | 20 | 19. The computer program product of claim 13 , wherein the computer-usable medium further comprises computer-usable program code that associates each XML processing instruction with at least two portions of template code, wherein each portion of template code is in a different programming language. | 19. The computer program product of claim 13 , wherein the computer-usable medium further comprises computer-usable program code that associates each XML processing instruction with at least two portions of template code, wherein each portion of template code is in a different programming language. 20. The computer program product of claim 19 , wherein the computer-usable program code that compiles further comprises computer-usable program code that replaces each XML processing instruction within the execution plan with the template, associated with the XML processing instruction, that is coded in a selected programming language in which the schema specific parser is to be created. | 0.5 |
8,433,575 | 1 | 2 | 1. A method for augmenting an audio signal comprising acts of: receiving an audio signal, extracting features from said audio signal, generating a time ordered table of dramatic parameters according to the extracted features, wherein the dramatic parameters include mood, changes of pace and incidents, selecting a story template at least in part in dependence on said table of dramatic parameters, wherein said story template comprises dramatic parameter data related to a narrative story structure, obtaining media fragments at least in part in dependence on the table of dramatic parameters by matching the dramatic parameters of the selected story template with those of the media fragments, and outputting said media fragments in tandem with said audio signal. | 1. A method for augmenting an audio signal comprising acts of: receiving an audio signal, extracting features from said audio signal, generating a time ordered table of dramatic parameters according to the extracted features, wherein the dramatic parameters include mood, changes of pace and incidents, selecting a story template at least in part in dependence on said table of dramatic parameters, wherein said story template comprises dramatic parameter data related to a narrative story structure, obtaining media fragments at least in part in dependence on the table of dramatic parameters by matching the dramatic parameters of the selected story template with those of the media fragments, and outputting said media fragments in tandem with said audio signal. 2. The method according to claim 1 , wherein said features extracted from said audio signal include one or more of tempo, key, volume. | 0.814917 |
8,612,207 | 11 | 13 | 11. A text mining method comprising: a step of analyzing a document from a storage unit that stores a set of documents as a text mining object and obtaining a sentence structure representing a dependency among words; a step of performing predetermined modification operation, including at least change in connection of branches in a graph structure, of a partial structure of the sentence structure and generating, using a computer, a similar structure having patterns with a similar meaning; a step of using the generated similar structures as an equivalent class of the partial structure on the generation source and detecting the pattern, wherein the step of generating the similar structure comprises: a step of performing parallel modification of the sentence structure, the parallel modification being structure modification including new branch generation for a particular one of nodes corresponding to the words put in a parallel relationship in the sentence structure so that the particular one is connected to each node connected by a branch from the node put in the parallel relationship for the particular one said step of performing parallel modification of the sentence structure generating the similar structure; a step of generating a plurality of new partial structures of the sentence structure from the partial structure and the similar structure; a step of performing non-directional branching of the directional branch of the sentence structure and the plurality of new partial structures to produce new similar structures; a step of replacing a synonym in the sentence structure and the plurality of new partial structures by referring to a synonym dictionary to produce new similar structures; and a step of performing non-ordering of ordering trees in the sentence structure and the plurality of new partial structures to produce new similar structures, and thereby the step of generating the similar structure generating the new similar structures of the sentence structure and setting the new similar structures as an equivalent class of the plurality of new partial structures. | 11. A text mining method comprising: a step of analyzing a document from a storage unit that stores a set of documents as a text mining object and obtaining a sentence structure representing a dependency among words; a step of performing predetermined modification operation, including at least change in connection of branches in a graph structure, of a partial structure of the sentence structure and generating, using a computer, a similar structure having patterns with a similar meaning; a step of using the generated similar structures as an equivalent class of the partial structure on the generation source and detecting the pattern, wherein the step of generating the similar structure comprises: a step of performing parallel modification of the sentence structure, the parallel modification being structure modification including new branch generation for a particular one of nodes corresponding to the words put in a parallel relationship in the sentence structure so that the particular one is connected to each node connected by a branch from the node put in the parallel relationship for the particular one said step of performing parallel modification of the sentence structure generating the similar structure; a step of generating a plurality of new partial structures of the sentence structure from the partial structure and the similar structure; a step of performing non-directional branching of the directional branch of the sentence structure and the plurality of new partial structures to produce new similar structures; a step of replacing a synonym in the sentence structure and the plurality of new partial structures by referring to a synonym dictionary to produce new similar structures; and a step of performing non-ordering of ordering trees in the sentence structure and the plurality of new partial structures to produce new similar structures, and thereby the step of generating the similar structure generating the new similar structures of the sentence structure and setting the new similar structures as an equivalent class of the plurality of new partial structures. 13. A text mining method according to claim 11 , further comprising: a step of adjusting the operation so that a user determines how similar patterns are identical and detects the pattern. | 0.601695 |
7,580,909 | 3 | 7 | 3. The system of claim 1 , the plurality of hypotheses being displayed as colored nodes within a belief network, and the respective confidence values being represented as at least one of the brightness, hue, and saturation of the color of the node. | 3. The system of claim 1 , the plurality of hypotheses being displayed as colored nodes within a belief network, and the respective confidence values being represented as at least one of the brightness, hue, and saturation of the color of the node. 7. The system of claim 3 , the plurality of hypotheses comprising supporting, detracting, and neutral hypotheses, supporting hypotheses being associated with a first color, detracting hypotheses being associated with a second color, and neutral hypotheses being associated with a third color. | 0.5 |
9,501,457 | 16 | 17 | 16. The non-transitory computer storage medium of claim 15 , wherein the operation of inserting script within said markup language includes script for redefining the at least one pointer for each object of the plurality of user specific objects and non-user specific objects associated with an object that has been edited as the result of the interpreted user initiated event. | 16. The non-transitory computer storage medium of claim 15 , wherein the operation of inserting script within said markup language includes script for redefining the at least one pointer for each object of the plurality of user specific objects and non-user specific objects associated with an object that has been edited as the result of the interpreted user initiated event. 17. The non-transitory computer storage medium of claim 16 , wherein the operation of inserting script within said markup language includes script for redrawing each object having re-established coordinates in said at least one canvas element as canvas natives visible in the browser. | 0.5 |
8,612,243 | 18 | 19 | 18. The non-transitory computer readable data storage medium article of manufacture of claim 17 , wherein storing an interaction record in the community of users includes: creating a smart folder, wherein the smart folder houses the interaction record with at least one tag set definition; and indexing the interaction record and the tag set definition. | 18. The non-transitory computer readable data storage medium article of manufacture of claim 17 , wherein storing an interaction record in the community of users includes: creating a smart folder, wherein the smart folder houses the interaction record with at least one tag set definition; and indexing the interaction record and the tag set definition. 19. The non-transitory computer readable data storage medium article of manufacture of claim 18 , wherein the interaction record to be housed in the smart folder conforms to a predetermined tag set definition to impose structure upon the interaction record before it is added to the community. | 0.5 |
8,224,642 | 14 | 15 | 14. A computer program product comprising a computer readable storage medium encoded with program code usable to control operation of a computer system, the program code including: program code for computing, for each language in a plurality of candidate languages, a document score for a test document using a language model associated with that language; program code for selecting a most likely language from the plurality of candidate languages based on the document scores for each language; program code for determining whether the test document is in the most likely language or in no language, wherein the determination is based at least in part on comparing the document scores for one or more impostor languages in an impostor set associated with the most likely language to an impostor profile for the most likely language, wherein the impostor profile for the most likely language includes a parameter set consisting of values characterizing a score distribution expected for documents in the most likely language when scored using the respective language models of the one or more impostor languages in the impostor set associated with the most likely language; and program code for storing, in a computer readable storage medium, language information for the test document, the language information including a result of the determination. | 14. A computer program product comprising a computer readable storage medium encoded with program code usable to control operation of a computer system, the program code including: program code for computing, for each language in a plurality of candidate languages, a document score for a test document using a language model associated with that language; program code for selecting a most likely language from the plurality of candidate languages based on the document scores for each language; program code for determining whether the test document is in the most likely language or in no language, wherein the determination is based at least in part on comparing the document scores for one or more impostor languages in an impostor set associated with the most likely language to an impostor profile for the most likely language, wherein the impostor profile for the most likely language includes a parameter set consisting of values characterizing a score distribution expected for documents in the most likely language when scored using the respective language models of the one or more impostor languages in the impostor set associated with the most likely language; and program code for storing, in a computer readable storage medium, language information for the test document, the language information including a result of the determination. 15. The computer program product of claim 14 wherein the language model for each language is a bigram based language model. | 0.790816 |
7,567,947 | 4 | 10 | 4. A system for creating a rule relating to semiconductor testing, comprising: means for providing at least one parameter for a rule relating to semiconductor testing; wherein said at least one parameter defines a condition for actualization of said rule; and a simulator assuming whether said condition exists and simulating actualization or non actualization of said rule accordingly. | 4. A system for creating a rule relating to semiconductor testing, comprising: means for providing at least one parameter for a rule relating to semiconductor testing; wherein said at least one parameter defines a condition for actualization of said rule; and a simulator assuming whether said condition exists and simulating actualization or non actualization of said rule accordingly. 10. The system of claim 4 , further comprising means for actualizing said rule in offline production and means for analyzing actualization of said rule, wherein said simulator, said means for specifying, said means for actualizing in offline production and said means for analyzing actualization are integrated with one another. | 0.733766 |
8,065,584 | 1 | 6 | 1. A method, comprising: scrambling a first occurrence of a data word to produce a first scrambled data word; block encoding said first scrambled data word to produce a first code word; scrambling a second occurrence of said data word to produce a second scrambled data word; and block encoding said second scrambled data word to produce a second code word; wherein said second code word and said first code word are different from one another. | 1. A method, comprising: scrambling a first occurrence of a data word to produce a first scrambled data word; block encoding said first scrambled data word to produce a first code word; scrambling a second occurrence of said data word to produce a second scrambled data word; and block encoding said second scrambled data word to produce a second code word; wherein said second code word and said first code word are different from one another. 6. The method of claim 1 , comprising: transmitting the first code word and the second code word to a receiver. | 0.815 |
8,165,277 | 19 | 24 | 19. A service creation environment for creating user-requested telephony features, comprising: a computing device; and an application stored on the computing device, the application operable to: receive a plurality of instructions defining a graphical representation of an implementation of one or more telephony features for an endpoint, the graphical representation comprising a plurality of graphical elements, each graphical element representing at least a portion of a state process of the one or more telephony features; generate the graphical representation in accordance with the plurality of instructions; convert a first graphical element into a first text command; convert a second graphical element into a second text command, the first and second text commands specifying a plurality of actions of the state process; determine customized feature logic comprising the first and second text commands, the first and second text commands operable to provide the one or more telephony features for the endpoint; and communicate the customized feature logic to the endpoint for storage. | 19. A service creation environment for creating user-requested telephony features, comprising: a computing device; and an application stored on the computing device, the application operable to: receive a plurality of instructions defining a graphical representation of an implementation of one or more telephony features for an endpoint, the graphical representation comprising a plurality of graphical elements, each graphical element representing at least a portion of a state process of the one or more telephony features; generate the graphical representation in accordance with the plurality of instructions; convert a first graphical element into a first text command; convert a second graphical element into a second text command, the first and second text commands specifying a plurality of actions of the state process; determine customized feature logic comprising the first and second text commands, the first and second text commands operable to provide the one or more telephony features for the endpoint; and communicate the customized feature logic to the endpoint for storage. 24. The service creation environment of claim 19 , wherein an action of the feature logic associated with the one or more telephony features specifies an output corresponding to a particular state of the one or more telephony features. | 0.617264 |
5,384,703 | 31 | 33 | 31. An automated, computer implemented method of electronically processing a document stored in a memory of a computer, said document containing words represented by roman characters, said method comprising the steps of: a) using the computer, automatically determining a frequency of occurrence of words in the document having at least a first predetermined number of characters and not contained in a stop list that is stored in the memory of the computer; b) using the computer, automatically forming a seed list comprised of a second predetermined number of the most frequently occurring words in the document having at least said first predetermined number of characters, said seed list stored in the memory of the computer; c) using the computer, automatically forming a summary of the document comprised of regions in the document containing at least two words in said seed list, said summary stored in the memory of the computer; and d) using the computer, automatically repeating steps (a)-(c) on said summary until a length of said summary is no greater than a predetermined length, each time steps (a)-(c) are repeated, adding the words on said seed list to said stop list and reducing a value of said first predetermined number. | 31. An automated, computer implemented method of electronically processing a document stored in a memory of a computer, said document containing words represented by roman characters, said method comprising the steps of: a) using the computer, automatically determining a frequency of occurrence of words in the document having at least a first predetermined number of characters and not contained in a stop list that is stored in the memory of the computer; b) using the computer, automatically forming a seed list comprised of a second predetermined number of the most frequently occurring words in the document having at least said first predetermined number of characters, said seed list stored in the memory of the computer; c) using the computer, automatically forming a summary of the document comprised of regions in the document containing at least two words in said seed list, said summary stored in the memory of the computer; and d) using the computer, automatically repeating steps (a)-(c) on said summary until a length of said summary is no greater than a predetermined length, each time steps (a)-(c) are repeated, adding the words on said seed list to said stop list and reducing a value of said first predetermined number. 33. The method of claim 31, further comprising using said computer, performing a word-stemming operation on words in said document prior to performing step (a). | 0.713262 |
8,494,837 | 9 | 10 | 9. A method for training a machine translation system, comprising the steps of: translating a test set from a first collection to a second collection using an existing parallel corpus stored in memory on the machine translation system; calculating a translation accuracy score for each item in the test set; comparing the translation accuracy score for each item to a desired performance score to determine whether the parallel corpus needs to be updated for that item; if the translation accuracy score for an item is equal to or greater than a desired performance score, removing that item from the test set, so as to create a test set E; using a unidirectional translation corpus, translating the test set E from the first collection to the second collection so as to create a set F in the second collection and translating the set F from the second collection back to the first collection so as to create a set E′ in the first collection, wherein differences between E and E′ are determined; computing confidence scores for a translation of each item in the test set E based on a similarity of E and E′; and adding translations to the parallel corpus based on the confidence scores. | 9. A method for training a machine translation system, comprising the steps of: translating a test set from a first collection to a second collection using an existing parallel corpus stored in memory on the machine translation system; calculating a translation accuracy score for each item in the test set; comparing the translation accuracy score for each item to a desired performance score to determine whether the parallel corpus needs to be updated for that item; if the translation accuracy score for an item is equal to or greater than a desired performance score, removing that item from the test set, so as to create a test set E; using a unidirectional translation corpus, translating the test set E from the first collection to the second collection so as to create a set F in the second collection and translating the set F from the second collection back to the first collection so as to create a set E′ in the first collection, wherein differences between E and E′ are determined; computing confidence scores for a translation of each item in the test set E based on a similarity of E and E′; and adding translations to the parallel corpus based on the confidence scores. 10. The method of claim 9 , wherein the method steps further comprise: creating a subset H of highest confidence scores; adding the translations in subset H directly to the parallel corpus; creating a subset L of lowest confidence scores; presenting subset L to human translators for correction; and adding human corrections to the parallel corpus. | 0.586698 |
7,548,491 | 9 | 11 | 9. A method for communicating with a mobile vehicle, comprising: receiving a voice command at a key fob; determining a function message based on the voice command; and sending the function message from a telematics unit to perform a requested function. | 9. A method for communicating with a mobile vehicle, comprising: receiving a voice command at a key fob; determining a function message based on the voice command; and sending the function message from a telematics unit to perform a requested function. 11. The method of claim 9 wherein the function message is sent to a vehicle communication bus to perform the requested function. | 0.851508 |
9,058,339 | 1 | 5 | 1. A system for source control in a program, the program comprising a plurality of hierarchical files for execution of a plurality of processes, the hierarchical files comprising parent files and child files, said system comprising: a graphical user interface for selection of a process of the plurality of processes by a user, the selected process including less than all of the files in the program; a computer processor for identifying files in the selected process and identifying at least one file that is a descendent of a file in the selected process; and a source control processor for locking the files in the selected process, the locking of the files in the selected process includes disallowing revisions to the files in the selected process, said source control processor locks the at least one file that is a descendent of a file in the selected process, the locking of the at least one file that is a descendent of a file in the selected process includes disallowing revisions to the at least one file that is a descendent of a file in the selected process, wherein said source control processor only locks the files in the selected process and the at least one file that is a descendent of a file in the selected process such that revisions are allowed to files not in the selected process and files that are not descendent of a file in the selected process. | 1. A system for source control in a program, the program comprising a plurality of hierarchical files for execution of a plurality of processes, the hierarchical files comprising parent files and child files, said system comprising: a graphical user interface for selection of a process of the plurality of processes by a user, the selected process including less than all of the files in the program; a computer processor for identifying files in the selected process and identifying at least one file that is a descendent of a file in the selected process; and a source control processor for locking the files in the selected process, the locking of the files in the selected process includes disallowing revisions to the files in the selected process, said source control processor locks the at least one file that is a descendent of a file in the selected process, the locking of the at least one file that is a descendent of a file in the selected process includes disallowing revisions to the at least one file that is a descendent of a file in the selected process, wherein said source control processor only locks the files in the selected process and the at least one file that is a descendent of a file in the selected process such that revisions are allowed to files not in the selected process and files that are not descendent of a file in the selected process. 5. The system according to claim 1 , wherein said computer processor identifies at least one file that shares a parent with a file in the selected process. | 0.79765 |
9,785,850 | 1 | 14 | 1. A method of communicating adjustments for relative positioning of a handheld electronic device with a camera, and a document, the method comprising: continuously receiving, at a processor of the handheld electronic device, a plurality of images of characters on the document; dynamically detecting edges of the characters while continuously receiving the images; thickening the edges of the characters; thresholding the edges of the characters; determining a contour of the characters; displaying, using a display of the handheld camera, the edges of the characters; determining an average font height of the characters using the edges of the characters; and determining relative positioning information about positioning of the handheld electronic device relative to the document. | 1. A method of communicating adjustments for relative positioning of a handheld electronic device with a camera, and a document, the method comprising: continuously receiving, at a processor of the handheld electronic device, a plurality of images of characters on the document; dynamically detecting edges of the characters while continuously receiving the images; thickening the edges of the characters; thresholding the edges of the characters; determining a contour of the characters; displaying, using a display of the handheld camera, the edges of the characters; determining an average font height of the characters using the edges of the characters; and determining relative positioning information about positioning of the handheld electronic device relative to the document. 14. The method of claim 1 , wherein thresholding includes using an assumption of a foreground and background in the images. | 0.930034 |
10,127,589 | 14 | 16 | 14. The method of claim 13 , further comprising receiving the candidate image that depicts the portion of the candidate specimen of the product exhibiting the reference detail by which the authenticity criterion is fulfillable. | 14. The method of claim 13 , further comprising receiving the candidate image that depicts the portion of the candidate specimen of the product exhibiting the reference detail by which the authenticity criterion is fulfillable. 16. The method of claim 14 , further comprising causing the user device to display the candidate image that depicts the portion of the candidate specimen in a window in which the reference image that depicts the portion of the reference specimen is also displayed, the portion of the reference specimen and the portion of the candidate specimen both exhibiting the reference detail and fulfilling the authenticity criterion mapped to the identifier of the product. | 0.5 |
8,769,486 | 1 | 4 | 1. A computer-implemented method comprising: receiving a specification of a statically typed first interface to a first function, the first interface including a specification of a data type of a parameter of the first function; analyzing the specification of the statically typed first interface to the first function to determine a function signature; determining, based on the analyzing, the function signature; identifying a second function using the function signature, the second function corresponding to the specification of the statically typed first interface to the first function, the second function written using a dynamically typed language; and generating an implementation of the first function that invokes the second function through a dynamically typed function specification associated with the second function. | 1. A computer-implemented method comprising: receiving a specification of a statically typed first interface to a first function, the first interface including a specification of a data type of a parameter of the first function; analyzing the specification of the statically typed first interface to the first function to determine a function signature; determining, based on the analyzing, the function signature; identifying a second function using the function signature, the second function corresponding to the specification of the statically typed first interface to the first function, the second function written using a dynamically typed language; and generating an implementation of the first function that invokes the second function through a dynamically typed function specification associated with the second function. 4. The method of claim 1 , wherein the first function outputs a first return value and the second function outputs a second return value. | 0.770903 |
10,032,455 | 1 | 8 | 1. A method of training an embedded speech recognizer on an electronic device in a distributed speech recognition system comprising the electronic device and a network device having a remote speech recognizer remote from the electronic device, the method comprising: recognizing, by the embedded speech recognizer, at least a first portion of input audio received by the electronic device to generate a local speech recognition result, wherein the recognizing is performed, at least in part, using a command grammar activated by the embedded speech recognizer in response to recognizing a command; sending, to the network device, at least a second portion of input audio received by the electronic device; receiving, from the network device, a remote speech recognition result corresponding to the at least a second portion of the input audio; performing, at the electronic device, a pronunciation alignment of the local speech recognition result and the remote speech recognition result; identifying, based on the aligned local and remote speech recognition results, a portion of the remote speech recognition result corresponding to a low-confidence part of the local speech recognition result; and training the embedded speech recognizer based, at least in part, on the remote speech recognition result, wherein training the embedded speech recognizer comprises adding the identified portion of the remote speech recognition result to the command grammar used by the embedded speech recognizer to recognize the at least a portion of the input audio. | 1. A method of training an embedded speech recognizer on an electronic device in a distributed speech recognition system comprising the electronic device and a network device having a remote speech recognizer remote from the electronic device, the method comprising: recognizing, by the embedded speech recognizer, at least a first portion of input audio received by the electronic device to generate a local speech recognition result, wherein the recognizing is performed, at least in part, using a command grammar activated by the embedded speech recognizer in response to recognizing a command; sending, to the network device, at least a second portion of input audio received by the electronic device; receiving, from the network device, a remote speech recognition result corresponding to the at least a second portion of the input audio; performing, at the electronic device, a pronunciation alignment of the local speech recognition result and the remote speech recognition result; identifying, based on the aligned local and remote speech recognition results, a portion of the remote speech recognition result corresponding to a low-confidence part of the local speech recognition result; and training the embedded speech recognizer based, at least in part, on the remote speech recognition result, wherein training the embedded speech recognizer comprises adding the identified portion of the remote speech recognition result to the command grammar used by the embedded speech recognizer to recognize the at least a portion of the input audio. 8. The method of claim 1 , further comprising: storing one or more statistics detailing a usage of pronunciations or grammatical forms spoken by a user of the electronic device, wherein training the embedded speech recognizer further comprises training the embedded speech recognizer based, at least in part, on the one or more statistics. | 0.750368 |
8,543,715 | 5 | 6 | 5. The method of claim 4 , wherein the responding comprises: incrementing a redirect counter value in response to receiving the redirect request; comparing the incremented redirect counter value with the determined redirect limit; and ignoring the redirect request when the redirect counter value exceeds the determined redirect limit. | 5. The method of claim 4 , wherein the responding comprises: incrementing a redirect counter value in response to receiving the redirect request; comparing the incremented redirect counter value with the determined redirect limit; and ignoring the redirect request when the redirect counter value exceeds the determined redirect limit. 6. The method of claim 5 , further comprising: transmitting an error code to the third-party content delivery system when the redirect counter value exceeds the determined redirect limit. | 0.5 |
10,089,765 | 1 | 4 | 1. A method performed by a computing device to display an output comprising an image generated based on an input of a selected text from sources, wherein the sources comprise at least one of books, newspapers, songs, letters, documents, speeches or any written item, the method comprising; selecting, by the computing device, a source from among the sources; selecting, by the computing device, the text from among the selected source; defining, by the computing device, expectations for the image; building, by the computing device, a transformed text from the selected text; dividing, by the computing device, the transformed text into slides of text; generating, by the computing device, man objects for respective slides of text, each of the main objects being a graphical element that represents the respective slides of text; defining, by the computing device, a shape and properties of respective main objects; defining, by the computing device, mathematical functions for relating the properties of the respective main objects to the respective slides of text; obtaining, by the computing device, numerical values for the respective slides of text based on the mathematical functions and the properties of the respective main objects, wherein the obtained numerical values include magnitude of the respective slides of text and an angle of the respective slides of text; building, by the computing device, scripts for generating the image, based on the shape of the respective main objects and the numerical values for the respective slides of text; generating, by the computing device, the image on a polar coordinate system in accordance with the scripts; displaying, by the computing device, the image generated; displaying, by the computing device, the output that comprises the image generated upon the defined expectations for the generated image being fulfilled; and when the defined expectations are not fulfilled, performing, by the computing device, interactive processes until the defined expectations for the generated images are fulfilled. | 1. A method performed by a computing device to display an output comprising an image generated based on an input of a selected text from sources, wherein the sources comprise at least one of books, newspapers, songs, letters, documents, speeches or any written item, the method comprising; selecting, by the computing device, a source from among the sources; selecting, by the computing device, the text from among the selected source; defining, by the computing device, expectations for the image; building, by the computing device, a transformed text from the selected text; dividing, by the computing device, the transformed text into slides of text; generating, by the computing device, man objects for respective slides of text, each of the main objects being a graphical element that represents the respective slides of text; defining, by the computing device, a shape and properties of respective main objects; defining, by the computing device, mathematical functions for relating the properties of the respective main objects to the respective slides of text; obtaining, by the computing device, numerical values for the respective slides of text based on the mathematical functions and the properties of the respective main objects, wherein the obtained numerical values include magnitude of the respective slides of text and an angle of the respective slides of text; building, by the computing device, scripts for generating the image, based on the shape of the respective main objects and the numerical values for the respective slides of text; generating, by the computing device, the image on a polar coordinate system in accordance with the scripts; displaying, by the computing device, the image generated; displaying, by the computing device, the output that comprises the image generated upon the defined expectations for the generated image being fulfilled; and when the defined expectations are not fulfilled, performing, by the computing device, interactive processes until the defined expectations for the generated images are fulfilled. 4. The method of claim 1 , wherein the output has attributes, wherein the attributes comprise at least one of color, temperature or any other attributes to be seen, heard, smelled or felt. | 0.889412 |
7,558,408 | 10 | 11 | 10. The system of claim 1 , wherein the programming instructions comprise instructions for receiving data management editing from the user regarding statistical thresholds utilized in the comparing by the face recognition module. | 10. The system of claim 1 , wherein the programming instructions comprise instructions for receiving data management editing from the user regarding statistical thresholds utilized in the comparing by the face recognition module. 11. The system of claim 10 , wherein the programming instructions further comprise instructions for receiving data management editing from the user regarding automated learning or adaptive recognition enhancement processes, or both. | 0.5 |
9,122,727 | 18 | 31 | 18. A system including memory and one or more processors operable to execute instructions, stored in the memory, comprising instructions to perform the operations of: identifying a respective ordered list of search result documents for each query in a plurality of queries; identifying: a given query in the plurality of queries; a first and second grouping in the ordered list for the given query; and a first and second grouping in the ordered list for each of the remaining queries in the plurality of queries; determining non-overlap scores between the given query and each of the remaining queries in the plurality of queries, wherein the non-overlap scores measure dissimilarities between the search result documents within the first grouping in the ordered list for the given query and the first grouping in the ordered list for each of the remaining queries in the plurality of queries; selecting one or more candidate queries from the remaining queries in the plurality of queries based on the non-overlap scores; determining overlap scores between the given query and each of the candidate queries, wherein the overlap scores measure similarities between the search result documents within the second grouping in the ordered list for the given query and the second grouping in the ordered list for each of the candidate queries; selecting one or more related queries from the candidate queries based on the overlap scores; and storing data associating the related queries with the given query. | 18. A system including memory and one or more processors operable to execute instructions, stored in the memory, comprising instructions to perform the operations of: identifying a respective ordered list of search result documents for each query in a plurality of queries; identifying: a given query in the plurality of queries; a first and second grouping in the ordered list for the given query; and a first and second grouping in the ordered list for each of the remaining queries in the plurality of queries; determining non-overlap scores between the given query and each of the remaining queries in the plurality of queries, wherein the non-overlap scores measure dissimilarities between the search result documents within the first grouping in the ordered list for the given query and the first grouping in the ordered list for each of the remaining queries in the plurality of queries; selecting one or more candidate queries from the remaining queries in the plurality of queries based on the non-overlap scores; determining overlap scores between the given query and each of the candidate queries, wherein the overlap scores measure similarities between the search result documents within the second grouping in the ordered list for the given query and the second grouping in the ordered list for each of the candidate queries; selecting one or more related queries from the candidate queries based on the overlap scores; and storing data associating the related queries with the given query. 31. The system of claim 18 , wherein: the queries in the plurality of queries are past queries submitted by prior users; and selecting one or more of the candidate queries is further based on a frequency that the respective candidate queries were submitted by the prior users. | 0.618785 |
8,966,645 | 14 | 20 | 14. A computer program product, comprising: a computer readable storage device having computer readable program code embodied therewith, where the computer readable program code when executed on a computer causes the computer to: evaluate, without use of any configured password, text entry context information associated with text entry within an inter-user communication application; determine that the evaluated text entry context information identifies a text string entered by a user as a potential password inadvertently entered into the inter-user communication application by the user; prompt, in response to determining that the text string is identified as the potential password, the user to confirm that the user intends to send the text string using the inter-user communication application; and transmit the text string via the inter-user communication application in response to a confirmation from the user to send the text string. | 14. A computer program product, comprising: a computer readable storage device having computer readable program code embodied therewith, where the computer readable program code when executed on a computer causes the computer to: evaluate, without use of any configured password, text entry context information associated with text entry within an inter-user communication application; determine that the evaluated text entry context information identifies a text string entered by a user as a potential password inadvertently entered into the inter-user communication application by the user; prompt, in response to determining that the text string is identified as the potential password, the user to confirm that the user intends to send the text string using the inter-user communication application; and transmit the text string via the inter-user communication application in response to a confirmation from the user to send the text string. 20. The computer program product of claim 14 , where: the text entry context information comprises at least one of run-time text-based and run-time time-based analysis of a manner of entry and content of characters of the text entry that omits evaluation of known passwords; in causing the computer to evaluate, without the use of any configured password, the text entry context information associated with the text entry within the inter-user communication application, the computer readable program code when executed on the computer causes the computer to: detect a windowing system focus change from a valid password entry field of a different application to the inter-user communication application; and detect entry of a single text string without spaces within a configured time from the focus change from the valid password entry field of the different application to the inter-user communication application; and in causing the computer to determine that the evaluated text entry context information identifies the text string entered by the user as the potential password inadvertently entered into the inter-user communication application by the user, the computer readable program code when executed on the computer causes the computer to: identify the single text string without spaces as the potential password in response to detecting the entry of the single text string without spaces within the configured time from the focus change from the valid password entry field of the different application to the inter-user communication application. | 0.537937 |
7,848,573 | 16 | 17 | 16. A system, comprising: an input device adapted to receive electronic ink input; and a processor-adapted to: (a) convert the electronic ink input to one or more machine-generated objects; (b) determine a size of the one or more machine-generated objects by calculating an average height of the corresponding electronic ink input and setting the size of the one or more machine-generated objects to be equivalent in scale to the calculated average height; (c) render the one or more machine-generated objects using the determined size for the machine-generated object or objects and an original inter-word spacing of the electronic ink input, wherein word positions of the rendered machine-generated object or objects on a display correspond to original word positions of the electronic ink input on the display; (d) receive a request from a user to reformat the machine-generated objects in a manner consistent with a word-processing format; and (e) in response to the request, adjust the word positions of the rendered machine-generated objects wherein the word positions, the inter-word spacings, word wrap, and margins are consistent with the word-processing format. | 16. A system, comprising: an input device adapted to receive electronic ink input; and a processor-adapted to: (a) convert the electronic ink input to one or more machine-generated objects; (b) determine a size of the one or more machine-generated objects by calculating an average height of the corresponding electronic ink input and setting the size of the one or more machine-generated objects to be equivalent in scale to the calculated average height; (c) render the one or more machine-generated objects using the determined size for the machine-generated object or objects and an original inter-word spacing of the electronic ink input, wherein word positions of the rendered machine-generated object or objects on a display correspond to original word positions of the electronic ink input on the display; (d) receive a request from a user to reformat the machine-generated objects in a manner consistent with a word-processing format; and (e) in response to the request, adjust the word positions of the rendered machine-generated objects wherein the word positions, the inter-word spacings, word wrap, and margins are consistent with the word-processing format. 17. A system according to claim 16 , wherein the electronic ink input includes electronic ink text input and the one or more machine-generated objects includes machine-generated text, wherein said determine the size of the one or more machine-generated objects constitutes determine a font size of the machine-generated text. | 0.5 |
6,098,042 | 3 | 4 | 3. The computer program product of claim 2 wherein the program code configured to identify selected portions of the text data comprises: program code configured to parse the text data; and program code configured to delineate the text data into phrases. | 3. The computer program product of claim 2 wherein the program code configured to identify selected portions of the text data comprises: program code configured to parse the text data; and program code configured to delineate the text data into phrases. 4. The program code of claim 3 wherein the program code configured to delineate further comprises: program code configured to identify punctuation characters peculiar to the natural language of the text data. | 0.5 |
9,659,578 | 19 | 22 | 19. A computer implemented method for identifying significant speech frames within speech signals for facilitating speech recognition, said method comprising: storing instructions and data in a memory; receiving, using a processor, said instructions and data from said memory; storing, a set of computing instructions related to spectral analysis into a first repository, a set of computing instructions related to feature vector extractions into a second repository, a set of computing instructions related to frame weighting and a set of computing instructions related to suitability measure; receiving, by an input module, at least an input speech signal, wherein the speech signal is represented by a plurality of feature vectors; dividing, using a divider of a spectrum analyzer, the input speech signal into a plurality of speech frames and computing at least a spectral magnitude of each of the speech frames; extracting, using an extractor, at least a feature vector from each of the speech frames; receiving at a suitability engine of said computer, the speech frames and the corresponding spectral magnitude of each of speech frames for the purpose of computing a suitability measure for each of the speech frames: computing, by a spectral flatness module of said suitability engine, a spectral flatness measure for each of the speech frames and determining, by said spectral flatness module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the spectral flatness measure computed; computing, by an energy normalized variance module of said suitability engine, an energy normalized variance for each of the speech frame and determining, by said energy normalized variance module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the energy normalized variance computed; computing, by an entropy module of said suitability engine, an entropy for each of the speech frame and determining, by said entropy module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the entropy computed; computing, by a signal-to-noise ratio module of said suitability engine, a signal-to-noise ratio for each of the speech frame and determining, by said signal-to-noise ratio module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the signal-to-noise ratio computed; computing, by a similarity module of said suitability engine, a similarity measure for each of the speech frame and determining, by said similarity module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to similarity measure computed; calculating, by a final suitability measure module of said suitability engine, a final suitability measure by considering the spectral flatness measure, the energy normalized variance, the entropy, the signal-to-noise ratio and the similarity measure along with the corresponding suitability measures computed for each of said speech frames; and computing and assigning, by a frame weight assigner of said computer, at least a weight for each of the speech frames to identify significant speech frames based on the spectral magnitude and the final suitability measure of respective speech frame. | 19. A computer implemented method for identifying significant speech frames within speech signals for facilitating speech recognition, said method comprising: storing instructions and data in a memory; receiving, using a processor, said instructions and data from said memory; storing, a set of computing instructions related to spectral analysis into a first repository, a set of computing instructions related to feature vector extractions into a second repository, a set of computing instructions related to frame weighting and a set of computing instructions related to suitability measure; receiving, by an input module, at least an input speech signal, wherein the speech signal is represented by a plurality of feature vectors; dividing, using a divider of a spectrum analyzer, the input speech signal into a plurality of speech frames and computing at least a spectral magnitude of each of the speech frames; extracting, using an extractor, at least a feature vector from each of the speech frames; receiving at a suitability engine of said computer, the speech frames and the corresponding spectral magnitude of each of speech frames for the purpose of computing a suitability measure for each of the speech frames: computing, by a spectral flatness module of said suitability engine, a spectral flatness measure for each of the speech frames and determining, by said spectral flatness module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the spectral flatness measure computed; computing, by an energy normalized variance module of said suitability engine, an energy normalized variance for each of the speech frame and determining, by said energy normalized variance module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the energy normalized variance computed; computing, by an entropy module of said suitability engine, an entropy for each of the speech frame and determining, by said entropy module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the entropy computed; computing, by a signal-to-noise ratio module of said suitability engine, a signal-to-noise ratio for each of the speech frame and determining, by said signal-to-noise ratio module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the signal-to-noise ratio computed; computing, by a similarity module of said suitability engine, a similarity measure for each of the speech frame and determining, by said similarity module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to similarity measure computed; calculating, by a final suitability measure module of said suitability engine, a final suitability measure by considering the spectral flatness measure, the energy normalized variance, the entropy, the signal-to-noise ratio and the similarity measure along with the corresponding suitability measures computed for each of said speech frames; and computing and assigning, by a frame weight assigner of said computer, at least a weight for each of the speech frames to identify significant speech frames based on the spectral magnitude and the final suitability measure of respective speech frame. 22. The method as claimed in claim 19 , wherein the step of computing the energy normalized variance for each of the speech frame further includes a step of accepting a noise estimation of said speech frames to compute a frame level signal-to-noise ratio. | 0.772727 |
8,192,469 | 35 | 41 | 35. A dynamic spine stabilization system comprising: a first anchor adapted to be anchored to a pedicle of a first vertebra, and a second anchor adapted to be anchored to an opposite pedicle of the first vertebra; a third anchor adapted to be anchored to a pedicle of a second vertebra, and a fourth anchor adapted to be anchored to an opposite pedicle of the second vertebra; a first horizontal rod connecting between the first anchor and the second anchor; a second horizontal rod connecting between the third anchor and the fourth anchor; a deflection rod having a first deflectable end and a second deflectable end; a connector which attaches a middle portion of the deflection rod to a middle portion of the first horizontal rod; a first vertical rod connected at one end by a first pivotable joint to the first deflectable end of the deflection rod and at another end to the second horizontal rod; and a second vertical rod connected at one end by a second pivotable joint to the second deflectable end of the deflection rod and at another end to the second horizontal rod. | 35. A dynamic spine stabilization system comprising: a first anchor adapted to be anchored to a pedicle of a first vertebra, and a second anchor adapted to be anchored to an opposite pedicle of the first vertebra; a third anchor adapted to be anchored to a pedicle of a second vertebra, and a fourth anchor adapted to be anchored to an opposite pedicle of the second vertebra; a first horizontal rod connecting between the first anchor and the second anchor; a second horizontal rod connecting between the third anchor and the fourth anchor; a deflection rod having a first deflectable end and a second deflectable end; a connector which attaches a middle portion of the deflection rod to a middle portion of the first horizontal rod; a first vertical rod connected at one end by a first pivotable joint to the first deflectable end of the deflection rod and at another end to the second horizontal rod; and a second vertical rod connected at one end by a second pivotable joint to the second deflectable end of the deflection rod and at another end to the second horizontal rod. 41. The dynamic spine stabilization system of claim 35 , wherein said first horizontal rod is bowed. | 0.894068 |
9,424,321 | 1 | 7 | 1. A method comprising: receiving, by at least one data processor, a plurality of data files from a plurality of data sources that comprise textual content; categorizing, by the at least one data processor, the plurality of data files into a taxonomy of categories in which each category has associated sample textual content defining a concept for the category and each category is a run-length encoded collection of at least one identification corresponding to at least one of the plurality of data files, the categorizing comprising, for each category: comparing, by the at least one data processor, for each of the plurality of data files, the textual content of the data file with the sample textual content for the category; calculating, by the at least one data processor, based on the comparing and for each of the plurality of data files, a file score corresponding to the degree of similarity between the defined concept of the category and a determined concept for the data file; and generating, by the at least one data processor, the identification stored in the run-length encoded collection by at least associating, for each of the plurality of data files, the data file with the category if the file score is equal to or greater than a pre-determined minimum score for the category; and providing, by the at least one data processor, at least a portion of the data file and/or the associated file score. | 1. A method comprising: receiving, by at least one data processor, a plurality of data files from a plurality of data sources that comprise textual content; categorizing, by the at least one data processor, the plurality of data files into a taxonomy of categories in which each category has associated sample textual content defining a concept for the category and each category is a run-length encoded collection of at least one identification corresponding to at least one of the plurality of data files, the categorizing comprising, for each category: comparing, by the at least one data processor, for each of the plurality of data files, the textual content of the data file with the sample textual content for the category; calculating, by the at least one data processor, based on the comparing and for each of the plurality of data files, a file score corresponding to the degree of similarity between the defined concept of the category and a determined concept for the data file; and generating, by the at least one data processor, the identification stored in the run-length encoded collection by at least associating, for each of the plurality of data files, the data file with the category if the file score is equal to or greater than a pre-determined minimum score for the category; and providing, by the at least one data processor, at least a portion of the data file and/or the associated file score. 7. The method of claim 1 , wherein the providing includes providing, by the at least one data processor, a first representation of the data file along with a second representation of all attachments, metadata, or electronic associations. | 0.828261 |
8,296,354 | 2 | 3 | 2. The first computer system as recited in claim 1 , wherein the act of accessing the typed data object comprises an act of accessing a class that represents parameters to the method. | 2. The first computer system as recited in claim 1 , wherein the act of accessing the typed data object comprises an act of accessing a class that represents parameters to the method. 3. The first computer system as recited in claim 2 , wherein the act of accessing the class that represents parameters to the method comprises an act of accessing a public class that represents parameters to a Common Language Runtime method. | 0.5 |
8,407,177 | 9 | 16 | 9. A method of evaluating a sociocultural event with a computer system, said method comprising: receiving and analyzing, using an analytical processing device, a communication sample associated with a sociocultural event associated with and at least partially originating from a target human subject to determine a contextual data element and one of an apparent cultural data element and an apparent linguistic data element, each data element being associated with the communication sample; correlating, using a correlative processing device, the contextual data element with one of a projected cultural data element and a projected linguistic data element expected of a corresponding hypothetical human subject; and comparing, using a comparative processing device, the one of the apparent cultural data element and the apparent linguistic data element with the corresponding one of the projected cultural data element and the projected linguistic data element to determine whether the sociocultural event is consistent with the target human subject, wherein the contextual data element further includes a communicative data element, wherein correlating the contextual data element with one of a projected cultural data element and a projected linguistic data element further comprises correlating, using the correlative processing device, the contextual data element with a database comprising a plurality of empirically-determined communicative data elements associated with a plurality of empirically-determined cultural data elements and empirically-determined linguistic data elements, at least one of the empirically-determined cultural data elements, the empirically-determined linguistic data elements and the empirically-determined communicative data elements, correlated with the contextual data element, defining the one of the projected cultural data element and the projected linguistic data element expected of the corresponding hypothetical human subject, and wherein the method further comprises forming the database, using a database processing device, by: selecting control cultural data elements from the empirically-determined cultural data elements using a network analysis procedure, and combining the control cultural data elements to form a composite conceptual network defining social aspects of the one of the projected cultural data element and the projected linguistic data element; selecting control communicative data elements from the empirically-determined communicative data elements and empirically-determined linguistic data elements, the control communicative data elements defining communicative aspects of the one of the projected cultural data element and the projected linguistic data element, and correlating the control communicative data elements with the control cultural data elements by mapping the control communicative data elements with the composite conceptual network; and integrating the control cultural data elements having the control communicative data elements mapped thereto so as to form the database. | 9. A method of evaluating a sociocultural event with a computer system, said method comprising: receiving and analyzing, using an analytical processing device, a communication sample associated with a sociocultural event associated with and at least partially originating from a target human subject to determine a contextual data element and one of an apparent cultural data element and an apparent linguistic data element, each data element being associated with the communication sample; correlating, using a correlative processing device, the contextual data element with one of a projected cultural data element and a projected linguistic data element expected of a corresponding hypothetical human subject; and comparing, using a comparative processing device, the one of the apparent cultural data element and the apparent linguistic data element with the corresponding one of the projected cultural data element and the projected linguistic data element to determine whether the sociocultural event is consistent with the target human subject, wherein the contextual data element further includes a communicative data element, wherein correlating the contextual data element with one of a projected cultural data element and a projected linguistic data element further comprises correlating, using the correlative processing device, the contextual data element with a database comprising a plurality of empirically-determined communicative data elements associated with a plurality of empirically-determined cultural data elements and empirically-determined linguistic data elements, at least one of the empirically-determined cultural data elements, the empirically-determined linguistic data elements and the empirically-determined communicative data elements, correlated with the contextual data element, defining the one of the projected cultural data element and the projected linguistic data element expected of the corresponding hypothetical human subject, and wherein the method further comprises forming the database, using a database processing device, by: selecting control cultural data elements from the empirically-determined cultural data elements using a network analysis procedure, and combining the control cultural data elements to form a composite conceptual network defining social aspects of the one of the projected cultural data element and the projected linguistic data element; selecting control communicative data elements from the empirically-determined communicative data elements and empirically-determined linguistic data elements, the control communicative data elements defining communicative aspects of the one of the projected cultural data element and the projected linguistic data element, and correlating the control communicative data elements with the control cultural data elements by mapping the control communicative data elements with the composite conceptual network; and integrating the control cultural data elements having the control communicative data elements mapped thereto so as to form the database. 16. A method according to claim 9 further comprising forming the empirically-determined communicative data elements, using a communicative data processing device, by: receiving control communication samples from a defined cultural group of human subjects; converting the control communication samples into a processable and extractable format using a communication format agreement procedure; associating communicative characteristics of the control communication samples with corresponding communicative data elements so as to define the empirically-determined communicative data elements; and associating linguistic characteristics of the control communication samples with corresponding linguistic data elements so as to define the empirically-determined linguistic data elements. | 0.5 |
7,720,828 | 1 | 4 | 1. A method for automatically processing electronic information messages, comprising: automatically via a software module receiving an electronic information message on a network device with one or more processors via a communications network from a source network device with one or more processors; automatically via the software module parsing the electronic information message to identify one or more keywords in the electronic information message, wherein the identified one or more keywords include keywords include advertising keywords stored in a database, non-advertising keywords such as public interest keywords and keywords dynamically generated using information theory to decide relevant keywords; automatically via the software module mapping a selected single identified keyword into a plurality of related keywords, or mapping a plurality of selected identified keywords into a single keyword before submitting the one or more queries to one or more search engines; automatically via the software module submitting the identified one or more keywords from the network device to the one or more search engines as one or more search engine queries via the communications network, wherein the one or more search engines include one or more publicly available search engines and one or more privately available search engines; automatically via the software module receiving query results from the one or more search engines; automatically via the software module selecting one or more electronic links from the one or more query results, wherein the one or more electronic links are selected based on pre-determined conditions, wherein one of the pre-determine conditions includes fee agreements with advertisers and wherein the electronic links include electronic links for linking directly to another information site on the communications network, for initiating a static search engine query and for initiating a dynamic search engine query; automatically via the software module adding the one or more selected electronic links to the electronic message creating a modified electronic information message, thereby allowing additional electronic information to be accessed from the modified electronic information message based on information content of the electronic information message, wherein a same selected electronic link is added to repeating occurrences of an identified keyword and wherein different selected electronic links are added to repeating occurrences of the identified keyword. | 1. A method for automatically processing electronic information messages, comprising: automatically via a software module receiving an electronic information message on a network device with one or more processors via a communications network from a source network device with one or more processors; automatically via the software module parsing the electronic information message to identify one or more keywords in the electronic information message, wherein the identified one or more keywords include keywords include advertising keywords stored in a database, non-advertising keywords such as public interest keywords and keywords dynamically generated using information theory to decide relevant keywords; automatically via the software module mapping a selected single identified keyword into a plurality of related keywords, or mapping a plurality of selected identified keywords into a single keyword before submitting the one or more queries to one or more search engines; automatically via the software module submitting the identified one or more keywords from the network device to the one or more search engines as one or more search engine queries via the communications network, wherein the one or more search engines include one or more publicly available search engines and one or more privately available search engines; automatically via the software module receiving query results from the one or more search engines; automatically via the software module selecting one or more electronic links from the one or more query results, wherein the one or more electronic links are selected based on pre-determined conditions, wherein one of the pre-determine conditions includes fee agreements with advertisers and wherein the electronic links include electronic links for linking directly to another information site on the communications network, for initiating a static search engine query and for initiating a dynamic search engine query; automatically via the software module adding the one or more selected electronic links to the electronic message creating a modified electronic information message, thereby allowing additional electronic information to be accessed from the modified electronic information message based on information content of the electronic information message, wherein a same selected electronic link is added to repeating occurrences of an identified keyword and wherein different selected electronic links are added to repeating occurrences of the identified keyword. 4. The method of claim 1 wherein the electronic links include mark-up language electronic links. | 0.808 |
10,083,244 | 6 | 10 | 6. A system comprising one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by location-based search engine that includes (i) a web crawler, (ii) a query processor, (iii) a uniform resource identifier constructor, and (iv) a uniform resource identifier interpreter, a query comprising search parameters that (i) specify a desired location and one or more desired amenities of a rental unit being sought by a user of the location-based search engine, and (ii) are specified through one or more interactions between the user and one or more drop down controls included on a search parameter entry graphical user interface associated with the location-based search engine; selecting, by the uniform resource identifier constructor, two or more of the search parameters that (i) specify the desired location and the one or more desired amenities of a rental unit being sought by the user of the location-based search engine, and (ii) are specified through the one or more interactions between the user and the one or more drop down controls included on the search parameter entry graphical user interface associated with the location-based search engine; for each of the selected search parameters: generating, by the uniform resource identifier constructor, a natural language representation of the selected search parameter; and determining, by the uniform resource identifier constructor, using rules that indicate a relative importance of the search parameters that specify the one or more desired amenities to users of the search engine, or to the web crawler for search engine optimization purposes, a rank of the selected parameter among the one or more selected parameters, wherein search parameters that are more frequently searched by users of the search engine are assigned a higher relative importance than search parameters that are less frequently searched by the users of the search engines; generating, by the uniform resource identifier constructor, a uniform resource identifier comprising the natural language representations of the selected parameters arranged in an order based on the ranks of the selected search parameters, including the search parameters that specify the one or more desired amenities of the rental unit being sought by the user, that were determined using the rules that indicate the relative importance of the search parameters to the users of the search engine, or to the web crawler for search engine optimization purposes; obtaining, by the query processor, one or more search results identified as responsive to the query; providing, by the location-based search engine, a search results page graphical user interface that includes the uniform resource identifier and the one or more search results for output, the uniform resource identifier including a natural language representation of the desired location and a natural language representation of one or more of the desired amenities of the rental unit; and in response to subsequently receiving the generated uniform resource identifier including the natural language representation of the desired location and the natural language representation of one or more of the desired amenities of the rental unit, generating, by the uniform resource identifier interpreter, a subsequent query that includes the same search parameters for execution by the location-based search engine. | 6. A system comprising one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by location-based search engine that includes (i) a web crawler, (ii) a query processor, (iii) a uniform resource identifier constructor, and (iv) a uniform resource identifier interpreter, a query comprising search parameters that (i) specify a desired location and one or more desired amenities of a rental unit being sought by a user of the location-based search engine, and (ii) are specified through one or more interactions between the user and one or more drop down controls included on a search parameter entry graphical user interface associated with the location-based search engine; selecting, by the uniform resource identifier constructor, two or more of the search parameters that (i) specify the desired location and the one or more desired amenities of a rental unit being sought by the user of the location-based search engine, and (ii) are specified through the one or more interactions between the user and the one or more drop down controls included on the search parameter entry graphical user interface associated with the location-based search engine; for each of the selected search parameters: generating, by the uniform resource identifier constructor, a natural language representation of the selected search parameter; and determining, by the uniform resource identifier constructor, using rules that indicate a relative importance of the search parameters that specify the one or more desired amenities to users of the search engine, or to the web crawler for search engine optimization purposes, a rank of the selected parameter among the one or more selected parameters, wherein search parameters that are more frequently searched by users of the search engine are assigned a higher relative importance than search parameters that are less frequently searched by the users of the search engines; generating, by the uniform resource identifier constructor, a uniform resource identifier comprising the natural language representations of the selected parameters arranged in an order based on the ranks of the selected search parameters, including the search parameters that specify the one or more desired amenities of the rental unit being sought by the user, that were determined using the rules that indicate the relative importance of the search parameters to the users of the search engine, or to the web crawler for search engine optimization purposes; obtaining, by the query processor, one or more search results identified as responsive to the query; providing, by the location-based search engine, a search results page graphical user interface that includes the uniform resource identifier and the one or more search results for output, the uniform resource identifier including a natural language representation of the desired location and a natural language representation of one or more of the desired amenities of the rental unit; and in response to subsequently receiving the generated uniform resource identifier including the natural language representation of the desired location and the natural language representation of one or more of the desired amenities of the rental unit, generating, by the uniform resource identifier interpreter, a subsequent query that includes the same search parameters for execution by the location-based search engine. 10. The system of claim 6 , the operations comprising: obtaining a changed uniform resource identifier comprising at least one natural language representation of a search parameter different than the natural language representations of the selected parameters of the uniform resource identifier; identifying new search parameters for a changed query based on the changed uniform resource identifier; and obtaining one or more different search results identified as responsive to the changed query. | 0.5 |
5,465,304 | 17 | 22 | 17. An apparatus for segmenting portions of a medium representation into text and non-text types, said apparatus comprising: a memory for storing said medium representation, said medium representation including a plurality of scanlines, said plurality of scanlines being organized into a plurality of groups of scanlines; a processor, being coupled to said memory, said processor for compressing said plurality of groups into a plurality of compressed scanlines, said processor for generating a plurality of run lengths by extracting a run length from each compressed scanline in said plurality of compressed scanlines, said processor for generating a plurality of run length classifications by generating a run length classification for each run length in said plurality of run lengths according to a length of each run length, said processor for constructing a set of rectangles from said plurality of run lengths and said plurality of run length classifications, said processor for assigning a classification to each rectangle of said set of rectangles as non-text type or unknown type using said run length classifications associated with each rectangle, and said processor for generating a plurality of text blocks from a set of rectangles of said set of rectangles having an unknown type and for storing said plurality of text blocks in said memory. | 17. An apparatus for segmenting portions of a medium representation into text and non-text types, said apparatus comprising: a memory for storing said medium representation, said medium representation including a plurality of scanlines, said plurality of scanlines being organized into a plurality of groups of scanlines; a processor, being coupled to said memory, said processor for compressing said plurality of groups into a plurality of compressed scanlines, said processor for generating a plurality of run lengths by extracting a run length from each compressed scanline in said plurality of compressed scanlines, said processor for generating a plurality of run length classifications by generating a run length classification for each run length in said plurality of run lengths according to a length of each run length, said processor for constructing a set of rectangles from said plurality of run lengths and said plurality of run length classifications, said processor for assigning a classification to each rectangle of said set of rectangles as non-text type or unknown type using said run length classifications associated with each rectangle, and said processor for generating a plurality of text blocks from a set of rectangles of said set of rectangles having an unknown type and for storing said plurality of text blocks in said memory. 22. The system of claim 17 wherein said non-text type includes horizontal line type, vertical line type, and image type. | 0.642857 |
10,133,734 | 7 | 9 | 7. A database-building data processing system configured for building an analysis database associating each of a plurality of n-grams with corresponding respective cognitive motivation orientations, the system comprising: a host computer with memory and at least one processor coupled to the memory; and a database-building module, the database-building module comprising program code that, when executed in the memory of the host computer: receives a training corpus of training documents, wherein: each training document comprises a plurality of meaningfully arranged words in electronic form; each training document has at least one annotated word sequence therein; wherein within each training document, each particular annotated word sequence is annotated with a corresponding word-sequence-level annotation identifying at least one cognitive motivation orientation that is associated with that particular annotated word sequence; for each training document: for each annotated word sequence in that particular training document: extracts n-grams overlapping that particular annotated word sequence; and associates each extracted n-gram with the at least one cognitive motivation orientation associated with that particular annotated word sequence; generates a set of indicator candidate n-grams wherein: each indicator candidate n-gram represents all instances of a particular n-gram in the training corpus for which at least one instance of that particular n-gram was extracted from any annotated word sequence in any training document; each indicator candidate n-gram being associated with every cognitive motivation orientation that is associated with at least one instance of the particular n-gram represented by that particular indicator candidate n-gram; applies at least one relevance filter to each indicator candidate n-gram in the set of indicator candidate n-grams to obtain a set of indicator n-grams, wherein; the set of indicator n-grams is a subset of the set of indicator candidate n-grams, so that each indicator n-gram corresponds to only one indicator candidate n-gram and thereby each indicator n-gram represents all instances of a corresponding particular n-gram in the training corpus for which at least one instance of that particular n-gram was extracted from any annotated word sequence in any training document; and each indicator n-gram is associated with only a single cognitive motivation orientation; wherein each indicator n-gram has, as its associated single cognitive motivation orientation, that single cognitive motivation orientation with which the instances of the particular n-gram represented by that particular indicator n-gram are most frequently associated; permitting the analysis database to support enhanced computer-implemented neurolinguistic analysis of a text sequence to identify cognitive motivation orientations expressed within the text sequence quickly, objectively and consistently. | 7. A database-building data processing system configured for building an analysis database associating each of a plurality of n-grams with corresponding respective cognitive motivation orientations, the system comprising: a host computer with memory and at least one processor coupled to the memory; and a database-building module, the database-building module comprising program code that, when executed in the memory of the host computer: receives a training corpus of training documents, wherein: each training document comprises a plurality of meaningfully arranged words in electronic form; each training document has at least one annotated word sequence therein; wherein within each training document, each particular annotated word sequence is annotated with a corresponding word-sequence-level annotation identifying at least one cognitive motivation orientation that is associated with that particular annotated word sequence; for each training document: for each annotated word sequence in that particular training document: extracts n-grams overlapping that particular annotated word sequence; and associates each extracted n-gram with the at least one cognitive motivation orientation associated with that particular annotated word sequence; generates a set of indicator candidate n-grams wherein: each indicator candidate n-gram represents all instances of a particular n-gram in the training corpus for which at least one instance of that particular n-gram was extracted from any annotated word sequence in any training document; each indicator candidate n-gram being associated with every cognitive motivation orientation that is associated with at least one instance of the particular n-gram represented by that particular indicator candidate n-gram; applies at least one relevance filter to each indicator candidate n-gram in the set of indicator candidate n-grams to obtain a set of indicator n-grams, wherein; the set of indicator n-grams is a subset of the set of indicator candidate n-grams, so that each indicator n-gram corresponds to only one indicator candidate n-gram and thereby each indicator n-gram represents all instances of a corresponding particular n-gram in the training corpus for which at least one instance of that particular n-gram was extracted from any annotated word sequence in any training document; and each indicator n-gram is associated with only a single cognitive motivation orientation; wherein each indicator n-gram has, as its associated single cognitive motivation orientation, that single cognitive motivation orientation with which the instances of the particular n-gram represented by that particular indicator n-gram are most frequently associated; permitting the analysis database to support enhanced computer-implemented neurolinguistic analysis of a text sequence to identify cognitive motivation orientations expressed within the text sequence quickly, objectively and consistently. 9. The data processing system of claim 7 , wherein the database-building module further comprises program code that, when executed in the memory of the host computer, assigns a confidence weight to each indicator n-gram. | 0.960896 |
10,078,750 | 1 | 6 | 1. A system for finding a compromised social networking account, the system comprising: a social networking site comprising one or more computers that provide a social networking service over the Internet; and a backend system for receiving social messages from the social networking site, identifying compromised social networking accounts from the received social messages, extracting keywords from social messages of the identified compromised social networking accounts, sending a search query with the extracted keywords as search terms, receiving search results responsive to the search query from the social networking site, and finding additional compromised social networking accounts from social messages that are included in the search results. | 1. A system for finding a compromised social networking account, the system comprising: a social networking site comprising one or more computers that provide a social networking service over the Internet; and a backend system for receiving social messages from the social networking site, identifying compromised social networking accounts from the received social messages, extracting keywords from social messages of the identified compromised social networking accounts, sending a search query with the extracted keywords as search terms, receiving search results responsive to the search query from the social networking site, and finding additional compromised social networking accounts from social messages that are included in the search results. 6. The system of claim 1 , wherein the identified compromised social networking accounts are accounts that have been hijacked from their registered owner. | 0.611111 |
10,134,385 | 17 | 18 | 17. A non-transitory computer-readable storage medium storing one or more programs configured to be executed by one or more processors of an electronic device, the one or more programs including instructions for: 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. | 17. A non-transitory computer-readable storage medium storing one or more programs configured to be executed by one or more processors of an electronic device, the one or more programs including instructions for: 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. 18. The computer-readable storage medium of claim 17 , wherein the one or more programs include further instructions for outputting the phonetic pronunciation via a user interface. | 0.6 |
8,977,620 | 14 | 16 | 14. One or more non-transitory computer-readable storage media having computer-executable instructions embodied thereon, wherein when executed by at least one processor, the computer-executable instructions cause the processor to: receive a plurality of documents from at least one user, wherein each document includes unplanned information relating to a customer support issue or sentiment; identify at least one customer support issue or sentiment contained within each document by parsing the plurality of documents; if a confidence level of the identification meets a confidence level threshold of the customer support issue or sentiment, classify the documents satisfying a confidence threshold using a classifier into one of a plurality of classes, each class associated with the identified at least one customer support issue or sentiment; cluster a remainder of the plurality of documents that do not meet the confidence level threshold into a plurality of clustered groups containing similar terms relating to the customer support issue or sentiment using a clustering engine, the clustering engine applying a word analysis; and output a frequency of each identified customer support issue or sentiment within at least one of the plurality of classes and plurality of clustered groups, the frequency based on said classification or said clustering. | 14. One or more non-transitory computer-readable storage media having computer-executable instructions embodied thereon, wherein when executed by at least one processor, the computer-executable instructions cause the processor to: receive a plurality of documents from at least one user, wherein each document includes unplanned information relating to a customer support issue or sentiment; identify at least one customer support issue or sentiment contained within each document by parsing the plurality of documents; if a confidence level of the identification meets a confidence level threshold of the customer support issue or sentiment, classify the documents satisfying a confidence threshold using a classifier into one of a plurality of classes, each class associated with the identified at least one customer support issue or sentiment; cluster a remainder of the plurality of documents that do not meet the confidence level threshold into a plurality of clustered groups containing similar terms relating to the customer support issue or sentiment using a clustering engine, the clustering engine applying a word analysis; and output a frequency of each identified customer support issue or sentiment within at least one of the plurality of classes and plurality of clustered groups, the frequency based on said classification or said clustering. 16. The computer-readable storage media of claim 14 , wherein the computer-executable instructions further cause the processor to label each group of the plurality of clustered groups based on a probability that the group relates to a determined customer support issue or sentiment. | 0.540717 |
7,797,269 | 7 | 11 | 7. An apparatus, comprising: a processor; a memory storing at least one context sensitive dictionary having a plurality of first words therein, a subset of one or more of the first words being associated with one or more respective associated words and phrases, the or each respective associated word and phrase representing an instance of the first word with which it is associated; a display configured to display images to a user under the control of the processor; and a user input that enables user character input; wherein the processor is further configured to cause the apparatus to: compare input characters when input with the first words in the at least one context sensitive dictionary; determine, in dependence on the comparison, one or more first words in the context sensitive dictionary corresponding, at least partially, to the input characters; and select, in dependence on the determination, one or more associated words and phrases associated with the determined first words; the display being configured to display the selected one or more associated words and phrases to the user as a substitution for the input characters. | 7. An apparatus, comprising: a processor; a memory storing at least one context sensitive dictionary having a plurality of first words therein, a subset of one or more of the first words being associated with one or more respective associated words and phrases, the or each respective associated word and phrase representing an instance of the first word with which it is associated; a display configured to display images to a user under the control of the processor; and a user input that enables user character input; wherein the processor is further configured to cause the apparatus to: compare input characters when input with the first words in the at least one context sensitive dictionary; determine, in dependence on the comparison, one or more first words in the context sensitive dictionary corresponding, at least partially, to the input characters; and select, in dependence on the determination, one or more associated words and phrases associated with the determined first words; the display being configured to display the selected one or more associated words and phrases to the user as a substitution for the input characters. 11. The apparatus of claim 7 , wherein the apparatus comprises a mobile phone, a PDA, a PDT, or a palmtop computer. | 0.815113 |
7,870,238 | 9 | 16 | 9. A computing device comprising: a control unit comprising a processor that executes a network configuration tool to manage a plurality of network devices from different vendors, the network configuration tool comprising: a management interface module that connects to first and second network devices of the plurality of network devices, wherein the first network device is from a first vendor and stores a first set of configuration information, and the second network device is from a second vendor and stores a second set of configuration information; an extraction module that adaptively extracts the first and second sets of configuration information stored to the respective first and second network devices, interfaces with first and second management software interfaces presented by the first and second network devices, parses from the first and second sets of configuration information respective first and second tags, and stores the stores the first and second tags to a database, wherein the first tag defines a configuration property for the first network device and the second tag defines a configuration property for the second network device; a graph module that determines whether the first tag and the second tag are of a same kind of tag, and when the first and second tags are of the same kind of tag, determines that the first tag and second tag each define similar configuration properties that are comparable; and a user interface module that presents aggregate configuration information in a manner that organizes, when the first and second tags are the same kind of tag, the first and second tags based primarily on the kind and secondarily on the network devices from which the first and second sets of configuration information was received. | 9. A computing device comprising: a control unit comprising a processor that executes a network configuration tool to manage a plurality of network devices from different vendors, the network configuration tool comprising: a management interface module that connects to first and second network devices of the plurality of network devices, wherein the first network device is from a first vendor and stores a first set of configuration information, and the second network device is from a second vendor and stores a second set of configuration information; an extraction module that adaptively extracts the first and second sets of configuration information stored to the respective first and second network devices, interfaces with first and second management software interfaces presented by the first and second network devices, parses from the first and second sets of configuration information respective first and second tags, and stores the stores the first and second tags to a database, wherein the first tag defines a configuration property for the first network device and the second tag defines a configuration property for the second network device; a graph module that determines whether the first tag and the second tag are of a same kind of tag, and when the first and second tags are of the same kind of tag, determines that the first tag and second tag each define similar configuration properties that are comparable; and a user interface module that presents aggregate configuration information in a manner that organizes, when the first and second tags are the same kind of tag, the first and second tags based primarily on the kind and secondarily on the network devices from which the first and second sets of configuration information was received. 16. The computing device of claim 9 , wherein the plurality of network devices each comprise one of a router, a wireless access point, a Dynamic Host Configuration Protocol (DHCP) server, a Domain Name System (DNS) server, a Digital Subscriber Line Access Multiplexer (DSLAM), a border gateway controller, a gateway, and an application layer gateway, wherein the memory comprises a database, and wherein the extraction module stores the first and second tags in accordance with a JavaScript Object Notation (JSON) file format. | 0.828105 |
8,234,693 | 13 | 14 | 13. An article, comprising: a computer readable medium comprising non-transitory stored instructions that enable a machine to: receive a document from a user having an associated security access profile; generate a security label to be stored as an attribute of the document, the security label comprising: a clearance component selected from an authorized subset of a plurality of clearance components, the authorized subset of the plurality of clearance components determined based on the security access profile associated with the user; and a secondary security component selected from an authorized subset of a plurality of secondary security components, the authorized subset of the plurality of secondary security components determined based on the clearance component of the security label and the security access profile associated with the user; store the document in a document repository storing a plurality of documents each having an associated security label; determine whether a third-party user is authorized access the document based on a comparison of a security access profile of the third-party user and the security label associated with the document; allow, when a determination that the third-party user is authorized to access the document based on the comparison of the security access profile of the third-party/user and the security label associated with the document, the third-party user to access the document; receive an edited version of the document from the third-party user, the edited version of the document having an associated updated security label, the updated security label comprising: an updated clearance component selected from an authorized subset of a plurality of clearance components, the authorized subset of a plurality of clearance components determined based on the security access profile associated with the third-party user; and one or more updated secondary security components selected from a subset of a plurality of secondary security components, the subset of a plurality of secondary security components determined based on the updated clearance component of the updated security label and the security access profile associated with the third-party user; and store the edited version of the document in the document repository storing the plurality of documents each having an associated security label. | 13. An article, comprising: a computer readable medium comprising non-transitory stored instructions that enable a machine to: receive a document from a user having an associated security access profile; generate a security label to be stored as an attribute of the document, the security label comprising: a clearance component selected from an authorized subset of a plurality of clearance components, the authorized subset of the plurality of clearance components determined based on the security access profile associated with the user; and a secondary security component selected from an authorized subset of a plurality of secondary security components, the authorized subset of the plurality of secondary security components determined based on the clearance component of the security label and the security access profile associated with the user; store the document in a document repository storing a plurality of documents each having an associated security label; determine whether a third-party user is authorized access the document based on a comparison of a security access profile of the third-party user and the security label associated with the document; allow, when a determination that the third-party user is authorized to access the document based on the comparison of the security access profile of the third-party/user and the security label associated with the document, the third-party user to access the document; receive an edited version of the document from the third-party user, the edited version of the document having an associated updated security label, the updated security label comprising: an updated clearance component selected from an authorized subset of a plurality of clearance components, the authorized subset of a plurality of clearance components determined based on the security access profile associated with the third-party user; and one or more updated secondary security components selected from a subset of a plurality of secondary security components, the subset of a plurality of secondary security components determined based on the updated clearance component of the updated security label and the security access profile associated with the third-party user; and store the edited version of the document in the document repository storing the plurality of documents each having an associated security label. 14. The software of claim 13 , wherein the document received from the user comprises one or more of: a newly-created document; and an imported existing document. | 0.924271 |
9,247,100 | 25 | 30 | 25. A computer program product comprising: a non-transitory computer readable storage medium having program code embodied therewith, the program code readable/executable by a processor to cause the processor to: generate text of a facsimile in a computer readable format; ascertain one or more of a significance and a relevance of at least a portion of the text by locating one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyze the text for at least one of a meaning and a context of the text; initiate a business process based on the analysis; detect a problem with the business process; generate a notification of the problem; notify one or more entities of the problem; and route at least one confirmation of receipt and/or delivery of the facsimile to one or more confirmation destinations based on the analysis, wherein the routing utilizes an outgoing communication device. | 25. A computer program product comprising: a non-transitory computer readable storage medium having program code embodied therewith, the program code readable/executable by a processor to cause the processor to: generate text of a facsimile in a computer readable format; ascertain one or more of a significance and a relevance of at least a portion of the text by locating one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyze the text for at least one of a meaning and a context of the text; initiate a business process based on the analysis; detect a problem with the business process; generate a notification of the problem; notify one or more entities of the problem; and route at least one confirmation of receipt and/or delivery of the facsimile to one or more confirmation destinations based on the analysis, wherein the routing utilizes an outgoing communication device. 30. The computer readable program product as recited in claim 25 , further comprising program code readable/executable by the processor to cause the processor to store at least some of the text in a memory. | 0.705714 |
9,883,071 | 1 | 4 | 1. An image processing apparatus configured to manage documents, said image processing apparatus comprising: a memory configured to store an instruction; and a processor configured to execute said instruction, said processor being further configured to: generate a first additional image based on an image in a designated region of a first document, generate a second additional image showing a difference between said first document and a second document, said second document being a revision of the first document; and register said first additional image and said second additional image on another device in association with a marker image indicating a revision stage of said first document. | 1. An image processing apparatus configured to manage documents, said image processing apparatus comprising: a memory configured to store an instruction; and a processor configured to execute said instruction, said processor being further configured to: generate a first additional image based on an image in a designated region of a first document, generate a second additional image showing a difference between said first document and a second document, said second document being a revision of the first document; and register said first additional image and said second additional image on another device in association with a marker image indicating a revision stage of said first document. 4. The image processing apparatus according to claim 1 , wherein said processor is further configured to print said marker image to replace said image in said designated region of said first document with the printed marker image. | 0.693333 |
8,423,352 | 8 | 9 | 8. A computer usable program product comprising a computer usable storage device including computer usable code for enhancing language detection in short communications, the computer usable code comprising: computer usable code for storing a short communication in an element of a line cache accessible to an application executing in a data processing system, the element being an element in a set of elements in the line cache; computer usable code for assembling a compound text from contents of a subset of the elements of the line cache; computer usable code for receiving a language identifier (language ID) for the compound text from a language detection algorithm; computer usable code for storing the language ID in a language cache element of a language ID cache accessible to the application, the language ID cache including a set of language cache elements; and computer usable code for determining, using contents of a subset of language cache elements, a language of the short communication. | 8. A computer usable program product comprising a computer usable storage device including computer usable code for enhancing language detection in short communications, the computer usable code comprising: computer usable code for storing a short communication in an element of a line cache accessible to an application executing in a data processing system, the element being an element in a set of elements in the line cache; computer usable code for assembling a compound text from contents of a subset of the elements of the line cache; computer usable code for receiving a language identifier (language ID) for the compound text from a language detection algorithm; computer usable code for storing the language ID in a language cache element of a language ID cache accessible to the application, the language ID cache including a set of language cache elements; and computer usable code for determining, using contents of a subset of language cache elements, a language of the short communication. 9. The computer usable program product of claim 8 , further comprising: computer usable code for receiving a confidence level from the language detection algorithm; computer usable code for storing the confidence level relative to the short communication; computer usable code for determining whether the confidence level is at least equal to a threshold confidence level; and computer usable code for setting a current language indicator of the short communication to be the language ID responsive to confidence level being at least equal to the threshold confidence level. | 0.687023 |
7,574,362 | 1 | 10 | 1. A method for sentence planning in a task classification system that interacts with a user, comprising: recognizing symbols in a user's single input communication to a task classification system; determining whether the user's input communication can be understood, wherein if the user's communication can be understood, understanding data is generated; generating a plurality of communicative goals based on the recognized symbols and understanding data, the generated plurality of communicative goals being related to information needed to be obtained from the user; in response to information from the user's single input communication: generating a plurality of sentence plans based on the plurality of generated communicative goals, each sentence plan in the plurality of sentence plans being a realization comprising elementary speech acts each corresponding to a respective communicative goal and combined into at least one complete sentence that accomplishes the plurality of communicative goals, and wherein each sentence plan of the plurality of sentence plans is a viable and potentially usable prompt in response to the user's single input communication; independent of the user, ranking the plurality of generated sentence plans; and outputting at least one of the ranked sentence plans to the user as a response to the user's single input communication such that one dialog turn occurs starting with the user's single input communication and ending with the outputted sentence plan. | 1. A method for sentence planning in a task classification system that interacts with a user, comprising: recognizing symbols in a user's single input communication to a task classification system; determining whether the user's input communication can be understood, wherein if the user's communication can be understood, understanding data is generated; generating a plurality of communicative goals based on the recognized symbols and understanding data, the generated plurality of communicative goals being related to information needed to be obtained from the user; in response to information from the user's single input communication: generating a plurality of sentence plans based on the plurality of generated communicative goals, each sentence plan in the plurality of sentence plans being a realization comprising elementary speech acts each corresponding to a respective communicative goal and combined into at least one complete sentence that accomplishes the plurality of communicative goals, and wherein each sentence plan of the plurality of sentence plans is a viable and potentially usable prompt in response to the user's single input communication; independent of the user, ranking the plurality of generated sentence plans; and outputting at least one of the ranked sentence plans to the user as a response to the user's single input communication such that one dialog turn occurs starting with the user's single input communication and ending with the outputted sentence plan. 10. The method of claim 1 , further comprising: determining whether all of the communicative goals have been met; and processing any tasks associated with the information obtained from the system's interactions with the user if the determining step determines that all of the communicative goals have been met. | 0.52454 |
8,640,017 | 1 | 11 | 1. A computer-implemented method of maintaining a collection of data, comprising: bootstrapping the collection of data to generate a feature lexicon, a language lexicon, and grammar configuration files for use by an information access process in processing one or more queries for the collection of data, wherein the bootstrapping comprises: extracting text from the collection of data, the text corresponding to keys and values; generating the feature lexicon from the extracted text, the feature lexicon comprising a vocabulary of words and their definition in the collection of data; generating the language lexicon from the extracted text, the language lexicon identifying words of interest in the collection of data; and generating the grammar configuration files corresponding to the extracted text, the grammar configuration files comprising rules that identify patterns in the collection of data; and processing the queries for the collection of data in the information access process using the feature lexicon, the language lexicon, and the grammar configuration files, wherein each query is normalized using the language lexicon, the normalized query is parsed into fragments that are annotated using the feature lexicon, and the fragments are converted into groupings of the keys and values using the grammar configuration files, in order to answer the query. | 1. A computer-implemented method of maintaining a collection of data, comprising: bootstrapping the collection of data to generate a feature lexicon, a language lexicon, and grammar configuration files for use by an information access process in processing one or more queries for the collection of data, wherein the bootstrapping comprises: extracting text from the collection of data, the text corresponding to keys and values; generating the feature lexicon from the extracted text, the feature lexicon comprising a vocabulary of words and their definition in the collection of data; generating the language lexicon from the extracted text, the language lexicon identifying words of interest in the collection of data; and generating the grammar configuration files corresponding to the extracted text, the grammar configuration files comprising rules that identify patterns in the collection of data; and processing the queries for the collection of data in the information access process using the feature lexicon, the language lexicon, and the grammar configuration files, wherein each query is normalized using the language lexicon, the normalized query is parsed into fragments that are annotated using the feature lexicon, and the fragments are converted into groupings of the keys and values using the grammar configuration files, in order to answer the query. 11. The computer-implemented method of claim 1 further comprising receiving a query; and answering the query in conjunction with the feature lexicon, language lexicon and grammar configuration files. | 0.664983 |
10,049,656 | 6 | 7 | 6. The computer-implemented method of claim 4 , further comprising performing at least one of automatic speech recognition or natural language understanding on a second utterance using the predictive language model interpolated with a second language model. | 6. The computer-implemented method of claim 4 , further comprising performing at least one of automatic speech recognition or natural language understanding on a second utterance using the predictive language model interpolated with a second language model. 7. The computer-implemented method of claim 6 , wherein the second language model is one of a content domain-specific personal language model or the general language model. | 0.524862 |
8,010,581 | 16 | 20 | 16. The method of claim 1 further comprising: displaying, concurrently, a plurality of panels on the user interface, including: an active panel displaying a selected data item, the selected data item selected from the plurality of data items, and a plurality of entity panels displaying data items, each having a respective determined relationship type to the selected data item. | 16. The method of claim 1 further comprising: displaying, concurrently, a plurality of panels on the user interface, including: an active panel displaying a selected data item, the selected data item selected from the plurality of data items, and a plurality of entity panels displaying data items, each having a respective determined relationship type to the selected data item. 20. The method of claim 16 wherein the data items displayed in one of the plurality of entity panels includes only data items integrated from at least one user selectable source. | 0.66791 |
9,305,552 | 11 | 18 | 11. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: selecting a pair of anchor words in a media presentation based on automatic speech recognition output of the media presentation and a transcription of the media presentation, to yield a selected pair of anchor words, wherein the selected pair of anchor words are separated from one another within the media presentation by a time less than an anchor word time duration requirement; and generating captions by aligning the transcription with the automatic speech recognition output between the selected pair of anchor words. | 11. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: selecting a pair of anchor words in a media presentation based on automatic speech recognition output of the media presentation and a transcription of the media presentation, to yield a selected pair of anchor words, wherein the selected pair of anchor words are separated from one another within the media presentation by a time less than an anchor word time duration requirement; and generating captions by aligning the transcription with the automatic speech recognition output between the selected pair of anchor words. 18. The system of claim 11 , the computer-readable storage medium having instructions stored which, when executed by the processor, result in operations comprising updating an automatic speech recognition dictionary associated with the automatic speech recognition output based on the transcription when the transcription is different from, and more reliable than, the automatic speech recognition output. | 0.5 |
9,235,659 | 15 | 20 | 15. A non-transitory computer-readable medium encoded with executable instructions that, when executed, cause one or more data processing systems to: receive a Computer Aided Design (CAD) model including a plurality of entities; receive a user input including a selection of at least one entity and a movement of the selected entity; apply any basic condition behaviors that correspond to the user input; apply any optional condition behaviors that correspond to the user input; build a variational system to be solved based on the user input, any applied basic condition behaviors, and any optional condition behaviors; perform a variational solve on the variational system to produce an edited CAD model; and store the edited CAD model. | 15. A non-transitory computer-readable medium encoded with executable instructions that, when executed, cause one or more data processing systems to: receive a Computer Aided Design (CAD) model including a plurality of entities; receive a user input including a selection of at least one entity and a movement of the selected entity; apply any basic condition behaviors that correspond to the user input; apply any optional condition behaviors that correspond to the user input; build a variational system to be solved based on the user input, any applied basic condition behaviors, and any optional condition behaviors; perform a variational solve on the variational system to produce an edited CAD model; and store the edited CAD model. 20. The computer-readable medium of claim 15 , wherein the data processing system also discovers geometric conditions of the CAD model including coincident vertices and vertex-on-edge conditions. | 0.696262 |
9,363,195 | 1 | 4 | 1. A method comprising: identifying at least one new resource to add to a cloud, the cloud comprising at least one preexisting resource; creating, by operation of at least one processor, an ontology extension for the at least one new resource including metadata associated with the at least one new resource; creating a relationship between the at least one new resource and the at least one preexisting resource, evaluating the relationship, and storing information regarding the relationship among the metadata included in the ontology extension; and storing the ontology extension. | 1. A method comprising: identifying at least one new resource to add to a cloud, the cloud comprising at least one preexisting resource; creating, by operation of at least one processor, an ontology extension for the at least one new resource including metadata associated with the at least one new resource; creating a relationship between the at least one new resource and the at least one preexisting resource, evaluating the relationship, and storing information regarding the relationship among the metadata included in the ontology extension; and storing the ontology extension. 4. The method of claim 1 , further comprising propagating information with respect to the at least one new resource to the at least one preexisting resource. | 0.6133 |
8,874,555 | 10 | 16 | 10. A system comprising: one or more computers, programmed to perform operations comprising: calculating one or more time trend statistics for a plurality of quality of result statistics for a first document as a search result for a first query, each of the quality of result statistics corresponding to a different time period, the one or more time trend statistics estimating changes in the quality of result statistics over time, wherein each of the one or more time trend statistics include a quality of result difference between a first quality of result statistic for a first document as a search result for a first query during a first time period and a second quality of result statistic for the first document as a search result the first query during a second time period; generating a first modified quality of result statistic by modifying a first quality of result statistic for the first document as a search result for the first query by a factor, where the factor is based on the one or more time trend statistics; and providing the first modified quality of result statistic as an input to a document ranking process for the first document and the first query. | 10. A system comprising: one or more computers, programmed to perform operations comprising: calculating one or more time trend statistics for a plurality of quality of result statistics for a first document as a search result for a first query, each of the quality of result statistics corresponding to a different time period, the one or more time trend statistics estimating changes in the quality of result statistics over time, wherein each of the one or more time trend statistics include a quality of result difference between a first quality of result statistic for a first document as a search result for a first query during a first time period and a second quality of result statistic for the first document as a search result the first query during a second time period; generating a first modified quality of result statistic by modifying a first quality of result statistic for the first document as a search result for the first query by a factor, where the factor is based on the one or more time trend statistics; and providing the first modified quality of result statistic as an input to a document ranking process for the first document and the first query. 16. The system of claim 10 , further programmed to perform operations comprising: identifying a third query as related to the first document based on a quality of result statistic for the third query and the first document; generating a third modified quality of result statistic for the third query and a second document by modifying a quality of result statistic for the third query and the second document by a factor, where the factor is based on the one or more time trend statistics; and providing the third modified quality of result statistic as an input to the document ranking process for the second document and the third query. | 0.5 |
9,390,707 | 1 | 5 | 1. A computer-implemented method for estimating the accuracy of a transcription of a voice recording, comprising: calculating an accuracy number by dividing a number of accurate words in the transcript on by a total number of words in the transcription; assigning a greater weight to at least one word exceeding a predefined number of characters as compared to at least one other word below the predetermined number of characters; automatically extracting using natural language processing, from a data structure that is one of a common language dictionary, customer specific dictionary or a knowledge base, a set of axioms associated with at least one of the words in the transcription, wherein the set of axioms comprises a computer-parsable definition of a relationship of data to the at least one of the words; and assigning a confidence level to each axiom of the set of axioms based on a result of the dividing and the assigning of weight, wherein the confidence level is assigned based on an output of a Gaussian function applied to a result of the dividing and the assigning of weight. | 1. A computer-implemented method for estimating the accuracy of a transcription of a voice recording, comprising: calculating an accuracy number by dividing a number of accurate words in the transcript on by a total number of words in the transcription; assigning a greater weight to at least one word exceeding a predefined number of characters as compared to at least one other word below the predetermined number of characters; automatically extracting using natural language processing, from a data structure that is one of a common language dictionary, customer specific dictionary or a knowledge base, a set of axioms associated with at least one of the words in the transcription, wherein the set of axioms comprises a computer-parsable definition of a relationship of data to the at least one of the words; and assigning a confidence level to each axiom of the set of axioms based on a result of the dividing and the assigning of weight, wherein the confidence level is assigned based on an output of a Gaussian function applied to a result of the dividing and the assigning of weight. 5. The method of claim 1 , further comprising retrieving, from a data structure, a set of axioms associated with at least one of the words in the transcription, wherein the set of axioms comprises a computer-parsable definition of a relationship of data to the at least one of the words. | 0.5 |
7,613,690 | 1 | 14 | 1. A method, performed at least in part by a computer, for identifying a reason that a search topic is popular, the method comprising: receiving an indication of a search topic that is popular, the search topic that is popular being related to a particular entity; in response to receiving the indication of the search topic that is popular, identifying a content feed from an electronic source of published information that includes content published less than a threshold period of time prior to the search topic becoming popular, the content of the content feed including metadata; determining whether the content, of the identified content feed, published less than the threshold period of time prior to the search topic becoming popular is relevant to the search topic; in response to a determination that the content, of the identified content feed, published less than the threshold period of time prior to the search topic becoming popular is relevant to the search topic: analyzing the content, of the identified content feed, published less than the threshold period of time prior to the search topic becoming popular, analyzing the content comprising determining that the content and metadata of the content feed are related to the same particular entity as the search topic; determining a reason that the search topic is popular based on the analysis, determining the reason comprising, when the content identifies the search topic, providing at least some of the content as the reason that the search topic is popular; and presenting to a user the search topic that is popular and the determined reason that the search topic is popular; and summarizing content of more than one content feed when the content of more than one content feed relates to the same particular entity as the search topic. | 1. A method, performed at least in part by a computer, for identifying a reason that a search topic is popular, the method comprising: receiving an indication of a search topic that is popular, the search topic that is popular being related to a particular entity; in response to receiving the indication of the search topic that is popular, identifying a content feed from an electronic source of published information that includes content published less than a threshold period of time prior to the search topic becoming popular, the content of the content feed including metadata; determining whether the content, of the identified content feed, published less than the threshold period of time prior to the search topic becoming popular is relevant to the search topic; in response to a determination that the content, of the identified content feed, published less than the threshold period of time prior to the search topic becoming popular is relevant to the search topic: analyzing the content, of the identified content feed, published less than the threshold period of time prior to the search topic becoming popular, analyzing the content comprising determining that the content and metadata of the content feed are related to the same particular entity as the search topic; determining a reason that the search topic is popular based on the analysis, determining the reason comprising, when the content identifies the search topic, providing at least some of the content as the reason that the search topic is popular; and presenting to a user the search topic that is popular and the determined reason that the search topic is popular; and summarizing content of more than one content feed when the content of more than one content feed relates to the same particular entity as the search topic. 14. The method of claim 1 wherein determining the reason that the search topic is popular comprises determining the reason that the search topic is popular based only on content published less than the threshold period of time prior to the search topic becoming popular. | 0.90189 |
9,176,642 | 1 | 4 | 1. A computer-implemented system for displaying clusters via a dynamic user interface, comprising: a cluster spine module to display cluster spines, each comprising two or more clusters of documents; a compass framing at least a portion of one or more of the cluster spines in the display; a label generation module to generate at least one label to identify a concept of one of the framed cluster spines; a label display module to display the label circumferentially around the compass; and a concept module to change the concept as the compass moves over others of the cluster spines. | 1. A computer-implemented system for displaying clusters via a dynamic user interface, comprising: a cluster spine module to display cluster spines, each comprising two or more clusters of documents; a compass framing at least a portion of one or more of the cluster spines in the display; a label generation module to generate at least one label to identify a concept of one of the framed cluster spines; a label display module to display the label circumferentially around the compass; and a concept module to change the concept as the compass moves over others of the cluster spines. 4. A system according to claim 1 , further comprising: a pinning module to pin the labels displayed circumferentially around the compass. | 0.87724 |
9,280,777 | 5 | 6 | 5. The method of claim 2 , wherein the corresponding recommendation score is calculated based on a likelihood of the one or more solutions to solve the selected at least one new business challenge and a projected cost to implement a solution. | 5. The method of claim 2 , wherein the corresponding recommendation score is calculated based on a likelihood of the one or more solutions to solve the selected at least one new business challenge and a projected cost to implement a solution. 6. The method of claim 5 , wherein the corresponding recommendation score is calculated as a weighted average of the likelihood of the one or more solutions to solve the selected at least one new business challenge and a projected cost to implement the one or more solutions. | 0.5 |
7,774,751 | 10 | 11 | 10. The Knowledge-driven architecture control system of claim 6 , wherein the Success Analysis component propagates via the Communicator to distributed network systems information on a new service API or a new knowledge subject after the first success operation that included the service or the knowledge subject and then after each update provided locally by the Success Analysis component. | 10. The Knowledge-driven architecture control system of claim 6 , wherein the Success Analysis component propagates via the Communicator to distributed network systems information on a new service API or a new knowledge subject after the first success operation that included the service or the knowledge subject and then after each update provided locally by the Success Analysis component. 11. The Knowledge-driven architecture control system of claim 10 , wherein information on new elements is propagated after the first successful operation that included the new element and thereafter after each local update of such information by the Success Analysis component. | 0.5 |
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