patent_num
int64 3.93M
10.2M
| claim_num1
int64 1
519
| claim_num2
int64 2
520
| sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
1
|
|---|---|---|---|---|---|
9,258,373 | 36 | 38 | 36. A method for generating a geofeed based on one or more geofeed parameters, the method being implemented in a computer that includes one or more processors configured to execute one or more computer program modules, the method comprising: obtaining, by the computer, content associated with the geofeed, the content aggregated from a plurality of content providers based on one or more geographically definable locations, the content being provided by the plurality of content providers based on respective requests formatted specifically for individual ones of the plurality of content providers, wherein the respective requests comprise the one or more geographically definable locations; obtaining, by the computer, the one or more geofeed parameters, wherein the one or more geofeed parameters comprise one or more ambient condition parameters or one or more orientation parameters; and communicating, by the computer, the geofeed comprising the content that is filtered in or out based on the geofeed parameters. | 36. A method for generating a geofeed based on one or more geofeed parameters, the method being implemented in a computer that includes one or more processors configured to execute one or more computer program modules, the method comprising: obtaining, by the computer, content associated with the geofeed, the content aggregated from a plurality of content providers based on one or more geographically definable locations, the content being provided by the plurality of content providers based on respective requests formatted specifically for individual ones of the plurality of content providers, wherein the respective requests comprise the one or more geographically definable locations; obtaining, by the computer, the one or more geofeed parameters, wherein the one or more geofeed parameters comprise one or more ambient condition parameters or one or more orientation parameters; and communicating, by the computer, the geofeed comprising the content that is filtered in or out based on the geofeed parameters. 38. The method of claim 36 , the method further comprising: identifying, by the computer, the one or more orientation parameters; determining, by the computer, one or more orientation attributes related to the content; and filtering, by the computer, in or out the content based on the one or more orientation parameters and the one or more orientation attributes related to the content. | 0.610664 |
8,732,214 | 10 | 11 | 10. A computer-readable medium embodied in a non-transient, physical memory device having stored thereon computer executable instructions for searching a product model number database comprising a plurality of product model numbers, the instructions performing steps comprising: receiving a string to be searched in the product model number database from a client device; creating multiple queries based on the string, at least two of the queries being selected from the group consisting of: a search for product model numbers beginning with the string; a search for product model numbers ending with the string; a search for product model numbers containing the string; or a search for product model numbers beginning with one or more leading zeroes followed by the string; querying the model number database using the created queries; receiving query results from the model number database responsive to the created queries; and transmitting the query results to the client device. | 10. A computer-readable medium embodied in a non-transient, physical memory device having stored thereon computer executable instructions for searching a product model number database comprising a plurality of product model numbers, the instructions performing steps comprising: receiving a string to be searched in the product model number database from a client device; creating multiple queries based on the string, at least two of the queries being selected from the group consisting of: a search for product model numbers beginning with the string; a search for product model numbers ending with the string; a search for product model numbers containing the string; or a search for product model numbers beginning with one or more leading zeroes followed by the string; querying the model number database using the created queries; receiving query results from the model number database responsive to the created queries; and transmitting the query results to the client device. 11. The computer-readable medium as recited in claim 10 , wherein at least three of the queries are selected from the group consisting of: a search for product model numbers beginning with the string; a search for product model numbers ending with the string; a search for product model numbers containing the string; or a search for product model numbers beginning with one or more leading zeroes followed by the string. | 0.597514 |
10,003,923 | 1 | 10 | 1. A method performed by a computer server for inferring location context categories for a set of mobile users having at least two members, comprising: for each mobile user in the set, obtaining at least one location context category; and applying multi-user collaborative machine learning with an objective function to the at least one location context category for each mobile user in the set to infer a single refined location context category for each mobile user in the set to form a matrix. | 1. A method performed by a computer server for inferring location context categories for a set of mobile users having at least two members, comprising: for each mobile user in the set, obtaining at least one location context category; and applying multi-user collaborative machine learning with an objective function to the at least one location context category for each mobile user in the set to infer a single refined location context category for each mobile user in the set to form a matrix. 10. A non-transitory article of manufacture tangibly embodying a computer readable program which when executed causes a computer to perform the steps of claim 1 . | 0.844231 |
9,600,562 | 1 | 7 | 1. A computer-implemented method for importing data for an Entity Relationship (E-R) model, the method comprising: receiving, by using a computer system, an exported E-R model data file and a data schema of the E-R model; determining a dependency type of an entity in the exported E-R model data file based on the data schema, wherein the dependency type corresponds to at least one of no correlation, weak correlation, and strong correlation; importing the entity in the exported E-R model data file based on the determined dependency type, wherein the importing the entity in the exported E-R model data file based on the determined dependency type includes: determining whether the imported entity with no correlation or weak correlation affects an entity recorded in a strong correlation table; responsive to the determined dependency type of the entity being at least one of weak correlation and no correlation, directly importing the entity; and responsive to the determined dependency type of the entity being strong correlation, storing the entity in the strong correlation table and deferring the importing of the entity until a minimum reference number of the strong correlation of the entity is satisfied; and responsive to the determination that the imported entity with no correlation or weak correlation affects the entity recorded in the strong correlation table, importing the entity recorded in the strong correlation table and deleting the entity recorded in the strong correlation table from the strong correlation table. | 1. A computer-implemented method for importing data for an Entity Relationship (E-R) model, the method comprising: receiving, by using a computer system, an exported E-R model data file and a data schema of the E-R model; determining a dependency type of an entity in the exported E-R model data file based on the data schema, wherein the dependency type corresponds to at least one of no correlation, weak correlation, and strong correlation; importing the entity in the exported E-R model data file based on the determined dependency type, wherein the importing the entity in the exported E-R model data file based on the determined dependency type includes: determining whether the imported entity with no correlation or weak correlation affects an entity recorded in a strong correlation table; responsive to the determined dependency type of the entity being at least one of weak correlation and no correlation, directly importing the entity; and responsive to the determined dependency type of the entity being strong correlation, storing the entity in the strong correlation table and deferring the importing of the entity until a minimum reference number of the strong correlation of the entity is satisfied; and responsive to the determination that the imported entity with no correlation or weak correlation affects the entity recorded in the strong correlation table, importing the entity recorded in the strong correlation table and deleting the entity recorded in the strong correlation table from the strong correlation table. 7. The method according to claim 1 , further comprising: responsive to all entities in the E-R model data file having been completely processed, generating an update request for all rows in a weak correlation table, so as to update dependency information of each imported entity. | 0.824307 |
8,996,975 | 2 | 4 | 2. The method of claim 1 , further comprising presenting a beginning of the frame on a display of the device. | 2. The method of claim 1 , further comprising presenting a beginning of the frame on a display of the device. 4. The method of claim 2 , wherein presenting the relevant portion comprises presenting the Web page starting at the beginning of the relevant portion, without scrolling the Web page. | 0.817365 |
7,672,841 | 1 | 9 | 1. A method of processing speech data from an utterance for a distributed speech query recognition system comprising the steps of: establishing a network connection between a server computing system and a client device suitable for transporting a streaming communication; receiving a continuous speech byte data stream containing speech data processed by a first component of the distributed speech query recognition system situated in the client device; wherein said speech data is characterized by a form and data content representing only a partial recognition of an utterance; further wherein said data stream includes NULL data used to identify a silence in speech data from said client device said NULL data being inserted at the client device after other NULL data is removed prior to transmission of the speech byte data stream; and further processing said speech data at a second component of the distributed speech query recognition system situated at said server computing system to generate additional speech related content and complete recognition of words in said speech data. | 1. A method of processing speech data from an utterance for a distributed speech query recognition system comprising the steps of: establishing a network connection between a server computing system and a client device suitable for transporting a streaming communication; receiving a continuous speech byte data stream containing speech data processed by a first component of the distributed speech query recognition system situated in the client device; wherein said speech data is characterized by a form and data content representing only a partial recognition of an utterance; further wherein said data stream includes NULL data used to identify a silence in speech data from said client device said NULL data being inserted at the client device after other NULL data is removed prior to transmission of the speech byte data stream; and further processing said speech data at a second component of the distributed speech query recognition system situated at said server computing system to generate additional speech related content and complete recognition of words in said speech data. 9. The method of claim 1 , wherein said speech data only includes NULL data during periods of silence. | 0.793522 |
8,015,131 | 1 | 2 | 1. A method performed by a computing system for learning tradeoffs between discriminative power and invariance of classifiers, comprising: receiving two or more classifiers, each classifier for classifying data and having associated therewith a kernel with corresponding kernel weight, the kernel specifying an attribute for its associated classifier; employing a learning technique to produce a combined classifier based on the two or more received classifiers by decreasing a function of the kernel weights to learn tradeoffs between discriminative power and invariance; generating by the computing system a base kernel for each of the received two or more classifiers; and selecting one of the generated base kernels by solving a convex optimization problem having a linear objective and quadratic inequality constraints. | 1. A method performed by a computing system for learning tradeoffs between discriminative power and invariance of classifiers, comprising: receiving two or more classifiers, each classifier for classifying data and having associated therewith a kernel with corresponding kernel weight, the kernel specifying an attribute for its associated classifier; employing a learning technique to produce a combined classifier based on the two or more received classifiers by decreasing a function of the kernel weights to learn tradeoffs between discriminative power and invariance; generating by the computing system a base kernel for each of the received two or more classifiers; and selecting one of the generated base kernels by solving a convex optimization problem having a linear objective and quadratic inequality constraints. 2. The method of claim 1 wherein the employing the learning technique includes: producing a linear combination of the generated base kernels that corresponds to the combined classifier. | 0.783372 |
9,760,549 | 9 | 21 | 9. A system for processing XML documents, comprising: processing resources including at least one processor, a memory, and a non-transitory computer readable storage medium; wherein the processing resources are configured to: parse an XML document into a plurality of constituent nodes, the XML document including a plurality of Document Object Model (DOM) objects representable in accordance with an object model; store the parsed constituent nodes and associated metadata in a plurality of partitions, wherein a first node of the parsed constituent nodes and associated metadata is stored in a first partition of the plurality of partitions and a second node of the parsed constituent nodes and associated metadata is stored in a second partition of the plurality of partitions, and each said partition having an associated commit level that initially is set to 0; store, for each said partition, an identifier thereof in a partition table list, the identifier(s) in the partition table list collectively identifying the working contents of the XML document, the partition table list initially being designated as a current partition table list and initially being designated as having a current commit level of 0; in response to a request for an atomic update to the XML document: push onto a stack, configured to hold one or more previous partition table lists, a copy of the current partition table list; increment the current commit level; determine whether a given partition's contents are changed as a result of the atomic update and whether the commit level associated with the given partition does not match the current commit level; and when a given partition's contents are changed as a result of the atomic update and the commit level associated with the given partition does not match the current commit level, copy the given partition's contents to create a new partition with the changed contents and replace the identifier for the given partition in the current partition table list with an identifier for the new partition; and in response to an atomic update being completed: pop from the stack the uppermost partition table list, the popped partition table list being a candidate partition table list; determine partitions in the current partition table list that have associated commit levels that match the current commit level into the candidate partition table list; copy identifiers for any partitions in the current partition table list that have associated commit levels that match the current commit level into the candidate partition table list; replace the current partition table list with the candidate list; and decrement the current commit level. | 9. A system for processing XML documents, comprising: processing resources including at least one processor, a memory, and a non-transitory computer readable storage medium; wherein the processing resources are configured to: parse an XML document into a plurality of constituent nodes, the XML document including a plurality of Document Object Model (DOM) objects representable in accordance with an object model; store the parsed constituent nodes and associated metadata in a plurality of partitions, wherein a first node of the parsed constituent nodes and associated metadata is stored in a first partition of the plurality of partitions and a second node of the parsed constituent nodes and associated metadata is stored in a second partition of the plurality of partitions, and each said partition having an associated commit level that initially is set to 0; store, for each said partition, an identifier thereof in a partition table list, the identifier(s) in the partition table list collectively identifying the working contents of the XML document, the partition table list initially being designated as a current partition table list and initially being designated as having a current commit level of 0; in response to a request for an atomic update to the XML document: push onto a stack, configured to hold one or more previous partition table lists, a copy of the current partition table list; increment the current commit level; determine whether a given partition's contents are changed as a result of the atomic update and whether the commit level associated with the given partition does not match the current commit level; and when a given partition's contents are changed as a result of the atomic update and the commit level associated with the given partition does not match the current commit level, copy the given partition's contents to create a new partition with the changed contents and replace the identifier for the given partition in the current partition table list with an identifier for the new partition; and in response to an atomic update being completed: pop from the stack the uppermost partition table list, the popped partition table list being a candidate partition table list; determine partitions in the current partition table list that have associated commit levels that match the current commit level into the candidate partition table list; copy identifiers for any partitions in the current partition table list that have associated commit levels that match the current commit level into the candidate partition table list; replace the current partition table list with the candidate list; and decrement the current commit level. 21. The system of claim 9 , wherein each of the partitions is cacheable and is encoded. | 0.940977 |
9,690,758 | 17 | 18 | 17. The system of claim 16 , wherein the mobile device further comprises a display, wherein the display is configured to: output, when displaying a list of e-books with auxiliary content, identification marks indicating e-books that have auxiliary content, and output at least one of a list output screen or a text output screen, wherein the list output screen shows, when the e-book has e-book auxiliary content, pages and words, serving as items, included in the e-book auxiliary content, according to a user's inputs, and wherein the text output screen shows the words to which the e-book auxiliary content are applied, displayed differently from other words on a same page of the e-book. | 17. The system of claim 16 , wherein the mobile device further comprises a display, wherein the display is configured to: output, when displaying a list of e-books with auxiliary content, identification marks indicating e-books that have auxiliary content, and output at least one of a list output screen or a text output screen, wherein the list output screen shows, when the e-book has e-book auxiliary content, pages and words, serving as items, included in the e-book auxiliary content, according to a user's inputs, and wherein the text output screen shows the words to which the e-book auxiliary content are applied, displayed differently from other words on a same page of the e-book. 18. The system of claim 17 , wherein, when a particular item comprising the word and page is selected on the list output screen, the display is further configured to output at least one of: sub-items included in the selected item; or information regarding a map that displays information regarding a route connecting a place location corresponding to a word, selected on a previous page, to a place location corresponding to the currently selected word on the currently selected page. | 0.781391 |
8,949,255 | 16 | 17 | 16. A data storage system for storing at least one file generated by a distributed application in a parallel computing system, wherein said file comprises a plurality of sub-files, comprising: a hardware processing device for obtaining a user specification of semantic information related to said file; determining semantically meaningful sub-file boundaries for said plurality of sub-files based on said semantic information; and for providing said semantic information as a data structure description to a data formatting library write function, wherein said semantic information is dependent upon a content of said file; and a memory for storing said semantic information related to said file with additional metadata related to said file and with one or more of said sub-files using said determined semantically meaningful sub-file boundaries in one or more storage nodes of said parallel computing system. | 16. A data storage system for storing at least one file generated by a distributed application in a parallel computing system, wherein said file comprises a plurality of sub-files, comprising: a hardware processing device for obtaining a user specification of semantic information related to said file; determining semantically meaningful sub-file boundaries for said plurality of sub-files based on said semantic information; and for providing said semantic information as a data structure description to a data formatting library write function, wherein said semantic information is dependent upon a content of said file; and a memory for storing said semantic information related to said file with additional metadata related to said file and with one or more of said sub-files using said determined semantically meaningful sub-file boundaries in one or more storage nodes of said parallel computing system. 17. The data storage system of claim 16 , wherein said semantic information provides a description of data in said file. | 0.679144 |
10,061,862 | 15 | 16 | 15. A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process to create a compact tree node representation of an extensible markup language (XML) document, the process comprising: creating a compact tree node representation of an extensible markup language (XML) document by: allocating a first portion of memory of a main memory of a computer to store a first memory block for storing an in-memory instance of an XML tree index data structure for the XML document, the in-memory instance of the XML tree index data structure comprising an array of rows in which each row holds a node identifier, one or more pointers referencing to one or more children nodes, and not comprising node data, wherein the node data are contents of the XML document corresponding to respective nodes; allocating a second portion of the memory of the main memory of the computer to store one or more separate data structures for storing at least a portion of the node data for the XML document, the one or more separate data structures each storing a different type of node data; traversing the XML document from a first node to a final node and through at least one intermediate node; and processing traversed nodes of the XML document, the processing comprising: in determining a traversed node is an element node, adding the element node to the first portion of the main memory and copying an element name of the element node into the one or more separate data structures for storing at least a portion of the node data; in determining the traversed node is a text node, populating a text node index into the first portion of the main memory and copying text node values into the one or more separate data structures for storing at least a portion of the node data, the text node values copied being accessible via the text node index; in determining the traversed node is an attribute node, populating an attribute node index into the first portion of the main memory and copying an attribute name and attribute value into the one or more separate data structures, the attribute value copied being accessible via the attribute node index. | 15. A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process to create a compact tree node representation of an extensible markup language (XML) document, the process comprising: creating a compact tree node representation of an extensible markup language (XML) document by: allocating a first portion of memory of a main memory of a computer to store a first memory block for storing an in-memory instance of an XML tree index data structure for the XML document, the in-memory instance of the XML tree index data structure comprising an array of rows in which each row holds a node identifier, one or more pointers referencing to one or more children nodes, and not comprising node data, wherein the node data are contents of the XML document corresponding to respective nodes; allocating a second portion of the memory of the main memory of the computer to store one or more separate data structures for storing at least a portion of the node data for the XML document, the one or more separate data structures each storing a different type of node data; traversing the XML document from a first node to a final node and through at least one intermediate node; and processing traversed nodes of the XML document, the processing comprising: in determining a traversed node is an element node, adding the element node to the first portion of the main memory and copying an element name of the element node into the one or more separate data structures for storing at least a portion of the node data; in determining the traversed node is a text node, populating a text node index into the first portion of the main memory and copying text node values into the one or more separate data structures for storing at least a portion of the node data, the text node values copied being accessible via the text node index; in determining the traversed node is an attribute node, populating an attribute node index into the first portion of the main memory and copying an attribute name and attribute value into the one or more separate data structures, the attribute value copied being accessible via the attribute node index. 16. The computer program product of claim 15 , further comprising determining when the intermediate node is a text node that has already been copied to the node data, and then not copying the text node to the node data. | 0.894101 |
9,465,848 | 1 | 9 | 1. A method comprising, by one or more computing devices: receiving from a first user of an online social network an unstructured text query, the online social network being associated with a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes; parsing the text query to identify one or more n-grams; determining a score for each n-gram that the n-gram corresponds to an edge or a node, wherein the score for each n-gram is a probability that the n-gram corresponds to an edge or a node; identifying one or more edges and one or more nodes based on their scores, each identified node and identified edge corresponding to at least one of the n-grams, each of the identified nodes being connected to at least one of the identified edges; and generating one or more structured queries that each comprise references to one or more of the identified edges and one or more of the identified nodes. | 1. A method comprising, by one or more computing devices: receiving from a first user of an online social network an unstructured text query, the online social network being associated with a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes; parsing the text query to identify one or more n-grams; determining a score for each n-gram that the n-gram corresponds to an edge or a node, wherein the score for each n-gram is a probability that the n-gram corresponds to an edge or a node; identifying one or more edges and one or more nodes based on their scores, each identified node and identified edge corresponding to at least one of the n-grams, each of the identified nodes being connected to at least one of the identified edges; and generating one or more structured queries that each comprise references to one or more of the identified edges and one or more of the identified nodes. 9. The method of claim 1 , wherein each n-gram comprises one or more characters of text entered by the first user. | 0.884381 |
6,047,253 | 5 | 11 | 5. A method for decoding an encoded speech signal obtained by sinusoidal analytic encoding of an input speech signal, comprising the steps of: deciding whether the input speech signal is voiced or unvoiced; and adding a noise component to a sinusoidal synthesis waveform based on pitch intensity information as a parameter of pitch intensity detected in all bands of a voiced speech portion of the input speech signal on the basis of results of the step of deciding whether the input speech signal is voiced or unvoiced. | 5. A method for decoding an encoded speech signal obtained by sinusoidal analytic encoding of an input speech signal, comprising the steps of: deciding whether the input speech signal is voiced or unvoiced; and adding a noise component to a sinusoidal synthesis waveform based on pitch intensity information as a parameter of pitch intensity detected in all bands of a voiced speech portion of the input speech signal on the basis of results of the step of deciding whether the input speech signal is voiced or unvoiced. 11. The speech decoding method as claimed in claim 5, wherein a portion of the encoded speech signal decided to be voiced is decoded by sinusoidal synthesis decoding, and a portion of the encoded speech signal decided to be unvoiced is decoded by code excitation linear predictive decoding. | 0.751286 |
5,577,165 | 21 | 30 | 21. A method of speech dialogue between a human user and a speech dialogue system, comprising the steps of: understanding an input speech from a user; determining a response output according to the input speech; generating a speech response and a visual response according to the response output; and outputting the speech response and the visual response generated to the user. | 21. A method of speech dialogue between a human user and a speech dialogue system, comprising the steps of: understanding an input speech from a user; determining a response output according to the input speech; generating a speech response and a visual response according to the response output; and outputting the speech response and the visual response generated to the user. 30. The method of claim 21, wherein the generating step generates the visual response which includes a content visualizing image formed by pictures of objects mentioned in the speech response and a numerical figure indicating a quantity of each of the objects. | 0.794629 |
8,317,613 | 16 | 25 | 16. A processor-implemented method for social interactive content development of a plurality of art assets for an interactive video game, comprising: determining proximity relationships amongst the plurality of art assets, each of the art assets being defined for display during execution of the interactive video game; monitoring access to the plurality of art assets; initiating a communication in response to triggering a predefined access threshold set for a specific art asset based on a proximity relationship of the specific art asset to a proximate art asset; wherein the method is executed by a processor. | 16. A processor-implemented method for social interactive content development of a plurality of art assets for an interactive video game, comprising: determining proximity relationships amongst the plurality of art assets, each of the art assets being defined for display during execution of the interactive video game; monitoring access to the plurality of art assets; initiating a communication in response to triggering a predefined access threshold set for a specific art asset based on a proximity relationship of the specific art asset to a proximate art asset; wherein the method is executed by a processor. 25. The method of claim 16 , further comprising displaying proximate art assets overlaid upon each other. | 0.913366 |
8,195,447 | 1 | 8 | 1. A method for a computer system to represent the meaning of a source sentence from a source language, the method comprising: obtaining a language-independent semantic structure to represent the meaning of the source sentence; synthesizing a syntactic structure of an output sentence from the language independent semantic structure using information which includes semantic descriptions, lexical descriptions of an output language, syntactic descriptions of the output language, and morphological descriptions of the output language, wherein the syntactic structure is built at least in part based on ratings of syntactic constructions for each element of the source sentence; and constructing the output sentence to represent the meaning of the source sentence in the output language by performing a lexical selection on the language-independent semantic structure of the sentence using lexical descriptions of the output language and semantic descriptions, wherein performing the lexical selection further comprises applying one or more semantic structure correction rules to overcome asymmetries between the language-independent semantic structure and the syntactic structure of the output sentence in the output language, and wherein applying one or more semantic structure correction rules to overcome asymmetries includes the use of one or more semanteme calculating rules and one or more semanteme normalization rules. | 1. A method for a computer system to represent the meaning of a source sentence from a source language, the method comprising: obtaining a language-independent semantic structure to represent the meaning of the source sentence; synthesizing a syntactic structure of an output sentence from the language independent semantic structure using information which includes semantic descriptions, lexical descriptions of an output language, syntactic descriptions of the output language, and morphological descriptions of the output language, wherein the syntactic structure is built at least in part based on ratings of syntactic constructions for each element of the source sentence; and constructing the output sentence to represent the meaning of the source sentence in the output language by performing a lexical selection on the language-independent semantic structure of the sentence using lexical descriptions of the output language and semantic descriptions, wherein performing the lexical selection further comprises applying one or more semantic structure correction rules to overcome asymmetries between the language-independent semantic structure and the syntactic structure of the output sentence in the output language, and wherein applying one or more semantic structure correction rules to overcome asymmetries includes the use of one or more semanteme calculating rules and one or more semanteme normalization rules. 8. The method of claim 1 , wherein the syntactic structure of the sentence includes deep slots and lexical meanings, wherein the language-independent semantic structure is generated by: (1) substituting each lexical meaning of the sentence in the source language with a corresponding language-independent semantic class, (2) confirming a linear order of lexical meanings, and (3) after the linear order is confirmed, deleting surface slots when generating the language-independent semantic structure, and wherein only deep slots and deep slot descriptions are used to build the language-independent semantic structure of the sentence. | 0.500787 |
7,599,831 | 1 | 5 | 1. A method for converting a natural language communication, said method comprising: a computer processor searching a natural language communication to identify words in said communication contained in a vocabulary database of words, wherein each of said database words is representable by a designated word semantic symbol and multiple different words in the vocabulary database determined to have a similar meaning are represented by the same semantic symbol in the vocabulary database; expressing said communication in terms of word semantic symbols from the vocabulary database that correspond to each of said words identified in said communication; searching said communication when expressed in terms of word semantic symbols so as to identify phrases in said communication contained in a phrase database of phrases, wherein each of said database phrases is representable by a designated phrase semantic symbol and multiple different phrases in the phrase database determined to have a similar meaning are represented by the same semantic symbol in the phrase database; expressing said communication in terms of phrase semantic symbols from the phrase database that correspond to each of said phrases identified in said communication; searching said communication when expressed in terms of the phrase semantic symbols so as to identify concepts in said communication; and expressing said communication in terms of concept semantic symbols that correspond to each of said concepts identified in said communication. | 1. A method for converting a natural language communication, said method comprising: a computer processor searching a natural language communication to identify words in said communication contained in a vocabulary database of words, wherein each of said database words is representable by a designated word semantic symbol and multiple different words in the vocabulary database determined to have a similar meaning are represented by the same semantic symbol in the vocabulary database; expressing said communication in terms of word semantic symbols from the vocabulary database that correspond to each of said words identified in said communication; searching said communication when expressed in terms of word semantic symbols so as to identify phrases in said communication contained in a phrase database of phrases, wherein each of said database phrases is representable by a designated phrase semantic symbol and multiple different phrases in the phrase database determined to have a similar meaning are represented by the same semantic symbol in the phrase database; expressing said communication in terms of phrase semantic symbols from the phrase database that correspond to each of said phrases identified in said communication; searching said communication when expressed in terms of the phrase semantic symbols so as to identify concepts in said communication; and expressing said communication in terms of concept semantic symbols that correspond to each of said concepts identified in said communication. 5. The method of claim 1 , wherein the natural language communication comprises a user instruction to a computer system, and the method further comprises: determining the instruction from the identified concepts. | 0.790099 |
8,554,723 | 1 | 2 | 1. A computer-implemented method of matching users to other users, the method comprising: storing, in computer storage, event data comprising order data reflective of items ordered from an electronic catalog by each of a plurality of users; programmatically generating a score that reflects a degree to which item preferences of a first user of said plurality of users are similar to item preferences of a second user of said plurality of users, said score taking into consideration a first plurality of items ordered by the first user, a second plurality of items ordered by the second user, and a type of one or more of the items ordered in common between the first and second users, said score further taking into consideration at least one additional type of event data reflective of user affinities for items represented in the electronic catalog, wherein generating the score further comprises accessing item similarity data to determine whether an item ordered by the first user is similar to an item ordered by the second user; and based at least in part on the score, programmatically determining whether to recommend the second user to the first user. | 1. A computer-implemented method of matching users to other users, the method comprising: storing, in computer storage, event data comprising order data reflective of items ordered from an electronic catalog by each of a plurality of users; programmatically generating a score that reflects a degree to which item preferences of a first user of said plurality of users are similar to item preferences of a second user of said plurality of users, said score taking into consideration a first plurality of items ordered by the first user, a second plurality of items ordered by the second user, and a type of one or more of the items ordered in common between the first and second users, said score further taking into consideration at least one additional type of event data reflective of user affinities for items represented in the electronic catalog, wherein generating the score further comprises accessing item similarity data to determine whether an item ordered by the first user is similar to an item ordered by the second user; and based at least in part on the score, programmatically determining whether to recommend the second user to the first user. 2. The method of claim 1 , wherein the score reflects a degree to which the first plurality of items and the second plurality of items are related. | 0.880875 |
9,378,209 | 11 | 14 | 11. A system comprising: at least one processor; and a non-transitory computer-readable storage medium to store a plurality of instructions that are executable by the at least one processor to perform acts comprising: receiving, from a user, a query comprising a quote from a television show; identifying the television show associated with the quote; determining a location of the quote within the television show based on one or more of a television quote index database, a transcribed television episode database, a full video television episode database, or a television trailer database; and providing a video segment in response to the query, the video segment comprising at least a portion of the television show that includes the quote. | 11. A system comprising: at least one processor; and a non-transitory computer-readable storage medium to store a plurality of instructions that are executable by the at least one processor to perform acts comprising: receiving, from a user, a query comprising a quote from a television show; identifying the television show associated with the quote; determining a location of the quote within the television show based on one or more of a television quote index database, a transcribed television episode database, a full video television episode database, or a television trailer database; and providing a video segment in response to the query, the video segment comprising at least a portion of the television show that includes the quote. 14. The system of claim 11 , wherein the acts further comprise: storing the video segment in a database; and providing the video segment in response to receiving a subsequent query that includes the quote from the television show. | 0.736239 |
9,396,269 | 14 | 16 | 14. A computer-implemented method comprising: performing an analysis of at least one of terms or phrases of searches performed by a plurality of members of a social network to infer interests of the plurality of members; determining, based on the analysis, that a first number of the searches is associated with a first topic of interest, the first number of the searches being performed by a first group of members included in the social network; determining, based on the analysis, that a second number of the searches is associated with a second topic of interest, the second number of the searches being performed by a second group of members included in the social network; receiving a search query from a user; in response to receiving the search query: determining, by a computer, search results responsive to the search query; returning, by the computer, the determined search results; accessing, by the computer, a database of mapping information, wherein the mapping information maps the first group of members included in the social network with the first topic of interest and the second group of members included in the social network with the second topic of interest; forming, by the computer and in the database, a first subnetwork of the social network, the first subnetwork including the first group of members included in the social network; forming, by the computer and in the database, a second subnetwork of the social network, the second subnetwork including the second group of members included in the social network; determining, by the computer, that the search query matches the first topic of interest; and returning, by the computer and at least partly in response to determining that the search query matches the first topic of interest, a link to at least one member of the first subnetwork of the social network. | 14. A computer-implemented method comprising: performing an analysis of at least one of terms or phrases of searches performed by a plurality of members of a social network to infer interests of the plurality of members; determining, based on the analysis, that a first number of the searches is associated with a first topic of interest, the first number of the searches being performed by a first group of members included in the social network; determining, based on the analysis, that a second number of the searches is associated with a second topic of interest, the second number of the searches being performed by a second group of members included in the social network; receiving a search query from a user; in response to receiving the search query: determining, by a computer, search results responsive to the search query; returning, by the computer, the determined search results; accessing, by the computer, a database of mapping information, wherein the mapping information maps the first group of members included in the social network with the first topic of interest and the second group of members included in the social network with the second topic of interest; forming, by the computer and in the database, a first subnetwork of the social network, the first subnetwork including the first group of members included in the social network; forming, by the computer and in the database, a second subnetwork of the social network, the second subnetwork including the second group of members included in the social network; determining, by the computer, that the search query matches the first topic of interest; and returning, by the computer and at least partly in response to determining that the search query matches the first topic of interest, a link to at least one member of the first subnetwork of the social network. 16. The method of claim 14 , further comprising presenting an advertisement to at least one of the members of the social network based on the search query. | 0.852381 |
9,430,495 | 8 | 12 | 8. A computer implemented method comprising: identifying a plurality of entries from a location store associated with a physical location within an area, each entry in the location store including a physical location description and one or more terms associated with the physical location description; identifying one or more terms in the identified plurality of entries having an associated number of occurrences within the plurality of entries that exceeds an associated number of occurrences within the location store by at least a threshold amount as trending terms; generating a score for an entry from the plurality of entries based at least in part on one or more difference between terms in the entry from the plurality of entries and terms in an additional entry from a plurality of entries and whether a term in the entry differing from a term in the additional entry is a trending term; and generating a combined entry including terms from the entry and from the additional entry if the score is less than a threshold value. | 8. A computer implemented method comprising: identifying a plurality of entries from a location store associated with a physical location within an area, each entry in the location store including a physical location description and one or more terms associated with the physical location description; identifying one or more terms in the identified plurality of entries having an associated number of occurrences within the plurality of entries that exceeds an associated number of occurrences within the location store by at least a threshold amount as trending terms; generating a score for an entry from the plurality of entries based at least in part on one or more difference between terms in the entry from the plurality of entries and terms in an additional entry from a plurality of entries and whether a term in the entry differing from a term in the additional entry is a trending term; and generating a combined entry including terms from the entry and from the additional entry if the score is less than a threshold value. 12. The computer implemented method of claim 8 , wherein identifying one or more terms in the identified plurality of entries having the associated number of occurrences within the plurality of entries that exceeds the associated number of occurrences within the location store by at least the threshold amount as trending terms comprises: identifying one or more terms associated with a ratio of the number of occurrences within the plurality of entries to the number of occurrences within the location store that equals or exceeds a specified value as one or more trending terms. | 0.756087 |
7,762,816 | 17 | 21 | 17. A computer-implemented system for developing a translation exercise, the system comprising: a processing system; and a computer-readable memory coupled to the processing system, the computer-readable memory containing one or more programming instructions, the programming instructions when executed causing the processing system to execute steps comprising: receiving a grammatical structure; for each of a plurality of text segments in a first language, translating the text segment in the first language into a corresponding text segment in a second language using a data processor; and selecting a selected text segment from the plurality of text segments as a prompt for a translation exercise based on whether the text segment in the second language that corresponds to the selected text segment has said grammatical structure using a data processor; and storing the selected text segment in a computer-readable memory. | 17. A computer-implemented system for developing a translation exercise, the system comprising: a processing system; and a computer-readable memory coupled to the processing system, the computer-readable memory containing one or more programming instructions, the programming instructions when executed causing the processing system to execute steps comprising: receiving a grammatical structure; for each of a plurality of text segments in a first language, translating the text segment in the first language into a corresponding text segment in a second language using a data processor; and selecting a selected text segment from the plurality of text segments as a prompt for a translation exercise based on whether the text segment in the second language that corresponds to the selected text segment has said grammatical structure using a data processor; and storing the selected text segment in a computer-readable memory. 21. The system of claim 17 wherein the one or more text segments in the first language comprise a sentence. | 0.856952 |
8,533,222 | 14 | 19 | 14. A computer-readable storage device encoded with a computer program product, the computer program product comprising instructions that when executed on one or more computers cause the one or more computers to perform operations comprising: receiving, over a network, client training data comprising a first plurality of training data sets belonging to a client entity; generating a plurality of trained predictive models using a plurality of training functions and a first sample of the client training data; determining a respective accuracy of each of the plurality of trained predictive models using a different, second sample of the client training data; receiving, over the network one or more new training data sets belonging to the client entity, wherein each of the one or more new training data sets is new relative to the first plurality of training data sets; updating the client training data to include the one or more new training data sets; generating a plurality of new trained predictive models using the plurality of training functions and a different, third sample of the client training data; determining, a respective accuracy of each of the plurality of new trained predictive models using a different, fourth sample of the client training data; generating a respective effectiveness score for each of the plurality of trained predictive models and each of the plurality of new trained predictive models using the determined accuracy of its respective trained predictive model; receiving, over the network from a client computing system, a first prediction request and first input data; selecting a first trained predictive model to service the first prediction request from among the plurality of trained predictive models and the plurality of new trained predictive models based on the respective effectiveness scores; running the first trained predictive model on the first input data to generate a predictive output; and providing, to the client computing system, the predictive output in response to the first prediction request. | 14. A computer-readable storage device encoded with a computer program product, the computer program product comprising instructions that when executed on one or more computers cause the one or more computers to perform operations comprising: receiving, over a network, client training data comprising a first plurality of training data sets belonging to a client entity; generating a plurality of trained predictive models using a plurality of training functions and a first sample of the client training data; determining a respective accuracy of each of the plurality of trained predictive models using a different, second sample of the client training data; receiving, over the network one or more new training data sets belonging to the client entity, wherein each of the one or more new training data sets is new relative to the first plurality of training data sets; updating the client training data to include the one or more new training data sets; generating a plurality of new trained predictive models using the plurality of training functions and a different, third sample of the client training data; determining, a respective accuracy of each of the plurality of new trained predictive models using a different, fourth sample of the client training data; generating a respective effectiveness score for each of the plurality of trained predictive models and each of the plurality of new trained predictive models using the determined accuracy of its respective trained predictive model; receiving, over the network from a client computing system, a first prediction request and first input data; selecting a first trained predictive model to service the first prediction request from among the plurality of trained predictive models and the plurality of new trained predictive models based on the respective effectiveness scores; running the first trained predictive model on the first input data to generate a predictive output; and providing, to the client computing system, the predictive output in response to the first prediction request. 19. The computer-readable storage device of claim 14 , wherein the third sample of client training data does not include any of the training data sets included in the first plurality of training data sets. | 0.921636 |
9,824,161 | 1 | 3 | 1. A computer-implemented method comprising: obtaining search results for a search query, each search result referencing a respective webpage resource, the respective resources including a first webpage resource and a second webpage resource, and each of the webpage resources being different from each other resource; for each webpage resource referenced by the search results obtained: identifying, within the webpage resource, structured data; identifying, for the webpage resource, a topic of the webpage resource; determining, from the structured data within the webpage resource, textual values included in the structured data and, for each textual value, an associated property value; wherein multiple topics are identified for the webpage resources; determining a textual value as a consistent value based on a number of different webpage resources that each have a matching topic and that include structured data having an identical textual value and an identical associated property value determined from the structured data, wherein the number of different webpage resources is exclusive of the webpage resources referenced by the search results that do not have a topic that matches the matching topic; and in response to determining a consistent value, providing (i) a representation of the consistent value as a possible answer to the search query, and (ii) the search results. | 1. A computer-implemented method comprising: obtaining search results for a search query, each search result referencing a respective webpage resource, the respective resources including a first webpage resource and a second webpage resource, and each of the webpage resources being different from each other resource; for each webpage resource referenced by the search results obtained: identifying, within the webpage resource, structured data; identifying, for the webpage resource, a topic of the webpage resource; determining, from the structured data within the webpage resource, textual values included in the structured data and, for each textual value, an associated property value; wherein multiple topics are identified for the webpage resources; determining a textual value as a consistent value based on a number of different webpage resources that each have a matching topic and that include structured data having an identical textual value and an identical associated property value determined from the structured data, wherein the number of different webpage resources is exclusive of the webpage resources referenced by the search results that do not have a topic that matches the matching topic; and in response to determining a consistent value, providing (i) a representation of the consistent value as a possible answer to the search query, and (ii) the search results. 3. The method of claim 1 , wherein determining a textual value as a consistent value is based, in part, on records of user selections in response to previously providing information from structured data. | 0.793699 |
10,091,248 | 1 | 8 | 1. A method comprising: receiving, by a first stage of a context-aware hardware accelerator of a network security device, a packet stream; identifying, by the first stage, a plurality of candidate packets within the packet stream that each satisfy one or more pre-match conditions relating to a set of access control rules by performing a pre-matching process on packets within the packet stream; emitting, by the first stage, information indicative of a candidate rule from the set of access control rules for which a full-match process is to be performed with respect to a candidate packet of the plurality of candidate packets selected based on a correlation of results of the pre-matching process; tokenizing, by the first stage, packet data of the candidate packet to produce matching tokens and corresponding locations of the matching tokens within the candidate packet; determining, by a second stage of the context-aware hardware accelerator, whether the candidate packet satisfies the candidate rule by performing the full-match process on the candidate packet including fetching and executing special purpose pattern matching instructions with reference to the candidate packet based on a plurality of predefined conditions associated with the candidate rule, corresponding contextual information provided by the candidate rule, the matching tokens and the corresponding locations; and providing, by the second stage, results of the full-match process to a general purpose processor of the network security device. | 1. A method comprising: receiving, by a first stage of a context-aware hardware accelerator of a network security device, a packet stream; identifying, by the first stage, a plurality of candidate packets within the packet stream that each satisfy one or more pre-match conditions relating to a set of access control rules by performing a pre-matching process on packets within the packet stream; emitting, by the first stage, information indicative of a candidate rule from the set of access control rules for which a full-match process is to be performed with respect to a candidate packet of the plurality of candidate packets selected based on a correlation of results of the pre-matching process; tokenizing, by the first stage, packet data of the candidate packet to produce matching tokens and corresponding locations of the matching tokens within the candidate packet; determining, by a second stage of the context-aware hardware accelerator, whether the candidate packet satisfies the candidate rule by performing the full-match process on the candidate packet including fetching and executing special purpose pattern matching instructions with reference to the candidate packet based on a plurality of predefined conditions associated with the candidate rule, corresponding contextual information provided by the candidate rule, the matching tokens and the corresponding locations; and providing, by the second stage, results of the full-match process to a general purpose processor of the network security device. 8. The method of claim 1 , wherein said performing, by the first stage, a pre-matching process further comprises performing passive matching of overflow patterns that occur between characters or strings within packet data of the packets within the packet stream. | 0.797214 |
9,495,467 | 11 | 12 | 11. The method of claim 9 , comprising providing a headline monitoring facility for use in selecting one or more electronic articles for which text headlines are to be provided. | 11. The method of claim 9 , comprising providing a headline monitoring facility for use in selecting one or more electronic articles for which text headlines are to be provided. 12. The method of claim 11 , wherein the headline monitoring facility uses at least some of the metadata generated by the preprocessing and comprises a display that includes information associated with one or more articles to assist an editor in prioritizing the one or more articles for headlining. | 0.866399 |
7,475,021 | 7 | 8 | 7. The method of claim 1 , further comprising analyzing said calendar entry records for validating currency of calendar data and updating said data if applicable, said analyzing said calendar entry records and updating said data comprises: opening a source associated with a calendar entry record to be analyzed; comparing content displayed upon said opening a source with content in said calendar entry record; if content displayed upon said opening a source is not similar to content in said calendar entry record: presenting both sets of data to said computer user; and prompting said computer user to select from options including at least one of: updating said calendar entry record with new data found as a result of said opening a source associated with a calendar entry record; creating a new calendar entry record; and canceling said calendar entry record; and if content displayed upon said opening a source is similar to content in said calendar entry record, retaining said calendar entry record. | 7. The method of claim 1 , further comprising analyzing said calendar entry records for validating currency of calendar data and updating said data if applicable, said analyzing said calendar entry records and updating said data comprises: opening a source associated with a calendar entry record to be analyzed; comparing content displayed upon said opening a source with content in said calendar entry record; if content displayed upon said opening a source is not similar to content in said calendar entry record: presenting both sets of data to said computer user; and prompting said computer user to select from options including at least one of: updating said calendar entry record with new data found as a result of said opening a source associated with a calendar entry record; creating a new calendar entry record; and canceling said calendar entry record; and if content displayed upon said opening a source is similar to content in said calendar entry record, retaining said calendar entry record. 8. The method of claim 7 , further comprising: including a notice in a calendar entry record when a source associated with said calendar entry record to be analyzed cannot be opened. | 0.985551 |
7,801,912 | 116 | 123 | 116. A computer-implemented method, comprising: receiving query requests from a plurality of client applications on a web service interface to a searchable data service, wherein said receiving comprises receiving the query requests at a common message endpoint provided by the web service interface to the plurality of client applications to send the query requests; forwarding each query request from the web service interface to at least one of a plurality of nodes configured to participate in the searchable data service, wherein each query request comprises an identification of a searchable index and search criteria for the searchable data service, wherein the plurality of nodes store searchable indexes for a plurality of independent data stores used by the client applications, wherein the data stores are on one or more storage devices separate from the plurality of nodes, and wherein each searchable index stores searchable data service objects for a particular one of the plurality of independent data stores such that each searchable index provides a complete index for only one of the independent data stores; receiving a query result for each query request from a respective one of the plurality of nodes, wherein each query result comprises an entity identifier from each of one or more searchable data service objects from a particular searchable index of the searchable data service that satisfy the search criteria of the query request; and returning at least the entity identifier from each of the one or more searchable data service objects that satisfy the query request to the client application in accordance with the web service interface, wherein each entity identifier locates a particular entity in a particular data store used by the client applications. | 116. A computer-implemented method, comprising: receiving query requests from a plurality of client applications on a web service interface to a searchable data service, wherein said receiving comprises receiving the query requests at a common message endpoint provided by the web service interface to the plurality of client applications to send the query requests; forwarding each query request from the web service interface to at least one of a plurality of nodes configured to participate in the searchable data service, wherein each query request comprises an identification of a searchable index and search criteria for the searchable data service, wherein the plurality of nodes store searchable indexes for a plurality of independent data stores used by the client applications, wherein the data stores are on one or more storage devices separate from the plurality of nodes, and wherein each searchable index stores searchable data service objects for a particular one of the plurality of independent data stores such that each searchable index provides a complete index for only one of the independent data stores; receiving a query result for each query request from a respective one of the plurality of nodes, wherein each query result comprises an entity identifier from each of one or more searchable data service objects from a particular searchable index of the searchable data service that satisfy the search criteria of the query request; and returning at least the entity identifier from each of the one or more searchable data service objects that satisfy the query request to the client application in accordance with the web service interface, wherein each entity identifier locates a particular entity in a particular data store used by the client applications. 123. The computer-implemented method as recited in claim 116 , wherein the web service interface is provided by a web services platform, and wherein the web services platform further comprises one or more services that perform metering, billing, authentication, and access control of subscribers to the searchable data service, wherein a subscriber is an entity associated with one or more client applications each configured to access the searchable data service via the web service interface as a search frontend to one or more of the plurality of data stores used by the client application. | 0.786844 |
8,911,478 | 1 | 17 | 1. In a spinal fixation structure having a bone anchor and a closure, the anchor for holding a spinal fixation longitudinal connecting member, the anchor having an open receiver with spaced apart arms defining a longitudinal connecting member receiving channel therebetween and the closure sized for being received within the channel and adapted for rotation and advancement into the channel between the arms to capture a portion of the longitudinal connecting member in the channel, the improvement comprising: a) a closure guide and advancement flange form extending helically along the closure and about a central axis of the closure, the flange form having a first portion located adjacent a root of the form and extending radially outwardly therefrom in a direction away from the central axis, the first portion having a first load flank, the flange form having a second portion extending radially outwardly from a termination of the load flank to a crest of the flange form, the second portion having a first splay control ramp and a rounded toe, the toe being spaced from the load flank both radially and axially, the closure flange form further comprising a depth and an axial height, the depth measured radially from the root to the crest and the axial height measured from the load flank to a stab flank and taken substantially along the root surface of the flange form, and wherein a ratio of the depth over the axial height is a value ranging from less than 1 to about 1; and b) a discontinuous receiver guide and advancement flange form extending helically about and along an inner surface of each receiver arm, the receiver flange form having a second load flank and a second splay control ramp respectively engaging the first load flank and the first splay control ramp during mating of the closure flange form with the receiver flange form, the receiver flange form having clearance surfaces disposed in close spaced relation to a remainder of the closure flange form. | 1. In a spinal fixation structure having a bone anchor and a closure, the anchor for holding a spinal fixation longitudinal connecting member, the anchor having an open receiver with spaced apart arms defining a longitudinal connecting member receiving channel therebetween and the closure sized for being received within the channel and adapted for rotation and advancement into the channel between the arms to capture a portion of the longitudinal connecting member in the channel, the improvement comprising: a) a closure guide and advancement flange form extending helically along the closure and about a central axis of the closure, the flange form having a first portion located adjacent a root of the form and extending radially outwardly therefrom in a direction away from the central axis, the first portion having a first load flank, the flange form having a second portion extending radially outwardly from a termination of the load flank to a crest of the flange form, the second portion having a first splay control ramp and a rounded toe, the toe being spaced from the load flank both radially and axially, the closure flange form further comprising a depth and an axial height, the depth measured radially from the root to the crest and the axial height measured from the load flank to a stab flank and taken substantially along the root surface of the flange form, and wherein a ratio of the depth over the axial height is a value ranging from less than 1 to about 1; and b) a discontinuous receiver guide and advancement flange form extending helically about and along an inner surface of each receiver arm, the receiver flange form having a second load flank and a second splay control ramp respectively engaging the first load flank and the first splay control ramp during mating of the closure flange form with the receiver flange form, the receiver flange form having clearance surfaces disposed in close spaced relation to a remainder of the closure flange form. 17. The improvement of claim 1 wherein the closure flange form is a first flange form having a first start and further comprising a second flange form having a second start, the first and second starts being opposed and located near a bottom of the closure. | 0.812135 |
7,698,652 | 1 | 4 | 1. An apparatus having a user interface assisting in searching for information from items of an ordered list in a data array, the items having descriptions, the apparatus comprising: a display; an array scroller for sequentially displaying on the display the descriptions from the ordered list on the user interface responsive to user actuation; and a helper character-generator operative to display a helper character representative of a portion of a description of an item in the ordered list being displayed, the displaying of the helper character being responsive to continued user actuation of the array scroller, wherein the helper character is displayed in a size which is larger than a size of the descriptions, wherein a change in the size is made based on a scrolling speed that is responsive to the continued user actuation. | 1. An apparatus having a user interface assisting in searching for information from items of an ordered list in a data array, the items having descriptions, the apparatus comprising: a display; an array scroller for sequentially displaying on the display the descriptions from the ordered list on the user interface responsive to user actuation; and a helper character-generator operative to display a helper character representative of a portion of a description of an item in the ordered list being displayed, the displaying of the helper character being responsive to continued user actuation of the array scroller, wherein the helper character is displayed in a size which is larger than a size of the descriptions, wherein a change in the size is made based on a scrolling speed that is responsive to the continued user actuation. 4. The apparatus of claim 1 , wherein the apparatus comprises at least one of a handheld device, a mobile telephone, and an Internet-enable device with a browser. | 0.786842 |
8,914,322 | 37 | 40 | 37. A non-transitory machine readable storage medium containing executable program instructions for causing a data processing system to perform a method of managing data, the method comprising: receiving a composite document having a main subdocument and a subpart subdocument, wherein the main subdocument and the subpart subdocument have different formats; capturing, by a first importer, first metadata from the main subdocument, wherein the first metadata describes the content of the main subdocument; identifying the subpart subdocument in the composite document; identifying a second importer based on the format of the subpart subdocument; capturing, by the second importer, second metadata from the subpart subdocument, wherein the second metadata describes the content of the subpart subdocument; combining the first metadata and the second metadata into a combined metadata for the composite document, wherein the combined metadata is stored in a metadata database having the second metadata associated with the first metadata, and wherein the metadata database includes the combined metadata and metadata for one or more other documents; indexing content of the main subdocument and the subpart subdocument and saving the indexed content; and searching the metadata in the metadata database using a search query, wherein the search is performed as the search query is being received, and wherein the search results locate the composite document and the subpart subdocument based on the combined metadata. | 37. A non-transitory machine readable storage medium containing executable program instructions for causing a data processing system to perform a method of managing data, the method comprising: receiving a composite document having a main subdocument and a subpart subdocument, wherein the main subdocument and the subpart subdocument have different formats; capturing, by a first importer, first metadata from the main subdocument, wherein the first metadata describes the content of the main subdocument; identifying the subpart subdocument in the composite document; identifying a second importer based on the format of the subpart subdocument; capturing, by the second importer, second metadata from the subpart subdocument, wherein the second metadata describes the content of the subpart subdocument; combining the first metadata and the second metadata into a combined metadata for the composite document, wherein the combined metadata is stored in a metadata database having the second metadata associated with the first metadata, and wherein the metadata database includes the combined metadata and metadata for one or more other documents; indexing content of the main subdocument and the subpart subdocument and saving the indexed content; and searching the metadata in the metadata database using a search query, wherein the search is performed as the search query is being received, and wherein the search results locate the composite document and the subpart subdocument based on the combined metadata. 40. The non-transitory machine readable storage medium of claim 37 , wherein the metadata of the composite document forms a hierarchical structure that includes a container format and the one or more subdocuments. | 0.813811 |
4,569,026 | 29 | 31 | 29. A method of simulating a personalized voice conversation between a talking video character and a human viewer of the video character, comprising the steps of: storing digital representations of the name of said human viewer; displaying a first video frame sequence including picture representations of a talking video character accompanied by a first voice sound associated with a plurality of second voice sounds; communicating to the human viewer during said first video frame sequence a first plurality of verbal expressions each verbal expression corresponding to a second voice sound in said plurality thereof; receiving from said viewer a response signal corresponding to a selected verbal expression in said plurality of verbal expressions; displaying said first video frame sequence again as a second video frame sequence, thereby repeating said talking video character; presenting the second voice sound corresponding to said selected verbal expression; and synthesizing as a third voice sound the name of said human viwer as a function of said digital representations during said first or second video frame sequence, thereby personalizing a simulated voice conversation between the human and the talking video character. | 29. A method of simulating a personalized voice conversation between a talking video character and a human viewer of the video character, comprising the steps of: storing digital representations of the name of said human viewer; displaying a first video frame sequence including picture representations of a talking video character accompanied by a first voice sound associated with a plurality of second voice sounds; communicating to the human viewer during said first video frame sequence a first plurality of verbal expressions each verbal expression corresponding to a second voice sound in said plurality thereof; receiving from said viewer a response signal corresponding to a selected verbal expression in said plurality of verbal expressions; displaying said first video frame sequence again as a second video frame sequence, thereby repeating said talking video character; presenting the second voice sound corresponding to said selected verbal expression; and synthesizing as a third voice sound the name of said human viwer as a function of said digital representations during said first or second video frame sequence, thereby personalizing a simulated voice conversation between the human and the talking video character. 31. The method of claim 29 wherein said video character is displayed as an animated cartoon. | 0.926282 |
8,719,318 | 15 | 20 | 15. A computer program product for responding to natural language input, comprising one or more non-transitory computer-readable media having computer program instructions stored therein, the computer program instructions being configured such that, when executed, the computer program instructions cause one or more computing devices to: receive a natural language question comprising a sequence of words; identify a first translation template of a plurality of translation templates using at least a first word of the sequence of words, the first translation template including a sequence of known and unknown strings, a first query and a second query, a first known string of the known and unknown strings corresponding to the first word; identify a first object in a knowledge base using a second word of the sequence of words and the first query of the first translation template; and generate one or more results using the knowledge base, the first object, and the second query of the first translation template. | 15. A computer program product for responding to natural language input, comprising one or more non-transitory computer-readable media having computer program instructions stored therein, the computer program instructions being configured such that, when executed, the computer program instructions cause one or more computing devices to: receive a natural language question comprising a sequence of words; identify a first translation template of a plurality of translation templates using at least a first word of the sequence of words, the first translation template including a sequence of known and unknown strings, a first query and a second query, a first known string of the known and unknown strings corresponding to the first word; identify a first object in a knowledge base using a second word of the sequence of words and the first query of the first translation template; and generate one or more results using the knowledge base, the first object, and the second query of the first translation template. 20. The computer program product of claim 15 , wherein the computer program instructions are further configured such that, when executed, the computer program instructions cause the one or more computing devices to generate an explanation representing how the one or more results were generated, the explanation including a natural language translation of the second query and one or more processing steps of the second query with reference to the knowledge base. | 0.59669 |
8,781,832 | 28 | 29 | 28. At least one computer readable memory encoded with instructions that, when executed, perform a method for processing acoustic data in accordance with a speech recognition system, the method comprising acts of: recording acoustic data in at least one recording medium; detecting, at a first time, a user-generated input event instructing the speech recognition system to start speech recognition processing, the first time corresponding to a first location of the recorded acoustic data recorded in the at least one recording medium; searching in the recorded acoustic data to identify a silence region having the shortest distance, among all silence regions in the recorded acoustic data, relative to the first location in the recorded acoustic data corresponding to the first time at which the user-generated input event was detected; and identifying a location in the identified silence region as a start location for speech recognition processing of at least a portion of the recorded acoustic data, wherein: if the recorded acoustic data is such that the identified silence region entirely follows the first location, the start location for speech recognition processing follows the first location; and if the recorded acoustic data is such that the identified silence region entirely precedes the first location, the start location for speech recognition processing precedes the first location. | 28. At least one computer readable memory encoded with instructions that, when executed, perform a method for processing acoustic data in accordance with a speech recognition system, the method comprising acts of: recording acoustic data in at least one recording medium; detecting, at a first time, a user-generated input event instructing the speech recognition system to start speech recognition processing, the first time corresponding to a first location of the recorded acoustic data recorded in the at least one recording medium; searching in the recorded acoustic data to identify a silence region having the shortest distance, among all silence regions in the recorded acoustic data, relative to the first location in the recorded acoustic data corresponding to the first time at which the user-generated input event was detected; and identifying a location in the identified silence region as a start location for speech recognition processing of at least a portion of the recorded acoustic data, wherein: if the recorded acoustic data is such that the identified silence region entirely follows the first location, the start location for speech recognition processing follows the first location; and if the recorded acoustic data is such that the identified silence region entirely precedes the first location, the start location for speech recognition processing precedes the first location. 29. The at least one computer readable memory of claim 28 , wherein the method further comprises: detecting, at a second time later than the first time, an indication to stop speech recognition processing, the second time corresponding to a second location of the recorded acoustic data; continuing to record acoustic data after the second time; and performing speech recognition processing on at least a portion of the recorded acoustic data recorded after the second time. | 0.501053 |
8,799,798 | 1 | 2 | 1. A method, comprising: analyzing handwriting data to recognize one or more objects depicted in the handwriting data, the handwriting data including a sketch of the one or more objects, analyzing the handwriting data comprising comparing the sketch of the one or more objects to images present in a database to determine if one or more of the images are similar to the sketch; determining if one or more applications of a plurality of applications are associated with the handwriting data based on the one or more objects recognized in the handwriting data, determining if one or more applications are associated with the handwriting data comprising: associating one or more keywords with each of the plurality of applications without associating any image with an application; determining one or more keywords associated with the one or more images that are determined to be similar to the sketch; and after determining the one or more keywords associated with the one or more images, determining if any applications are associated with the one or more keywords; and if one application is determined to be associated with the handwriting data, launching the one application. | 1. A method, comprising: analyzing handwriting data to recognize one or more objects depicted in the handwriting data, the handwriting data including a sketch of the one or more objects, analyzing the handwriting data comprising comparing the sketch of the one or more objects to images present in a database to determine if one or more of the images are similar to the sketch; determining if one or more applications of a plurality of applications are associated with the handwriting data based on the one or more objects recognized in the handwriting data, determining if one or more applications are associated with the handwriting data comprising: associating one or more keywords with each of the plurality of applications without associating any image with an application; determining one or more keywords associated with the one or more images that are determined to be similar to the sketch; and after determining the one or more keywords associated with the one or more images, determining if any applications are associated with the one or more keywords; and if one application is determined to be associated with the handwriting data, launching the one application. 2. The method according to claim 1 , further comprising displaying information allowing a user to select an application to launch from the two or more applications if two or more applications are determined to be associated with the handwriting data. | 0.843945 |
9,204,107 | 15 | 17 | 15. A method of video processing using memory and at least one processor, comprising: receiving video input; performing analysis of the video input, using the at least one processor, to determine if a gross change event has occurred in the video input and to produce one or more gross change primitives if a gross change event is determined to have occurred in the video input; generating view identification information using the at least one processor and the one or more gross change primitives; selecting one or more rules using the at least one processor and the view identification information; determining a response, using the at least one processor, based on the one or more selected rules and the one or more gross change primitives. | 15. A method of video processing using memory and at least one processor, comprising: receiving video input; performing analysis of the video input, using the at least one processor, to determine if a gross change event has occurred in the video input and to produce one or more gross change primitives if a gross change event is determined to have occurred in the video input; generating view identification information using the at least one processor and the one or more gross change primitives; selecting one or more rules using the at least one processor and the view identification information; determining a response, using the at least one processor, based on the one or more selected rules and the one or more gross change primitives. 17. The method of claim 15 , further comprising: determining one or more bad frames in the video input; tracking consecutive bad frames using a histogram having classifications of bad frames; generating a gross change event if a time duration of a number of consecutive bad frames in the histogram is greater than a threshold; and detecting a classification of the gross change event using the histogram of consecutive bad frames. | 0.797361 |
8,949,340 | 15 | 17 | 15. The computer program product of claim 2 , further comprising: computer code for determining a location of the user; computer code for updating the user profile based on the location of the user; and computer code for causing delivery of at least a location-related portion of the content based on the location of the user. | 15. The computer program product of claim 2 , further comprising: computer code for determining a location of the user; computer code for updating the user profile based on the location of the user; and computer code for causing delivery of at least a location-related portion of the content based on the location of the user. 17. The computer program product of claim 15 , wherein the computer program is operable such that the location of the user is determined utilizing a global positioning system. | 0.977046 |
8,457,948 | 28 | 29 | 28. The non-transitory computer-readable medium of claim 25 , wherein the set of attributes comprises at least one attribute type and at least one corresponding attribute value. | 28. The non-transitory computer-readable medium of claim 25 , wherein the set of attributes comprises at least one attribute type and at least one corresponding attribute value. 29. The non-transitory computer-readable medium of claim 28 , wherein the plurality of sentence templates include an indicator specifying whether the sentence template variables are replaced by an attribute type or an attribute value. | 0.947274 |
8,850,384 | 3 | 4 | 3. The method of claim 1 , wherein: the requested action is any one of an add operation candidate action or a delete operation candidate action; and updating the SOA service model comprises any one of adding an operation candidate to the service candidate, or deleting an operation candidate from the service candidate in the SOA service model. | 3. The method of claim 1 , wherein: the requested action is any one of an add operation candidate action or a delete operation candidate action; and updating the SOA service model comprises any one of adding an operation candidate to the service candidate, or deleting an operation candidate from the service candidate in the SOA service model. 4. The method of claim 3 , further comprising: receiving a user selection of an encapsulated composition candidate for an operation candidate associated with the service candidate; and linking the operation candidate to the selected composition candidate, the operation candidate representing a composition controller of the selected composition candidate. | 0.864329 |
8,875,109 | 13 | 15 | 13. One or more computer-readable non-transitory storage media embodying software operable when executed by one or more computer systems to: mark a variable in source code of a software program written in an object-oriented scripting language, wherein marking the variable is performed with a keyword; mark one or more locations in the source code of the software program; construct a control flow graph (CFG) for the software program; and track the marked variable through the CFG by determining a path in the CFG that leads from a first node corresponding to the marked variable to a one of the marked locations in the source code of the software program. | 13. One or more computer-readable non-transitory storage media embodying software operable when executed by one or more computer systems to: mark a variable in source code of a software program written in an object-oriented scripting language, wherein marking the variable is performed with a keyword; mark one or more locations in the source code of the software program; construct a control flow graph (CFG) for the software program; and track the marked variable through the CFG by determining a path in the CFG that leads from a first node corresponding to the marked variable to a one of the marked locations in the source code of the software program. 15. The media of claim 13 , wherein the software is further operable when executed by the one or more computer systems to report one or more execution paths in the CFG that comprise the first node corresponding to the marked variable. | 0.732877 |
10,042,619 | 10 | 11 | 10. A computer-implemented method for efficiently managing enterprise architecture using resource description framework, via program instructions stored in a memory and executed by a processor, the computer-implemented method comprising: defining one or more Resource Description Framework (RDF)/Extensible Markup Language (XML) models corresponding to one or more applications, wherein the one or more RDF/XML models are one or more RDF graph models serialized using XML; parsing the one or more defined RDF/XML models to create corresponding Java objects; processing the one or more parsed RDF/XML models for creating the corresponding one or more applications, wherein the one or more applications are created by using the created Java objects to facilitate interaction with one or more enterprise relational databases; generating one or more graphical user interfaces corresponding to the one or more created applications, wherein the created one or more applications facilitate efficient management of enterprise architecture; and evaluating an application from the created one or more applications, wherein the evaluation comprises: configuring one or more dimensions associated with the application; configuring a first and a second attribute corresponding to each dimension of the one or more dimensions; facilitating selection of a first evaluation technique to evaluate the first attribute and a second evaluation technique to evaluate the second attribute, the first evaluation technique is different from the second evaluation technique, wherein the evaluation of the first and the second attribute corresponds to evaluation of the application; and generating a score heat map for the application based on the evaluation of the application. | 10. A computer-implemented method for efficiently managing enterprise architecture using resource description framework, via program instructions stored in a memory and executed by a processor, the computer-implemented method comprising: defining one or more Resource Description Framework (RDF)/Extensible Markup Language (XML) models corresponding to one or more applications, wherein the one or more RDF/XML models are one or more RDF graph models serialized using XML; parsing the one or more defined RDF/XML models to create corresponding Java objects; processing the one or more parsed RDF/XML models for creating the corresponding one or more applications, wherein the one or more applications are created by using the created Java objects to facilitate interaction with one or more enterprise relational databases; generating one or more graphical user interfaces corresponding to the one or more created applications, wherein the created one or more applications facilitate efficient management of enterprise architecture; and evaluating an application from the created one or more applications, wherein the evaluation comprises: configuring one or more dimensions associated with the application; configuring a first and a second attribute corresponding to each dimension of the one or more dimensions; facilitating selection of a first evaluation technique to evaluate the first attribute and a second evaluation technique to evaluate the second attribute, the first evaluation technique is different from the second evaluation technique, wherein the evaluation of the first and the second attribute corresponds to evaluation of the application; and generating a score heat map for the application based on the evaluation of the application. 11. The computer-implemented method of claim 10 , wherein the one or more RDF/XML models are defined by customizing one or more pre-stored base models and further wherein the one or more pre-stored base models provide one or more templates comprising ontologies required to create the one or more applications. | 0.808642 |
9,235,978 | 14 | 18 | 14. A computer program product for automatically generating a suggested alert definition based on user interaction with a computing system, comprising: a non-transitory computer-readable storage medium; and computer-executable code, encoded on the non-transitory computer-readable storage medium of a computing system, configured to cause at least one processor to perform the steps of: generating a suggested alert definition for a notification application, the notification application configured to maintain active alert definitions for a user, wherein an active alert definition of the notification application specifies data to monitor and an alert trigger condition to cause the notification application to generate a corresponding alert notification for the user, wherein providing the suggested alert definition comprises: accessing a first data set of captured user interactions with a client computing device from electronic memory storage, wherein the first data set comprises information regarding user interaction with an application of the client computing device that is independent of the notification application; analyzing the first data set, and generating a suggested alert definition related to the user interaction based on the analysis of the first data set, the suggested alert definition specifying data to monitor and a trigger condition for suggesting conversion to an active alert of the notification application; and providing computer-readable code to display the suggested alert definition on a computing device display. | 14. A computer program product for automatically generating a suggested alert definition based on user interaction with a computing system, comprising: a non-transitory computer-readable storage medium; and computer-executable code, encoded on the non-transitory computer-readable storage medium of a computing system, configured to cause at least one processor to perform the steps of: generating a suggested alert definition for a notification application, the notification application configured to maintain active alert definitions for a user, wherein an active alert definition of the notification application specifies data to monitor and an alert trigger condition to cause the notification application to generate a corresponding alert notification for the user, wherein providing the suggested alert definition comprises: accessing a first data set of captured user interactions with a client computing device from electronic memory storage, wherein the first data set comprises information regarding user interaction with an application of the client computing device that is independent of the notification application; analyzing the first data set, and generating a suggested alert definition related to the user interaction based on the analysis of the first data set, the suggested alert definition specifying data to monitor and a trigger condition for suggesting conversion to an active alert of the notification application; and providing computer-readable code to display the suggested alert definition on a computing device display. 18. The computer program product of claim 14 , wherein the computer-executable code is further configured to cause the processor perform the step of: prior to generating the suggested alert definition, retrieving a user profile, wherein generating the suggested alert definition comprises using the user profile in addition to analyzing the first data set. | 0.716561 |
7,970,793 | 7 | 8 | 7. The method of claim 6 the adding the calendar event further comprising updating a previous calendar event if the specific event information matches information of the previous calendar event, and comprises a time stamp that is different from a time stamp of the previous calendar event information. | 7. The method of claim 6 the adding the calendar event further comprising updating a previous calendar event if the specific event information matches information of the previous calendar event, and comprises a time stamp that is different from a time stamp of the previous calendar event information. 8. The method of claim 7 wherein the keyword comprises a type of entry, a subject, a leader, a participant, a frequency, a schedule, a time, or a location. | 0.958864 |
8,266,163 | 6 | 7 | 6. A data processing system for utilizing reference/identification (ID) linking in extensible markup language (XML) wrapper code generation in a data processing system, said data processing system comprising: a processor; an interconnect coupled to said processor; and a computer-readable storage medium embodying computer program code, said computer program code comprising instructions executable by said processor and configured for: receiving a type document and reference/ID constraints document; and accessing said reference/ID constraints document to translate between XML structures and object structures, wherein said instructions for accessing further include instructions configured for: creating a directed constraint graph from said reference/ID constraints document, wherein said directed constraint graph comprises at least one root XML structure that is not referenced by other XML structures and at least one leaf XML structure that does not reference other XML structures; generating a first set of deserialization code for at least one XML structure not in said directed constraint graph, wherein said first set of deserialization code translates said at least one XML structure not in said directed constraint graph into at least one object structure not in said directed constraint graph; creating a second set of deserialization code for said at least one XML leaf structure in said directed constraint graph, wherein said second set of deserialization code translates said at least one leaf XML structure into at least one leaf object structure; generating a third set of deserialization code for at least one next highest XML structure in said directed constraint graph, wherein said third set of deserialization code translates said at least one next highest XML structure into at least one next highest object structure; storing at least one intermediate object structure in at least one temporary hash table, wherein said at least one intermediate object structure is not a root object structure or a leaf object structure; and creating cleanup functions within said first, second, and third sets of deserialization code, wherein said cleanup functions remove all temporary hash tables utilized in object serialization. | 6. A data processing system for utilizing reference/identification (ID) linking in extensible markup language (XML) wrapper code generation in a data processing system, said data processing system comprising: a processor; an interconnect coupled to said processor; and a computer-readable storage medium embodying computer program code, said computer program code comprising instructions executable by said processor and configured for: receiving a type document and reference/ID constraints document; and accessing said reference/ID constraints document to translate between XML structures and object structures, wherein said instructions for accessing further include instructions configured for: creating a directed constraint graph from said reference/ID constraints document, wherein said directed constraint graph comprises at least one root XML structure that is not referenced by other XML structures and at least one leaf XML structure that does not reference other XML structures; generating a first set of deserialization code for at least one XML structure not in said directed constraint graph, wherein said first set of deserialization code translates said at least one XML structure not in said directed constraint graph into at least one object structure not in said directed constraint graph; creating a second set of deserialization code for said at least one XML leaf structure in said directed constraint graph, wherein said second set of deserialization code translates said at least one leaf XML structure into at least one leaf object structure; generating a third set of deserialization code for at least one next highest XML structure in said directed constraint graph, wherein said third set of deserialization code translates said at least one next highest XML structure into at least one next highest object structure; storing at least one intermediate object structure in at least one temporary hash table, wherein said at least one intermediate object structure is not a root object structure or a leaf object structure; and creating cleanup functions within said first, second, and third sets of deserialization code, wherein said cleanup functions remove all temporary hash tables utilized in object serialization. 7. The system according to claim 6 , wherein said instructions are further configured for: generating a fourth set of deserialization code for said at least one root XML structure, wherein said fourth set of deserialization code translates said at least one root XML structure into at least one object root structure. | 0.673868 |
9,613,139 | 16 | 17 | 16. The method of claim 11 , wherein the at least one tendency parameter defines the sentiment and a direction in which the sentiment trend should be monitored. | 16. The method of claim 11 , wherein the at least one tendency parameter defines the sentiment and a direction in which the sentiment trend should be monitored. 17. The method of claim 16 , wherein the real-time changes in the direction of the sentiment trend include a change from a positive sentiment to a negative sentiment and a change from a negative sentiment to a positive sentiment. | 0.927024 |
8,429,604 | 21 | 25 | 21. A system comprising: non-transitory computer-readable medium to which instructions are stored; and processor operable to execute said instructions that when executed by the processor causes the processor to access a web page source code file that comprises structural code and behavioral code for the web page, wherein said behavioral code comprises at least one of scripting language code and event handler code, extract, from the web page source code file, at least a portion of the behavioral code into a separate file, insert, into the web page source code file, binding code for referencing the extracted behavioral code to maintain run-time behavior of the web page consistent with its run-time behavior said extracting, and wherein a user interface enables selection of one or more of identified behavioral code that is to be extracted from the web page source code file into the separate file; and wherein the one or more of the identified behavioral code is extracted from the web page source code file into the separate file. | 21. A system comprising: non-transitory computer-readable medium to which instructions are stored; and processor operable to execute said instructions that when executed by the processor causes the processor to access a web page source code file that comprises structural code and behavioral code for the web page, wherein said behavioral code comprises at least one of scripting language code and event handler code, extract, from the web page source code file, at least a portion of the behavioral code into a separate file, insert, into the web page source code file, binding code for referencing the extracted behavioral code to maintain run-time behavior of the web page consistent with its run-time behavior said extracting, and wherein a user interface enables selection of one or more of identified behavioral code that is to be extracted from the web page source code file into the separate file; and wherein the one or more of the identified behavioral code is extracted from the web page source code file into the separate file. 25. The system of claim 21 wherein said event handler code comprises event attributes defined by markup language code. | 0.841823 |
7,693,865 | 1 | 6 | 1. A method comprising performing a machine-executed operation involving instructions for identifying a navigational query, wherein the machine-executed operation is at least one of: A) storing said instructions onto a volatile or non-volatile storage medium; and B)executing the instructions; wherein said instructions are instructions which, when executed by one or more processors, cause performance of: determining whether a query is a navigational query by receiving a set of query-URL pair-wise features based at least in part on said query in conjunction with an associated query result set; integrating subsets of said set of query-URL pair-wise features to generate a set of query-based features that are independent of any particular URL; automatically selecting, from said set of query-based features, a subset of most effective features for identifying navigational queries, wherein said selecting is based on a machine learning feature selection method; based on said subset of most effective features, using a machine learning classification method to determine whether said query is a navigational query. | 1. A method comprising performing a machine-executed operation involving instructions for identifying a navigational query, wherein the machine-executed operation is at least one of: A) storing said instructions onto a volatile or non-volatile storage medium; and B)executing the instructions; wherein said instructions are instructions which, when executed by one or more processors, cause performance of: determining whether a query is a navigational query by receiving a set of query-URL pair-wise features based at least in part on said query in conjunction with an associated query result set; integrating subsets of said set of query-URL pair-wise features to generate a set of query-based features that are independent of any particular URL; automatically selecting, from said set of query-based features, a subset of most effective features for identifying navigational queries, wherein said selecting is based on a machine learning feature selection method; based on said subset of most effective features, using a machine learning classification method to determine whether said query is a navigational query. 6. The method of claim 1 , wherein said receiving comprises receiving a set of query-URL pair-wise features comprising click features, URL features, and anchor text features. | 0.664093 |
7,849,416 | 23 | 24 | 23. The method of claim 1 , further comprising: automatically generating a graphical program based on the sequence of operations, wherein the graphical program is executable to perform the sequence of operations, wherein the graphical program comprises a plurality of interconnected nodes visually indicating functionality of the graphical program, wherein automatically generating the graphical program comprises automatically including the plurality of interconnected nodes in the graphical program without user input specifying the nodes. | 23. The method of claim 1 , further comprising: automatically generating a graphical program based on the sequence of operations, wherein the graphical program is executable to perform the sequence of operations, wherein the graphical program comprises a plurality of interconnected nodes visually indicating functionality of the graphical program, wherein automatically generating the graphical program comprises automatically including the plurality of interconnected nodes in the graphical program without user input specifying the nodes. 24. The method of claim 23 , wherein the graphical program comprises a graphical data flow program, wherein the plurality of interconnected nodes visually indicates data flow that occurs among the nodes. | 0.954259 |
7,958,154 | 1 | 2 | 1. A computer program product comprising a non-transient computer useable medium having a computer readable program for providing command manager support for pluggable data formats, the operations of the computer program product comprising: receiving a hierarchical input data structure from a client, the hierarchical input data structure representing hierarchical data in a structure independent of a specific type of data repository; determining that the hierarchical input data structure comprises one of a snapshot structure and delta structure; in response to the hierarchical input data structure comprising a snapshot structure, the operations of the computer program product further comprising: creating a map object structure and copying one or more keys of the hierarchical input data structure into the map object structure; retrieving data values for each field of the map object structure from a hierarchical repository data structure in a data repository; comparing the hierarchical input data structure with the map object structure using a cursor Application Programming Interface (API) and accessor API; creating in an adaptor a data exchange systems programming interface (DESPI) hierarchical command structure comprising repository-specific commands and further comprising one or more node locations positions, the repository-specific commands configured to update a hierarchical repository data structure such that the hierarchical repository data structure is identical to the hierarchical input data structure; executing the DESPI hierarchical command structure such that the individual repository-specific commands are executed in the data repository. | 1. A computer program product comprising a non-transient computer useable medium having a computer readable program for providing command manager support for pluggable data formats, the operations of the computer program product comprising: receiving a hierarchical input data structure from a client, the hierarchical input data structure representing hierarchical data in a structure independent of a specific type of data repository; determining that the hierarchical input data structure comprises one of a snapshot structure and delta structure; in response to the hierarchical input data structure comprising a snapshot structure, the operations of the computer program product further comprising: creating a map object structure and copying one or more keys of the hierarchical input data structure into the map object structure; retrieving data values for each field of the map object structure from a hierarchical repository data structure in a data repository; comparing the hierarchical input data structure with the map object structure using a cursor Application Programming Interface (API) and accessor API; creating in an adaptor a data exchange systems programming interface (DESPI) hierarchical command structure comprising repository-specific commands and further comprising one or more node locations positions, the repository-specific commands configured to update a hierarchical repository data structure such that the hierarchical repository data structure is identical to the hierarchical input data structure; executing the DESPI hierarchical command structure such that the individual repository-specific commands are executed in the data repository. 2. The computer program product of claim 1 , wherein the hierarchical input data structure comprises a delta structure, the operations of the computer program product further comprising: determining that the delta structure is a Service Data Object (SDO) comprising a change summary; creating a hierarchical command structure comprising repository-specific commands derived from the change summary of the delta structure; creating in the adaptor a DESPI hierarchical command structure from the hierarchical command structure, creating a DESPI hierarchical command structure further comprising: starting at a top node of the hierarchical command structure and creating for each node of the hierarchical command structure a node of the DESPI hierarchical command structure; copying command attributes of the hierarchical command structure to the DESPI hierarchical command structure; providing cursor positions for the DESPI hierarchical command structure; executing the DESPI hierarchical command structure such that the individual repository-specific commands are executed in the data repository. | 0.500456 |
7,676,743 | 97 | 98 | 97. The computer-readable medium of claim 95 , further comprising as a first step in the method associating the frames within a group. | 97. The computer-readable medium of claim 95 , further comprising as a first step in the method associating the frames within a group. 98. The computer-readable medium of claim 97 , further comprising, after associating the frames within a group, providing a visual cue to the frames in the group to distinguish the group from other groups. | 0.926733 |
9,569,334 | 12 | 17 | 12. A computing system, comprising: a storage element operable to store a representation of an application source code; and a processor operable to perform operations including: specifying a plurality of runtime binding rules, each runtime binding rule of the plurality of runtime binding rules configured to augment the representation of the application source code using code slicing techniques, each runtime binding rule of the plurality of runtime binding rules associated with one or more locations within the representation of the application source code, at least one runtime binding rule of the plurality of runtime binding rules associated with a method invocation and a concrete implementation and specifying that the concrete implementation be visited either before or after the method invocation, the concrete implementation is visited before the method invocation when a first location of the one or more locations is before the method innovation and the concrete implementation is visited after the method invocation when a second location of the one or more locations is after the method innovation; beginning to traverse the representation of the application source code; monitoring a history of the traverse; continuing to traverse the representation of the application source code based on the history of the traverse, wherein continuing to traverse the representation of the application source code includes identifying a plurality of concrete implementations of a method invocation and traversing less than all of the concrete implementations based at least in part on one or more of the plurality of runtime binding rules, the concrete implementations being traversed being selected based at least in part on the history of the traverse, and updating the history of the traverse; and providing a set of identified vulnerabilities, the set of identified vulnerabilities based at least in part on the history of the traverse. | 12. A computing system, comprising: a storage element operable to store a representation of an application source code; and a processor operable to perform operations including: specifying a plurality of runtime binding rules, each runtime binding rule of the plurality of runtime binding rules configured to augment the representation of the application source code using code slicing techniques, each runtime binding rule of the plurality of runtime binding rules associated with one or more locations within the representation of the application source code, at least one runtime binding rule of the plurality of runtime binding rules associated with a method invocation and a concrete implementation and specifying that the concrete implementation be visited either before or after the method invocation, the concrete implementation is visited before the method invocation when a first location of the one or more locations is before the method innovation and the concrete implementation is visited after the method invocation when a second location of the one or more locations is after the method innovation; beginning to traverse the representation of the application source code; monitoring a history of the traverse; continuing to traverse the representation of the application source code based on the history of the traverse, wherein continuing to traverse the representation of the application source code includes identifying a plurality of concrete implementations of a method invocation and traversing less than all of the concrete implementations based at least in part on one or more of the plurality of runtime binding rules, the concrete implementations being traversed being selected based at least in part on the history of the traverse, and updating the history of the traverse; and providing a set of identified vulnerabilities, the set of identified vulnerabilities based at least in part on the history of the traverse. 17. The computing system of claim 12 , wherein the processor is further operable to perform operations including: determining whether a method invocation or its corresponding concrete implementation is marked with a runtime binding rule; and when it is determined that the method invocation or its corresponding concrete implementation is marked with a runtime binding rule, jumping to a method declaration identified by the runtime binding rule. | 0.534447 |
5,434,929 | 1 | 3 | 1. A method for indicating preferred character handwriting styles in a pen-based computer system that includes an input screen, a stylus for engaging the screen to input handwritten text to the computer system, and a recognizer for recognizing handwritten text, the method comprising the steps of: activating a character style preference editor; displaying a plurality of variant character styles for a selected character, each variant character style representing a distinct style of writing the selected character that is recognizable by the recognizer; and receiving inputs indicative of the likelihood that a handwritten character input with the stylus will have a form analogous to a selected variant character style and setting a use probability factor associated with the selected variant character style in accordance with the input. | 1. A method for indicating preferred character handwriting styles in a pen-based computer system that includes an input screen, a stylus for engaging the screen to input handwritten text to the computer system, and a recognizer for recognizing handwritten text, the method comprising the steps of: activating a character style preference editor; displaying a plurality of variant character styles for a selected character, each variant character style representing a distinct style of writing the selected character that is recognizable by the recognizer; and receiving inputs indicative of the likelihood that a handwritten character input with the stylus will have a form analogous to a selected variant character style and setting a use probability factor associated with the selected variant character style in accordance with the input. 3. A method as recited in claim 1 further including processing inputs made to said character style preference editor. | 0.868539 |
9,852,225 | 13 | 15 | 13. The computer-readable storage device of claim 12 , comprising determining a weight for each n-gram based on a number of times links to the given web page are selected when the n-gram is included in the at least one search query that was used to present a search results page that includes the links to the given web page. | 13. The computer-readable storage device of claim 12 , comprising determining a weight for each n-gram based on a number of times links to the given web page are selected when the n-gram is included in the at least one search query that was used to present a search results page that includes the links to the given web page. 15. The computer-readable storage device of claim 13 , comprising filtering one or more n-grams from the search queries based on the weight associated with the n-gram being below a predetermined value. | 0.937809 |
7,945,469 | 44 | 45 | 44. The method of claim 1 wherein the electronic marketplace provides a programmatic interface that includes one or more Web services, and wherein information about each of the at least some available tasks is received from an executing application program of a task requester based on an invocation by that executing application program of one of the Web services to submit the available task. | 44. The method of claim 1 wherein the electronic marketplace provides a programmatic interface that includes one or more Web services, and wherein information about each of the at least some available tasks is received from an executing application program of a task requester based on an invocation by that executing application program of one of the Web services to submit the available task. 45. The method of claim 44 wherein the programmatic interface is an application programming interface that is provided by the electronic marketplace for interacting with executing programs of task requesters, and wherein each supplying of received results for one of the at least some available tasks includes supplying the received results to the application program from which the information about the available task was received as a response to the invocation by that application program. | 0.910266 |
9,058,327 | 14 | 16 | 14. The system of claim 13 , wherein the processing device is further configured to: present the set of training documents in a graphical user interface (GUI) of a selection tool; receive, by the selection tool, a content selection of a portion of the training document and a training classification; and associate the training classification with the portion of the training document. | 14. The system of claim 13 , wherein the processing device is further configured to: present the set of training documents in a graphical user interface (GUI) of a selection tool; receive, by the selection tool, a content selection of a portion of the training document and a training classification; and associate the training classification with the portion of the training document. 16. The system of claim 14 , further comprising: receive a marking from the selection tool; determine that the selected portion of the training document is a positive contribution to the training classification when the marking is positive; and determine that the selected portion of the training document is a negative contribution to the training classification when the marking is negative. | 0.717266 |
8,930,412 | 1 | 8 | 1. A method comprising: receiving, within an electronic system including a processor, a user selection of a portal visitor type to create a customizable portal associated with a business organization, wherein the portal visitor type identifies users that can access the customizable portal, wherein the portal visitor type is associated with a department of the business organization; determining content associated with an industry type, wherein the industry type is associated with the portal visitor type and with the department of the business organization; providing the determined content for user selection thereof; and creating the customizable portal configured to be packaged, wherein the customizable portal is based on the selected content, the portal visitor type, the department of the business organization and the industry type, and wherein the customizable portal is configured for automatic archiving based on a group consisting of an expiration date and a content usage threshold associated with the department. | 1. A method comprising: receiving, within an electronic system including a processor, a user selection of a portal visitor type to create a customizable portal associated with a business organization, wherein the portal visitor type identifies users that can access the customizable portal, wherein the portal visitor type is associated with a department of the business organization; determining content associated with an industry type, wherein the industry type is associated with the portal visitor type and with the department of the business organization; providing the determined content for user selection thereof; and creating the customizable portal configured to be packaged, wherein the customizable portal is based on the selected content, the portal visitor type, the department of the business organization and the industry type, and wherein the customizable portal is configured for automatic archiving based on a group consisting of an expiration date and a content usage threshold associated with the department. 8. The method of claim 1 further comprising: in response to a content usage being less than a certain threshold, generating an alert message to an owner of the customizable portal or archiving the selected content. | 0.827697 |
7,983,478 | 1 | 6 | 1. A method for handwritten character generation, implemented at least in part by a computing device, the method comprising: receiving a character; and generating a corresponding handwritten character using Hidden Markov Models trained to generate handwritten characters, the generating including using a Multi-Space Probability Distribution technique that includes a probability for determining whether a stroke is real or imaginary. | 1. A method for handwritten character generation, implemented at least in part by a computing device, the method comprising: receiving a character; and generating a corresponding handwritten character using Hidden Markov Models trained to generate handwritten characters, the generating including using a Multi-Space Probability Distribution technique that includes a probability for determining whether a stroke is real or imaginary. 6. The method of claim 1 , wherein the Hidden Markov Models comprise Hidden Markov Models trained using Eastern Asian character data. | 0.874765 |
9,397,695 | 1 | 2 | 1. A computer program product for generating a code alphabet for use by a deployed program to determine codewords for words used in a computing system, wherein the codewords have an average codeword length less than a length of the words, the computer program product comprising a computer readable storage medium having computer readable program code embodied therein that executes to perform operations, the operations comprising: generating a code alphabet having a number of symbols formed by merging symbols that provide variable length codings of the words, wherein the code alphabet is used by the deployed program. | 1. A computer program product for generating a code alphabet for use by a deployed program to determine codewords for words used in a computing system, wherein the codewords have an average codeword length less than a length of the words, the computer program product comprising a computer readable storage medium having computer readable program code embodied therein that executes to perform operations, the operations comprising: generating a code alphabet having a number of symbols formed by merging symbols that provide variable length codings of the words, wherein the code alphabet is used by the deployed program. 2. The computer program product of claim 1 , wherein the operations further comprise: generating a word frequency distribution of frequencies of occurrences of all of the words; assigning values to different numbers of merged words based on the word frequency distribution; and selecting one of the numbers of the merged words based on the assigned values, wherein the number of symbols comprises the selected number of the merged words, wherein each symbol maps to one of the merged words. | 0.691047 |
8,375,320 | 1 | 2 | 1. A method for providing context-based task reminders, comprising: receiving a task item associated with a first reminder; receiving one or more context information data sources, wherein receiving one or more context information data sources includes receiving one or more context information data sources from one of a calendar data source, a contacts data source, a tasks data source, a presence data source, a location data source, an email data source, an Internet content data source, a social networking content data source, one or more electronic documents, a person proximity data source, a motion detection data source, a communications data source and a light sensing data source; parsing the task item for one or more task item information components; parsing the one or more context information data sources for determining information relevant to the received task item, including parsing content contained in the one or more context information data sources for one or more data sources information components; comparing the one or more data sources information components with the one or more task item information components to determine if the one or more data sources information components matches the one or more task item information components; if the one or more data sources information components matches the one or more task item information components, then determining the information relevant to the received task item including determining the data sources containing the one or more data sources information components matching the one or more task item information components that are relevant to the received task item; determining a revised reminder for the task item based on the information relevant to the received task item; and displaying the revised reminder for the task item based on the information relevant to the received task item. | 1. A method for providing context-based task reminders, comprising: receiving a task item associated with a first reminder; receiving one or more context information data sources, wherein receiving one or more context information data sources includes receiving one or more context information data sources from one of a calendar data source, a contacts data source, a tasks data source, a presence data source, a location data source, an email data source, an Internet content data source, a social networking content data source, one or more electronic documents, a person proximity data source, a motion detection data source, a communications data source and a light sensing data source; parsing the task item for one or more task item information components; parsing the one or more context information data sources for determining information relevant to the received task item, including parsing content contained in the one or more context information data sources for one or more data sources information components; comparing the one or more data sources information components with the one or more task item information components to determine if the one or more data sources information components matches the one or more task item information components; if the one or more data sources information components matches the one or more task item information components, then determining the information relevant to the received task item including determining the data sources containing the one or more data sources information components matching the one or more task item information components that are relevant to the received task item; determining a revised reminder for the task item based on the information relevant to the received task item; and displaying the revised reminder for the task item based on the information relevant to the received task item. 2. The method of claim 1 , wherein receiving the task item associated with the first reminder includes receiving the task item from a repository of tasks, wherein the first reminder for the received task item is set to occur at a first time; and wherein determining the revised reminder for the task item based on the information relevant to the received task item includes setting the revised reminder to occur at a second time based on the information relevant to the received task item. | 0.50102 |
9,858,528 | 1 | 6 | 1. A method programmed in a non-transitory memory of a device comprising: a. parsing target information into segments and prioritizing the segments, so that a highest priority segment is fact checked first, wherein priority is based on a relatedness of a segment to a current topic being discussed and when the segment was presented, wherein if the segment is not fact checked before a timeout threshold, then the segment is removed from a fact check queue, wherein a plurality of fact check queues are implemented, wherein a first fact check queue contains the segments to be fact checked in real-time, and a second fact check queue contains the segments to be fact checked in non-real-time; b. automatically fact checking the target information by comparing the target information with source information to generate a result; and c. automatically presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information, wherein comparing the target information with the source information begins searching the source information located on a fastest access time hardware device and continues to slower access time hardware devices. | 1. A method programmed in a non-transitory memory of a device comprising: a. parsing target information into segments and prioritizing the segments, so that a highest priority segment is fact checked first, wherein priority is based on a relatedness of a segment to a current topic being discussed and when the segment was presented, wherein if the segment is not fact checked before a timeout threshold, then the segment is removed from a fact check queue, wherein a plurality of fact check queues are implemented, wherein a first fact check queue contains the segments to be fact checked in real-time, and a second fact check queue contains the segments to be fact checked in non-real-time; b. automatically fact checking the target information by comparing the target information with source information to generate a result; and c. automatically presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information, wherein comparing the target information with the source information begins searching the source information located on a fastest access time hardware device and continues to slower access time hardware devices. 6. The method of claim 1 further comprising parsing the target information into phrases, parsing the phrases into words, counting the number of words in each phrase, and comparing each phrase with the source information containing the same number of words as the number of words in the phrase being compared. | 0.852207 |
8,713,003 | 28 | 30 | 28. The method of claim 17 , wherein the one or more interaction events comprise at least one of: application installation count, time spent using the application, application content printing, application content saving, application content copying, application content bookmarking, application content address copying, application content number of visits, application content scrolling, application content pointer clicking, application content zooming, application content switching, time spent reading application content, application content highlighting, application content emailing, application content address emailing, or application address emailing. | 28. The method of claim 17 , wherein the one or more interaction events comprise at least one of: application installation count, time spent using the application, application content printing, application content saving, application content copying, application content bookmarking, application content address copying, application content number of visits, application content scrolling, application content pointer clicking, application content zooming, application content switching, time spent reading application content, application content highlighting, application content emailing, application content address emailing, or application address emailing. 30. The method of claim 28 , wherein the one or more interaction events comprise at least one of: levels completed in a gaming application, scenes completed in a gaming application, or checkpoints completed in a gaining application. | 0.930497 |
9,280,906 | 7 | 8 | 7. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, identifying a first corresponding word, wherein the first corresponding word occurs in both an item of textual content and in an item of audio content; identifying a second corresponding word, wherein the second corresponding word occurs after the first corresponding word in both the item of textual content and in the item of audio content; identifying a third corresponding word, wherein the third corresponding word occurs after the second corresponding word in both the item of textual content and in the item of audio content; causing a synchronous audible and textual presentation of the first corresponding word; causing a textual presentation of the second corresponding word without synchronously audibly presenting the second corresponding word; prompting a user to speak the second corresponding word; obtaining a spoken response as audio input; determining that the spoken response includes the second corresponding word; and in response to determining that the spoken response includes the second corresponding word, causing audible presentation of the third corresponding word. | 7. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, identifying a first corresponding word, wherein the first corresponding word occurs in both an item of textual content and in an item of audio content; identifying a second corresponding word, wherein the second corresponding word occurs after the first corresponding word in both the item of textual content and in the item of audio content; identifying a third corresponding word, wherein the third corresponding word occurs after the second corresponding word in both the item of textual content and in the item of audio content; causing a synchronous audible and textual presentation of the first corresponding word; causing a textual presentation of the second corresponding word without synchronously audibly presenting the second corresponding word; prompting a user to speak the second corresponding word; obtaining a spoken response as audio input; determining that the spoken response includes the second corresponding word; and in response to determining that the spoken response includes the second corresponding word, causing audible presentation of the third corresponding word. 8. The computer-implemented method of claim 7 , wherein the first corresponding word and the second corresponding word are separated by a predetermined number of words in the textual content. | 0.83275 |
9,703,548 | 18 | 34 | 18. A non-transitory computer readable storage medium for generating project specific configuration data, the computer readable storage medium comprising computer code instructions executable by a computer and comprising instructions for: receiving, via a data interface, a plurality of items of project template data; storing, using a database connection, the project template data; receiving, via the data interface, question configuration data representing at least one question and at least one associated candidate answer; storing, using the database connection, the question configuration data; receiving, via the data interface, rule data representing a rule relating the project template data and the question configuration data; storing, using the database connection, the rule data; sending, via the data interface, question data from the question configuration data; receiving, via the data interface, answer data in response to the question data; and generating project specific configuration data from the project template data in accordance with the answer data and the rule data, wherein the rule data maps the answer data to the items of project template data to select items of project template data, wherein the selected items of project template data are added to build the project configuration data. | 18. A non-transitory computer readable storage medium for generating project specific configuration data, the computer readable storage medium comprising computer code instructions executable by a computer and comprising instructions for: receiving, via a data interface, a plurality of items of project template data; storing, using a database connection, the project template data; receiving, via the data interface, question configuration data representing at least one question and at least one associated candidate answer; storing, using the database connection, the question configuration data; receiving, via the data interface, rule data representing a rule relating the project template data and the question configuration data; storing, using the database connection, the rule data; sending, via the data interface, question data from the question configuration data; receiving, via the data interface, answer data in response to the question data; and generating project specific configuration data from the project template data in accordance with the answer data and the rule data, wherein the rule data maps the answer data to the items of project template data to select items of project template data, wherein the selected items of project template data are added to build the project configuration data. 34. The non-transitory computer readable storage medium as claimed in claim 18 , further comprising instructions for associating at least one rule with the at least one associated candidate answer. | 0.875158 |
9,268,818 | 20 | 29 | 20. A system for identifying a component of content recommended by a user, the system comprising: at least one processor; and a computer-readable medium coupled to the at least one processor having instructions stored thereon which, when executed by the at least one processor, causes the at least one processor to: receive, through a user interface of a social network application installed on a user device, an indication that a user recommended content displayed in a web browser on the user device, wherein the recommended content includes a plurality of different content components corresponding to different portions of the recommended content; responsive to receiving the indication that the user recommended content displayed in the web browser, retrieve candidate annotations that describe characteristics of each of the plurality of different content components; update the user interface presented at the user device with a request for the user to select at least one of the candidate annotations for at least one of the plurality of content components; receive, through the social network application, a user selection of at least one of the candidate annotations as an annotation for at least one of the plurality of content components; and distribute through a social network the user recommended content with the selected at least one candidate annotation at a presentation location corresponding to the at least one content component of the recommended content. | 20. A system for identifying a component of content recommended by a user, the system comprising: at least one processor; and a computer-readable medium coupled to the at least one processor having instructions stored thereon which, when executed by the at least one processor, causes the at least one processor to: receive, through a user interface of a social network application installed on a user device, an indication that a user recommended content displayed in a web browser on the user device, wherein the recommended content includes a plurality of different content components corresponding to different portions of the recommended content; responsive to receiving the indication that the user recommended content displayed in the web browser, retrieve candidate annotations that describe characteristics of each of the plurality of different content components; update the user interface presented at the user device with a request for the user to select at least one of the candidate annotations for at least one of the plurality of content components; receive, through the social network application, a user selection of at least one of the candidate annotations as an annotation for at least one of the plurality of content components; and distribute through a social network the user recommended content with the selected at least one candidate annotation at a presentation location corresponding to the at least one content component of the recommended content. 29. The system of claim 20 , wherein the indication that the user recommended content is an indication that the user selected a user recommendation control displayed in conjunction with the content. | 0.849085 |
9,269,028 | 3 | 4 | 3. The method of claim 1 , wherein the character set comprises the characters A,C,T, and G. | 3. The method of claim 1 , wherein the character set comprises the characters A,C,T, and G. 4. The method of claim 3 , wherein the character set comprises only the characters A,C,T, and G. | 0.966782 |
9,812,130 | 5 | 6 | 5. The method of claim 1 wherein the at least one trigger is linked to the second language model. | 5. The method of claim 1 wherein the at least one trigger is linked to the second language model. 6. The method of claim 5 wherein the at least one trigger comprises a plurality of triggers and wherein the second language model comprises a plurality of second language models. | 0.952125 |
8,981,971 | 1 | 4 | 1. A method for seismic exploration of the earth comprising the steps of applying to the earth a seismic input signal which is characterized by a seismic source wavelet I(t), recording a seismic trace f(t) in response to said seismic source wavelet, and transforming said seismic source wavelet I(t) into a zero-degree phase wavelet φ p (t) and a shifted 90 degree phase wavelet Ψ p (t), where the wavelets φ p (t) and Ψ p (t) span a two dimensional sub-space, creating a sub-space dictionary as
D s ={(φ p ,Ψ p )} pεΓ where Γ is a set of wavelets which are derived using φ p (t) wavelet and Ψ p (t) wavelet, and projecting said seismic trace f(t) onto said dictionary D s to find the best matching projection, with a residual determined after each projection matching, wherein the sum of said residuals determines the fidelity in data compression. | 1. A method for seismic exploration of the earth comprising the steps of applying to the earth a seismic input signal which is characterized by a seismic source wavelet I(t), recording a seismic trace f(t) in response to said seismic source wavelet, and transforming said seismic source wavelet I(t) into a zero-degree phase wavelet φ p (t) and a shifted 90 degree phase wavelet Ψ p (t), where the wavelets φ p (t) and Ψ p (t) span a two dimensional sub-space, creating a sub-space dictionary as
D s ={(φ p ,Ψ p )} pεΓ where Γ is a set of wavelets which are derived using φ p (t) wavelet and Ψ p (t) wavelet, and projecting said seismic trace f(t) onto said dictionary D s to find the best matching projection, with a residual determined after each projection matching, wherein the sum of said residuals determines the fidelity in data compression. 4. The method of claim 1 wherein said conventional existing wavelet dictionary includes Symlets. | 0.942993 |
8,903,802 | 1 | 2 | 1. A method for managing a new continuous query that includes folding a new continuous query into a shared continuous query plan (SCP) associated with a global range table, the method comprising: receiving via a computer readable storage medium a new continuous query; compiling the new continuous query to generate an iterator model plan (IMP) and an associated local range table that includes a list of range variables, each of which uniquely identifies an object in the new continuous query, and wherein the IMP corresponds to an execution plan generated for the new continuous query and comprises one or more IMP operators, each of which includes one or more expressions whose variables are associated with the local range table; analyzing the one or more IMP operators of the IMP and one or more SCP operators of the SCP to produce one or more variable transforms and one or more plan items; wherein the one or more variable transforms modify the one or more expressions of the one or more IMP operators by associating the one or more IMP operators with variables of a global range table; wherein the one or more plan items comprise one or more groups of the one or more IMP operators; applying the variable transforms to modify the variables of the one or more iterator model plan IMP operators; generating a continuous query operator based on each plan item included in the one or more plan items; and providing the generated continuous query operator to a shared continuous query plan. | 1. A method for managing a new continuous query that includes folding a new continuous query into a shared continuous query plan (SCP) associated with a global range table, the method comprising: receiving via a computer readable storage medium a new continuous query; compiling the new continuous query to generate an iterator model plan (IMP) and an associated local range table that includes a list of range variables, each of which uniquely identifies an object in the new continuous query, and wherein the IMP corresponds to an execution plan generated for the new continuous query and comprises one or more IMP operators, each of which includes one or more expressions whose variables are associated with the local range table; analyzing the one or more IMP operators of the IMP and one or more SCP operators of the SCP to produce one or more variable transforms and one or more plan items; wherein the one or more variable transforms modify the one or more expressions of the one or more IMP operators by associating the one or more IMP operators with variables of a global range table; wherein the one or more plan items comprise one or more groups of the one or more IMP operators; applying the variable transforms to modify the variables of the one or more iterator model plan IMP operators; generating a continuous query operator based on each plan item included in the one or more plan items; and providing the generated continuous query operator to a shared continuous query plan. 2. The method of claim 1 , further comprising providing the generated continuous query operator to a routing table. | 0.745575 |
8,346,775 | 1 | 3 | 1. A method for managing information in a computer system, the method comprising: (a) the computer receiving a request to store text in a table in a database, wherein the request contains the text; (b) the computer responsive to receiving the request containing the text, determining whether a first collection of textual information having a first concept that is related to a second concept for the text is present in the database, wherein the first concept is related to the second concept when the first concept is within a degree of relatedness to the second concept, wherein step (b) comprises: identifying, by the processing unit, a quantity of available resources for a data processing system in which the processor unit is located; and selecting, by the processing unit, the degree of relatedness based on the quantity of available resources such that the degree of relatedness increases as the quantity of available resources increases and decreases as the quantity of available resources decreases; (c) the computer, responsive to a determination that the first collection of textual information in the database having the first concept that is related to the second concept for the text is present in the database, associating the text with the first collection of textual information in the database; and (d) the computer, responsive to a determination that the first collection of textual information in the database having the first concept that is related to the second concept for the text is absent from the database, creating a second collection for the data with a third concept that is related to the second concept for the text within the degree of relatedness. | 1. A method for managing information in a computer system, the method comprising: (a) the computer receiving a request to store text in a table in a database, wherein the request contains the text; (b) the computer responsive to receiving the request containing the text, determining whether a first collection of textual information having a first concept that is related to a second concept for the text is present in the database, wherein the first concept is related to the second concept when the first concept is within a degree of relatedness to the second concept, wherein step (b) comprises: identifying, by the processing unit, a quantity of available resources for a data processing system in which the processor unit is located; and selecting, by the processing unit, the degree of relatedness based on the quantity of available resources such that the degree of relatedness increases as the quantity of available resources increases and decreases as the quantity of available resources decreases; (c) the computer, responsive to a determination that the first collection of textual information in the database having the first concept that is related to the second concept for the text is present in the database, associating the text with the first collection of textual information in the database; and (d) the computer, responsive to a determination that the first collection of textual information in the database having the first concept that is related to the second concept for the text is absent from the database, creating a second collection for the data with a third concept that is related to the second concept for the text within the degree of relatedness. 3. The method of claim 1 , wherein the first collection of textual information is a semantic grouping, and wherein step (b) comprises: performing, by the processing unit, a latent semantic analysis on the first concept and second concept, wherein the latent semantic analysis results in at least the degree of relatedness between the first concept and the second concept. | 0.796154 |
7,856,350 | 13 | 14 | 13. The computer implemented method of claim 12 wherein obtaining information includes: receiving results based on the query comprising the question focus and clue words based on the type of the definitional question; processing the results to obtain expansion terms; and querying the source of information with the question focus and selected expansion terms based on the results; and wherein generating the centroid vector comprises using the results from querying the source of information with the question focus and selected expansion terms based on the results. | 13. The computer implemented method of claim 12 wherein obtaining information includes: receiving results based on the query comprising the question focus and clue words based on the type of the definitional question; processing the results to obtain expansion terms; and querying the source of information with the question focus and selected expansion terms based on the results; and wherein generating the centroid vector comprises using the results from querying the source of information with the question focus and selected expansion terms based on the results. 14. The computer implemented method of claim 13 wherein generating the centroid vector includes generating the centroid vector based on co-occurring terms proximate the question focus in phrases and/or sentences in the results. | 0.542339 |
9,860,828 | 1 | 2 | 1. A method for performing a service search in a first wireless device supporting a Wi-Fi Direct service, the method for performing a service search comprises: transmitting a probe request frame including a hash value; receiving, from a second wireless device, a probe response frame including first service information corresponding to the hash value; transmitting a service search request frame including a search word to the second wireless device, wherein a wildcard search and an exact search are supported by the first wireless device and the second wireless device, wherein a service search type is set to either the wildcard search or the exact search by an application service platform (ASP) of the first wireless device, wherein the search word is set based on the service search type, wherein the search word includes a prefix string and a preset symbol when the service search type is set to the wildcard search, wherein the search word includes an exact string of a service name when the service search type is set to the exact search; and receiving, from the second wireless device, a service search response frame including second service information, wherein the second service information includes one or more service names having the prefix string when the service search type is set to the wildcard search, and wherein the second service information includes only a service name matching the service name included in the search word as the exact string when the service search type is set to the exact search. | 1. A method for performing a service search in a first wireless device supporting a Wi-Fi Direct service, the method for performing a service search comprises: transmitting a probe request frame including a hash value; receiving, from a second wireless device, a probe response frame including first service information corresponding to the hash value; transmitting a service search request frame including a search word to the second wireless device, wherein a wildcard search and an exact search are supported by the first wireless device and the second wireless device, wherein a service search type is set to either the wildcard search or the exact search by an application service platform (ASP) of the first wireless device, wherein the search word is set based on the service search type, wherein the search word includes a prefix string and a preset symbol when the service search type is set to the wildcard search, wherein the search word includes an exact string of a service name when the service search type is set to the exact search; and receiving, from the second wireless device, a service search response frame including second service information, wherein the second service information includes one or more service names having the prefix string when the service search type is set to the wildcard search, and wherein the second service information includes only a service name matching the service name included in the search word as the exact string when the service search type is set to the exact search. 2. The method of claim 1 , wherein the preset symbol corresponds to ‘*’ when the service search type is set to the wildcard search. | 0.807353 |
9,258,406 | 13 | 17 | 13. A method of controlling a mobile device, the method comprising: recognizing a conversation between users through mobile devices; verifying an intent of at least one user among the users based on the recognition result; and executing an additional function corresponding to the verified user's intent in a mobile device of the user. | 13. A method of controlling a mobile device, the method comprising: recognizing a conversation between users through mobile devices; verifying an intent of at least one user among the users based on the recognition result; and executing an additional function corresponding to the verified user's intent in a mobile device of the user. 17. The method of claim 13 , wherein the executing of the additional function displays business information corresponding to a predetermined region on the mobile device of the user when the verified user's intent is to determine an appointment place in the predetermined region with a counter party of the conversation. | 0.754992 |
9,679,060 | 8 | 12 | 8. A method of enhancing a user interaction with a search engine application, the search engine application including a graphical user interface including a query box for entry of a query and a background image around or behind the query box, comprising: (a) following the online activity of a user within one or more social media sites; (b) analyzing the user activity within the one or more social media sites followed in said step (a) to detect temporal event that is personal to the user; and (c) customizing the background image around or behind the query box in the graphical user interface based on the event of the user detected in said step (b), said customizing step comprising the step of customizing the background of the graphical user interface for the search engine application to include at least one of graphics and text related to the event personal to the user detected in said step (b). | 8. A method of enhancing a user interaction with a search engine application, the search engine application including a graphical user interface including a query box for entry of a query and a background image around or behind the query box, comprising: (a) following the online activity of a user within one or more social media sites; (b) analyzing the user activity within the one or more social media sites followed in said step (a) to detect temporal event that is personal to the user; and (c) customizing the background image around or behind the query box in the graphical user interface based on the event of the user detected in said step (b), said customizing step comprising the step of customizing the background of the graphical user interface for the search engine application to include at least one of graphics and text related to the event personal to the user detected in said step (b). 12. The method of claim 8 , further comprising the step of analyzing the user activity on the social media sites followed in said step (a) to correlate the user's activity with the user's interests. | 0.694444 |
9,589,053 | 10 | 12 | 10. An apparatus according to claim 8 wherein the processing circuitry is configured to construct the concept by identifying a plurality of terms related to the respective search term based upon the string matching and constructing the concept associated with the respective search term incorporating at least some of the terms related to the respective search term. | 10. An apparatus according to claim 8 wherein the processing circuitry is configured to construct the concept by identifying a plurality of terms related to the respective search term based upon the string matching and constructing the concept associated with the respective search term incorporating at least some of the terms related to the respective search term. 12. An apparatus according to claim 10 wherein the processing circuitry is configured to construct the concept by receiving input indicating the terms to be incorporated within the concept associated with the respective search term prior to conducting the search of the one or more data sources. | 0.917736 |
7,752,597 | 9 | 14 | 9. A computer implemented process for generating a runtime environment for a class of a layered software application, said process comprising: opening a layer file folder, wherein said layer file folder is located in a computer file system and said layer file folder is associated with a software development layer of said layered software application, said software development layer representing a unique version of said layered software application, and wherein said layer file folder is for storing classes belonging to a layer of said layered software application; opening a class file stored in said layer file folder, wherein said class file comprises a text file representing said class of said layered software application, and wherein said class file comprises data describing a method performed as part of said class; and determining which information in the class file of said layer folder should be loaded into the runtime environment being generated including determining if said method of said class file has been previously loaded into said runtime environment. | 9. A computer implemented process for generating a runtime environment for a class of a layered software application, said process comprising: opening a layer file folder, wherein said layer file folder is located in a computer file system and said layer file folder is associated with a software development layer of said layered software application, said software development layer representing a unique version of said layered software application, and wherein said layer file folder is for storing classes belonging to a layer of said layered software application; opening a class file stored in said layer file folder, wherein said class file comprises a text file representing said class of said layered software application, and wherein said class file comprises data describing a method performed as part of said class; and determining which information in the class file of said layer folder should be loaded into the runtime environment being generated including determining if said method of said class file has been previously loaded into said runtime environment. 14. The method of claim 9 , wherein said determining if said method of said class file has been previously loaded into said runtime environment comprises: loading said method into said runtime environment to override a previously loaded version of said method, wherein said previously loaded version of said method is from a lower precedence layer of said layered software application. | 0.711826 |
8,239,366 | 1 | 10 | 1. A method, implemented at least in part on a microprocessor, of performing a search for content on the Internet, the method comprising: receiving voice input provided from a user; and generating at least one text search query for a plurality of Internet-accessible search engines that search for content on the Internet, wherein the at least one text search query is generated, at least in part, by performing speech recognition on the voice input; wherein the at least one text search query comprises at least two text search queries; wherein the act of generating further comprises: generating a first of the at least two text search queries, at least in part by performing speech recognition on the voice input using a first language model associated with a first of the plurality of search engines; and generating a second of the at least two text search queries, at least in part by performing speech recognition on the voice input using a second language model, different from the first language model, associated with a second of the plurality of search engines; wherein the first language model is one that was trained on content indexed by the first of the plurality of search engines; wherein the first of the plurality of search engines is a site-specific search engine; and wherein the second of the plurality of search engines is a general search engine. | 1. A method, implemented at least in part on a microprocessor, of performing a search for content on the Internet, the method comprising: receiving voice input provided from a user; and generating at least one text search query for a plurality of Internet-accessible search engines that search for content on the Internet, wherein the at least one text search query is generated, at least in part, by performing speech recognition on the voice input; wherein the at least one text search query comprises at least two text search queries; wherein the act of generating further comprises: generating a first of the at least two text search queries, at least in part by performing speech recognition on the voice input using a first language model associated with a first of the plurality of search engines; and generating a second of the at least two text search queries, at least in part by performing speech recognition on the voice input using a second language model, different from the first language model, associated with a second of the plurality of search engines; wherein the first language model is one that was trained on content indexed by the first of the plurality of search engines; wherein the first of the plurality of search engines is a site-specific search engine; and wherein the second of the plurality of search engines is a general search engine. 10. The method of claim 1 , wherein the first language model is one that was trained on content related to the content indexed by the first of the plurality of search engines in addition to the content indexed by the first of the plurality of search engines. | 0.877376 |
9,916,146 | 8 | 11 | 8. A system for analyzing executable software code by decompiling the executable code, the system comprising: a first processor; and a first memory in communication with the first processor, the first memory comprising instructions which, when executed by a processing unit comprising at least one of the first processor and a second processor, the processing unit being in communication with a memory module comprising at least one of the first memory and a second memory, program the processing unit to: parse said executable code to identify one or more data flows; recursively, for at least one identified data flow: discover a fitting data flow model; optimize said fitting data flow model to form a refined data flow model; propagate said refined data flow model until substantially all data variables are modeled; and express said refined data flow model in an intermediate representation; parse said executable code to identify one or more control flows; recursively, for at least one identified control flow: discover a fitting control flow model comprising one or more control branches; optimize said fitting control flow model to form a refined control flow model; propagate said refined control flow model until substantially all said control branches are modeled; and express said refined control flow model in an intermediate representation, wherein said refined data flow model and said refined control flow model express a nanocode model of said executable software code in said intermediate representation; and perform vulnerability analysis of the complete nanocode model to identify at least one of a flaw and a vulnerability in said executable code. | 8. A system for analyzing executable software code by decompiling the executable code, the system comprising: a first processor; and a first memory in communication with the first processor, the first memory comprising instructions which, when executed by a processing unit comprising at least one of the first processor and a second processor, the processing unit being in communication with a memory module comprising at least one of the first memory and a second memory, program the processing unit to: parse said executable code to identify one or more data flows; recursively, for at least one identified data flow: discover a fitting data flow model; optimize said fitting data flow model to form a refined data flow model; propagate said refined data flow model until substantially all data variables are modeled; and express said refined data flow model in an intermediate representation; parse said executable code to identify one or more control flows; recursively, for at least one identified control flow: discover a fitting control flow model comprising one or more control branches; optimize said fitting control flow model to form a refined control flow model; propagate said refined control flow model until substantially all said control branches are modeled; and express said refined control flow model in an intermediate representation, wherein said refined data flow model and said refined control flow model express a nanocode model of said executable software code in said intermediate representation; and perform vulnerability analysis of the complete nanocode model to identify at least one of a flaw and a vulnerability in said executable code. 11. The system of claim 8 , wherein: the identified flaw comprises at least one of a software flaw, a programming practice that is designated unacceptable, and a pointer to a data structure designated unacceptable; and the identified vulnerability comprises at least one of: a software vulnerability exploitable via an attack, a programming practice that is designated unacceptable, a pointer to a data structure designated unacceptable, an unchecked buffer, and an embedded malicious code. | 0.501018 |
7,617,183 | 13 | 14 | 13. The method as claimed in claim 12 , further comprising expanding each term to remove NOT operators. | 13. The method as claimed in claim 12 , further comprising expanding each term to remove NOT operators. 14. The method as claimed in claim 13 , wherein the sum of terms are expanded using Boolean logic. | 0.952748 |
7,647,345 | 1 | 8 | 1. A method implemented by an information processing device, for processing a plurality of documents including a set of documents including primarily text information, said method comprising: for each document including primarily text information: analyzing, by the information processing device, said text information of said document to detect a set of words relating to said document; detecting, by the information processing device, for each of said set of words a respective degree of relative significance based on at least one of a frequency and a nature of occurrence of the words with respect to said document; selecting a subset of most significant words from said set of words, said subset containing significantly less words than said set of words; generating a pseudo-image representative of said document, said representative pseudo-image including said selected subset of words arranged in a predetermined image layout such that: a most significant word of said subset is represented with most prominence at a first predetermined region within said representative pseudo-image, and one or more other word(s) of said subset are represented at at least one other predetermined region of said representative pseudo-image in dependence on the corresponding degree of relative significance of those word(s); and displaying in a sequence over time said set of documents including the most significant word in the first predetermined region and the one or more other word(s) in the at least one other predetermined region. | 1. A method implemented by an information processing device, for processing a plurality of documents including a set of documents including primarily text information, said method comprising: for each document including primarily text information: analyzing, by the information processing device, said text information of said document to detect a set of words relating to said document; detecting, by the information processing device, for each of said set of words a respective degree of relative significance based on at least one of a frequency and a nature of occurrence of the words with respect to said document; selecting a subset of most significant words from said set of words, said subset containing significantly less words than said set of words; generating a pseudo-image representative of said document, said representative pseudo-image including said selected subset of words arranged in a predetermined image layout such that: a most significant word of said subset is represented with most prominence at a first predetermined region within said representative pseudo-image, and one or more other word(s) of said subset are represented at at least one other predetermined region of said representative pseudo-image in dependence on the corresponding degree of relative significance of those word(s); and displaying in a sequence over time said set of documents including the most significant word in the first predetermined region and the one or more other word(s) in the at least one other predetermined region. 8. The method according to claim 1 , wherein said time-sequence of representative pseudo-images are displayed with a substantially constant image display size. | 0.761261 |
8,484,040 | 18 | 20 | 18. A data processing system, comprising: a processor comprising: a receiver for raw activity data, the data comprising an audio stream; an automatic speech recognition component for processing the audio stream; a topic detector; a sub-activity detection component; and a connection strength calculating component, wherein the processor is operative to perform the steps of: with the receiver receiving a data stream of a multi-participant meeting having participants, wherein multiple topics are discussed; using the topic detector and the sub-activity detection component, analyzing the data stream to detect one of the topics and to define topical sub-activities of the one topic, the topical sub-activities being performed by at least a portion of the participants; identifying respective contributions to the one topic by two of the participants in the topical sub-activities associated therewith; making an evaluation of the respective contributions to selected ones of the topical sub-activities; and using the connection strength calculating component for calculating a connection weight between the two participants based on the evaluation of the respective contributions. | 18. A data processing system, comprising: a processor comprising: a receiver for raw activity data, the data comprising an audio stream; an automatic speech recognition component for processing the audio stream; a topic detector; a sub-activity detection component; and a connection strength calculating component, wherein the processor is operative to perform the steps of: with the receiver receiving a data stream of a multi-participant meeting having participants, wherein multiple topics are discussed; using the topic detector and the sub-activity detection component, analyzing the data stream to detect one of the topics and to define topical sub-activities of the one topic, the topical sub-activities being performed by at least a portion of the participants; identifying respective contributions to the one topic by two of the participants in the topical sub-activities associated therewith; making an evaluation of the respective contributions to selected ones of the topical sub-activities; and using the connection strength calculating component for calculating a connection weight between the two participants based on the evaluation of the respective contributions. 20. The data processing system according to claim 18 , wherein analyzing the data stream to define topical sub-activities comprises: identifying the participants; demarcating the topical sub-activities by speech pauses of the identified participants; and subdividing the demarcated topical sub-activities by detecting replacement times wherein one speaker is replaced by another speaker among the identified participants. | 0.523756 |
9,002,943 | 4 | 5 | 4. A computer-implemented method comprising: receiving, by a gateway server from a mobile device, a first request to retrieve content from a content server, the request identifying a subscriber using a mobile device, the mobile device, the gateway server, and the content server all being remote and separate from each other; associating, by the gateway server, the identified subscriber with a corresponding user profile, the user profile providing a plurality of rules that define how content is to be displayed; transmitting, by the gateway server to the content server, a second request to retrieve the content from the content server; receiving, by the gateway server, the content from the content server; parsing the content by: deconstructing the content and mapping the deconstructed content to a first document object model, and transforming the mapped content according to the plurality of rules defined in the user profile to generate a second document object model; and transmitting, by the gateway server to the mobile device, the transformed content for rendering on the mobile device. | 4. A computer-implemented method comprising: receiving, by a gateway server from a mobile device, a first request to retrieve content from a content server, the request identifying a subscriber using a mobile device, the mobile device, the gateway server, and the content server all being remote and separate from each other; associating, by the gateway server, the identified subscriber with a corresponding user profile, the user profile providing a plurality of rules that define how content is to be displayed; transmitting, by the gateway server to the content server, a second request to retrieve the content from the content server; receiving, by the gateway server, the content from the content server; parsing the content by: deconstructing the content and mapping the deconstructed content to a first document object model, and transforming the mapped content according to the plurality of rules defined in the user profile to generate a second document object model; and transmitting, by the gateway server to the mobile device, the transformed content for rendering on the mobile device. 5. A method as in claim 4 , wherein the parsing is performed by the gateway server. | 0.935957 |
8,520,983 | 15 | 19 | 15. A computer system for selectively recognizing text in an image, comprising: a computer-readable storage medium comprising executable computer program code for: an image User Interface (UI) module for: displaying the image on a touch sensitive display device; detecting an underline gesture associated with an area of the touch sensitive display device, the area of the touch sensitive display device associated with the underline gesture being vertical relative to an orientation of the image; a text region identification module for identifying a text region in the image associated with the area of the touch sensitive display device, the text region comprising text displayed vertically relative to the orientation of the image; and an OCR module for recognizing the text in the text region using OCR technology. | 15. A computer system for selectively recognizing text in an image, comprising: a computer-readable storage medium comprising executable computer program code for: an image User Interface (UI) module for: displaying the image on a touch sensitive display device; detecting an underline gesture associated with an area of the touch sensitive display device, the area of the touch sensitive display device associated with the underline gesture being vertical relative to an orientation of the image; a text region identification module for identifying a text region in the image associated with the area of the touch sensitive display device, the text region comprising text displayed vertically relative to the orientation of the image; and an OCR module for recognizing the text in the text region using OCR technology. 19. The computer system of claim 15 , wherein identifying the text region in the image comprises: identifying an area of the image displayed on the area of the touch sensitive display device; determining an angle of the area of the image and a horizontal axis of the touch sensitive display device; determining a skew angle of the text region based on the angle of the area of the image; correcting the skew angle by rotating at least a portion of the image including the text region; and identifying the text region in the at least a portion of the image. | 0.500898 |
7,640,232 | 56 | 58 | 56. The system of claim 44 , wherein the received search parameters have an applicability to one or more subjects, the system further comprising: means for integrating any of the specified received search parameters with a search query, wherein the integrated received search parameters are applicable to a determined subject of the received search query. | 56. The system of claim 44 , wherein the received search parameters have an applicability to one or more subjects, the system further comprising: means for integrating any of the specified received search parameters with a search query, wherein the integrated received search parameters are applicable to a determined subject of the received search query. 58. The system of claim 56 , wherein the determined subject matter is based upon the received search query. | 0.98092 |
8,612,234 | 8 | 13 | 8. A system comprising: a processor; and a storage device having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving an input having a speech segment and a non-speech segment; establishing a first restriction of recognizing only speech states during the speech segment; establishing a second restriction of recognizing only non-speech states during the non-speech segment; generating a hypothesis lattice, wherein the hypothesis lattice allows any sequence of speech states and non-speech states; and generating a reference lattice, wherein the reference lattice is based on the hypothesis lattice and conforms to the first restriction and the second restriction. | 8. A system comprising: a processor; and a storage device having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving an input having a speech segment and a non-speech segment; establishing a first restriction of recognizing only speech states during the speech segment; establishing a second restriction of recognizing only non-speech states during the non-speech segment; generating a hypothesis lattice, wherein the hypothesis lattice allows any sequence of speech states and non-speech states; and generating a reference lattice, wherein the reference lattice is based on the hypothesis lattice and conforms to the first restriction and the second restriction. 13. The system of claim 8 , wherein the reference lattice is redefined at each iteration of training | 0.809886 |
10,019,514 | 1 | 4 | 1. A computerized-method of searching for an element in speech related documents, the method comprising: transcribing, by a controller, a set of digital speech recordings stored in a speech recording database to a set of digital phoneme strings and including the phoneme strings in a set of digital phonetic transcriptions; reverse-indexing, by the controller, using one or more parser rules, the phonetic transcriptions according to one or more phonemes and storing the reverse-indexed transcriptions in an inverted index database including a mapping to documents such that the one or more phonemes can be used as a search key for searching in the phonetic transcriptions for a phoneme string; transcribing, by the controller, a textual search term into a set of search phoneme strings; and using, by the controller, the set of search phoneme strings to search for the textual search term in the set of phonetic transcriptions and produce a list of the documents ranked according to the match of the phoneme strings to the documents. | 1. A computerized-method of searching for an element in speech related documents, the method comprising: transcribing, by a controller, a set of digital speech recordings stored in a speech recording database to a set of digital phoneme strings and including the phoneme strings in a set of digital phonetic transcriptions; reverse-indexing, by the controller, using one or more parser rules, the phonetic transcriptions according to one or more phonemes and storing the reverse-indexed transcriptions in an inverted index database including a mapping to documents such that the one or more phonemes can be used as a search key for searching in the phonetic transcriptions for a phoneme string; transcribing, by the controller, a textual search term into a set of search phoneme strings; and using, by the controller, the set of search phoneme strings to search for the textual search term in the set of phonetic transcriptions and produce a list of the documents ranked according to the match of the phoneme strings to the documents. 4. The method of claim 1 , comprising: dividing the set of phonetic transcriptions into a plurality of short sub-documents; and indexing the sub-documents according to one or more phonemes such that a phoneme can be used as a search key for searching in the sub-documents for the phoneme. | 0.55418 |
10,152,588 | 4 | 5 | 4. The system of claim 1 , wherein determining to accept the proposed password comprises: determining a similarity score based on a comparison between the first set of formation rules and the second set of formation rules; and determining that the similarity score is below a predetermined threshold score. | 4. The system of claim 1 , wherein determining to accept the proposed password comprises: determining a similarity score based on a comparison between the first set of formation rules and the second set of formation rules; and determining that the similarity score is below a predetermined threshold score. 5. The system of claim 4 , wherein the first set of formation rules comprises a first weight and the second set of formation rules comprises a second weight different from the first weight. | 0.909914 |
8,473,293 | 2 | 3 | 2. The system of claim 1 , the operations further comprising: identifying a candidate term score minimum threshold associated with the speech recognition dictionary; and determining whether the generated candidate term score for the identified candidate term meets or exceeds the candidate term score minimum threshold. | 2. The system of claim 1 , the operations further comprising: identifying a candidate term score minimum threshold associated with the speech recognition dictionary; and determining whether the generated candidate term score for the identified candidate term meets or exceeds the candidate term score minimum threshold. 3. The system of claim 2 , where the identified candidate term is not included within the speech recognition dictionary, the operations further comprising: adding the identified candidate term to the speech recognition dictionary in response to the determination that the generated candidate term score for the identified candidate term meets or exceeds the candidate term score minimum threshold. | 0.797862 |
8,684,746 | 11 | 12 | 11. A computer program product, comprising: a non-transitory computer-readable medium having instructions stored thereon executable by at least one processor, comprising: code to receive, from a first user through a first user electronic interface adapter at a first educational institution, a first set of questions and a difficulty and a type for each question of the first set of questions; code to receive, from a second user through a second user electronic interface adapter at a second educational institution, a second set of questions and a difficulty and a type for each question of the second set of questions; code to combine the first set of questions and the second set of questions into a global question bank; code to receive, from the first user, a selection of questions from the second set of questions; code to form a proficiency examination from the first set of questions and the selection of questions; code to display through a first display adapter, to a student, a first random question of a first question type from the proficiency examination; and code to receive, from the student, a first answer corresponding to the first random question; code to determine if the first answer is a correct answer for the first random question; code to increasing a current difficulty if the first answer is the correct answer; code to decrease the current difficulty if the first answer is not the correct answer; code to display, to a student, a second random question at the current difficulty; code to calculate a number of questions displayed to the student of the first question type; code to display to the student through the first display adapter, a second random question of the first question type at the current difficulty if the number of first question types displayed does not exceed the first question type threshold; and code to display to the student through the first display adapter, a third random question of a second question type at the current difficulty if the number of first question types displayed does not exceed the first question type threshold. | 11. A computer program product, comprising: a non-transitory computer-readable medium having instructions stored thereon executable by at least one processor, comprising: code to receive, from a first user through a first user electronic interface adapter at a first educational institution, a first set of questions and a difficulty and a type for each question of the first set of questions; code to receive, from a second user through a second user electronic interface adapter at a second educational institution, a second set of questions and a difficulty and a type for each question of the second set of questions; code to combine the first set of questions and the second set of questions into a global question bank; code to receive, from the first user, a selection of questions from the second set of questions; code to form a proficiency examination from the first set of questions and the selection of questions; code to display through a first display adapter, to a student, a first random question of a first question type from the proficiency examination; and code to receive, from the student, a first answer corresponding to the first random question; code to determine if the first answer is a correct answer for the first random question; code to increasing a current difficulty if the first answer is the correct answer; code to decrease the current difficulty if the first answer is not the correct answer; code to display, to a student, a second random question at the current difficulty; code to calculate a number of questions displayed to the student of the first question type; code to display to the student through the first display adapter, a second random question of the first question type at the current difficulty if the number of first question types displayed does not exceed the first question type threshold; and code to display to the student through the first display adapter, a third random question of a second question type at the current difficulty if the number of first question types displayed does not exceed the first question type threshold. 12. The computer program product of claim 11 , in which the medium further comprises: code to calculate numerical scores for questions answered correctly by the student at each difficulty; and code to determine a placement for the student based, in part, on the numerical scores. | 0.501786 |
7,761,461 | 7 | 9 | 7. The method of claim 1 , wherein the first physical representation is a hierarchical representation and the second physical representation is a relational representation. | 7. The method of claim 1 , wherein the first physical representation is a hierarchical representation and the second physical representation is a relational representation. 9. The method of claim 7 , wherein each data structure is a table of the relational representation. | 0.966372 |
9,743,357 | 26 | 27 | 26. An energy harvesting device for generating electrical energy and for managing the energy to power a communication device; the device comprising: a. at least a storage medium; b. at least a communication apparatus communicatively coupled to a charging circuit apparatus and in association with a control apparatus; and c. said charging circuit apparatus further comprises sensors embedded in silicon substrate and in association with the storage medium to provide at least one of a communication medium, a detection platform, a communication clarity, a detection selectivity, energy harvesting, and a detection sensitivity. | 26. An energy harvesting device for generating electrical energy and for managing the energy to power a communication device; the device comprising: a. at least a storage medium; b. at least a communication apparatus communicatively coupled to a charging circuit apparatus and in association with a control apparatus; and c. said charging circuit apparatus further comprises sensors embedded in silicon substrate and in association with the storage medium to provide at least one of a communication medium, a detection platform, a communication clarity, a detection selectivity, energy harvesting, and a detection sensitivity. 27. The energy harvesting communication device of claim 26 , wherein said storage apparatus further comprises at least one of: an IC card; a SIM card; a memory apparatus; a chip; a capacitive apparatus; a battery apparatus; a case; a cover; a housing; a cell platform; an integrated storage and management circuit; an integrated energy storage and management circuit; a chip comprising carbon nanotubes in association with photonic crystals; means for converting thermal energy into electrical energy; a plasmonic crystal chip; a photonic crystal chip; a silicon substrate nano-fiber plasmonic embedded with ferrous material structure; a chip having a reflective layer; a transparent conducting nanomaterial structure. | 0.838869 |
9,058,327 | 1 | 5 | 1. A method comprising: updating, by a predictive coding system, a set of training documents based on a selected portion of a training document of the set to obtain an updated set of training documents; searching, by the predictive coding system, content within other training documents in the updated set using a machine learning engine based on the selected portion and variations of the selected portion; determining a probability measure for the content; and classifying, by the predictive coding system, a second training document containing the content based on the probability measure. | 1. A method comprising: updating, by a predictive coding system, a set of training documents based on a selected portion of a training document of the set to obtain an updated set of training documents; searching, by the predictive coding system, content within other training documents in the updated set using a machine learning engine based on the selected portion and variations of the selected portion; determining a probability measure for the content; and classifying, by the predictive coding system, a second training document containing the content based on the probability measure. 5. The method of claim 1 , further comprising: identifying additional documents to add to the updated set; receiving input for the additional documents; and modifying the updated set of training documents to include at least one of the additional documents based on the received input associated with the additional documents. | 0.665984 |
8,898,173 | 1 | 3 | 1. A computer-implemented method performed by a data processing apparatus, comprising: receiving, by one or more processors, a search query and a geographic region associated with the search query, the geographic region having a central location and a bounding polygon; identifying, by the one or more processors, a plurality of candidate search results responsive to the search query, each candidate search result being associated with a geographic location; calculating, by the one or more processors and for each candidate search result, a central distance score, wherein the central distance score comprises a score based on a first geographic distance between the geographic location of the candidate search result and the central location of the geographic region; calculating, by the one or more processors and for each candidate search result, a polygon distance score, wherein the polygon distance score changes as a scoring function of a second geographic distance between the geographic location of the candidate search result and an edge of the bounding polygon of the geographic region nearest the geographic location of the candidate search result, wherein the scoring function uses the second geographic distance as an input and the polygon distance score is subject to a score limit; calculating, by the one or more processors and for each candidate search result, a respective location relevance score based on the central distance score and the polygon distance score for the candidate search result; and ranking, by the one or more processors, the plurality of candidate search results based at least in part on the calculated location relevance scores of the plurality of candidate search results. | 1. A computer-implemented method performed by a data processing apparatus, comprising: receiving, by one or more processors, a search query and a geographic region associated with the search query, the geographic region having a central location and a bounding polygon; identifying, by the one or more processors, a plurality of candidate search results responsive to the search query, each candidate search result being associated with a geographic location; calculating, by the one or more processors and for each candidate search result, a central distance score, wherein the central distance score comprises a score based on a first geographic distance between the geographic location of the candidate search result and the central location of the geographic region; calculating, by the one or more processors and for each candidate search result, a polygon distance score, wherein the polygon distance score changes as a scoring function of a second geographic distance between the geographic location of the candidate search result and an edge of the bounding polygon of the geographic region nearest the geographic location of the candidate search result, wherein the scoring function uses the second geographic distance as an input and the polygon distance score is subject to a score limit; calculating, by the one or more processors and for each candidate search result, a respective location relevance score based on the central distance score and the polygon distance score for the candidate search result; and ranking, by the one or more processors, the plurality of candidate search results based at least in part on the calculated location relevance scores of the plurality of candidate search results. 3. The method of claim 1 , wherein the polygon distance score is based on a piece-wise continuous function that is continuous across the polygon boundary, the piece-wise continuous function having a first part that increases with the second geographic distance when the geographic location is within the bounding polygon and a second part that decreases with the second geographic distance when the geographic location is outside of the bounding polygon further, comprising: determining, for each candidate search result, whether the geographic location is within the bounding polygon; and calculating the polygon distance score using the first part of the piece-wise continuous function if the geographic location is within the bounding polygon and using the second part of the piece-wise continuous function if the geographic location is outside of the bounding polygon. | 0.524537 |
9,047,275 | 10 | 12 | 10. The method of claim 8 further comprising, if the degree of correspondence is sufficiently significant, confirming the hypothesis and saving correspondence between the first and second fragments, otherwise changing boundaries of the fragment so as to select a new hypothesis. | 10. The method of claim 8 further comprising, if the degree of correspondence is sufficiently significant, confirming the hypothesis and saving correspondence between the first and second fragments, otherwise changing boundaries of the fragment so as to select a new hypothesis. 12. The method of claim 10 wherein saving correspondence between the first and second fragments further comprise saving correspondence between their syntactic structures and saving correspondence between their semantic structures. | 0.936217 |
4,393,502 | 20 | 21 | 20. The method of claim 17 further comprising the steps of receiving said transmission block; using said error detecting code and the words of said odd and even sub-blocks to detect errors which may be present in the sub-blocks; selectively delaying the words in said odd sub-block and in said even sub-block to de-interleave said odd information and error-correcting words and to de-interleave said even information and error-correcting words; using the at least one de-interleaved odd error-correcting word to correct odd information words which have been detected as being erroneous and using the at least one de-interleaved even error-correcting word to correct even information words which have been detected as being erroneous; approximating a correct odd or even information word to replace an uncorrectable information word by interpolating adjacent correct even or odd information words, respectively; and recovering a corrected sequence of information words. | 20. The method of claim 17 further comprising the steps of receiving said transmission block; using said error detecting code and the words of said odd and even sub-blocks to detect errors which may be present in the sub-blocks; selectively delaying the words in said odd sub-block and in said even sub-block to de-interleave said odd information and error-correcting words and to de-interleave said even information and error-correcting words; using the at least one de-interleaved odd error-correcting word to correct odd information words which have been detected as being erroneous and using the at least one de-interleaved even error-correcting word to correct even information words which have been detected as being erroneous; approximating a correct odd or even information word to replace an uncorrectable information word by interpolating adjacent correct even or odd information words, respectively; and recovering a corrected sequence of information words. 21. The method of claim 20 wherein each received odd and even sub-block is a Q sub-block formed of a Q-parity word interleaved with a P sub-block and even P sub-block is formed of a P-parity word and information words which have been selectively delayed to form interleaved words; and wherein said steps of de-interleaving and error-correcting comprise selectively delaying the words in said odd Q sub-block and in said even Q sub-block to de-interleave said odd information words, said Q-parity word and said P-parity word of each odd Q sub-block and to de-interleave said even information words, said Q-parity word and said P-parity word of each even Q sub-block; using the odd Q-parity word to correct odd information and P-parity words which have been detected as being erroneous so as to form a corrected odd P sub-block and using the even Q-parity word to correct those even information and P-parity words which have been detected as being erroneous so as to form a corrected even P sub-block; selectively delaying the words in said corrected odd P sub-block and in said corrected even P sub-block to de-interleave said odd information and P-parity words of said odd P sub-block and to de-interleave said even information and P-parity words of said even P sub-block; and using the odd P-parity word to correct those de-interleaved odd information words which remain erroneous and using the even P-parity word to correct those de-interleaved even information words which remain erroneous. | 0.500335 |
9,613,621 | 10 | 18 | 10. An electronic apparatus, comprising: an input unit, receiving a speech signal; a storage unit, storing a plurality of program code segments; and a processing unit, coupled to the input unit and the storage unit, the processing unit executing a plurality of commands through the program code segments, and the commands comprising: obtaining a phonetic transcription sequence of the speech signal according to an acoustic model; obtaining a plurality of syllable sequences and a plurality of corresponding phonetic spelling matching probabilities according to the phonetic transcription sequence and a syllable acoustic lexicon; obtaining an intonation information corresponding to each of the syllable sequences according to a tone of the phonetic transcription sequence; obtaining a plurality of phonetic spelling sequences and a plurality of phonetic spelling sequence probabilities, from the language model, according to each phonetic spelling of phonetic spelling sequences and the intonation information; obtaining, from the language model, a plurality of text sequences corresponding to the phonetic transcription sequence, and a plurality of spelling sequence probabilities; generating a plurality of associated probabilities by multiplying each of the phonetic spelling matching probabilities and each of the spelling sequence probabilities; and selecting the text sequence corresponding to a largest one among the associated probabilities to be used as a recognition result of the speech signal, wherein different intonation information in the language model is divided into different semantemes, and the semantemes are corresponding to different phonetic spelling sequences. | 10. An electronic apparatus, comprising: an input unit, receiving a speech signal; a storage unit, storing a plurality of program code segments; and a processing unit, coupled to the input unit and the storage unit, the processing unit executing a plurality of commands through the program code segments, and the commands comprising: obtaining a phonetic transcription sequence of the speech signal according to an acoustic model; obtaining a plurality of syllable sequences and a plurality of corresponding phonetic spelling matching probabilities according to the phonetic transcription sequence and a syllable acoustic lexicon; obtaining an intonation information corresponding to each of the syllable sequences according to a tone of the phonetic transcription sequence; obtaining a plurality of phonetic spelling sequences and a plurality of phonetic spelling sequence probabilities, from the language model, according to each phonetic spelling of phonetic spelling sequences and the intonation information; obtaining, from the language model, a plurality of text sequences corresponding to the phonetic transcription sequence, and a plurality of spelling sequence probabilities; generating a plurality of associated probabilities by multiplying each of the phonetic spelling matching probabilities and each of the spelling sequence probabilities; and selecting the text sequence corresponding to a largest one among the associated probabilities to be used as a recognition result of the speech signal, wherein different intonation information in the language model is divided into different semantemes, and the semantemes are corresponding to different phonetic spelling sequences. 18. The electronic apparatus of claim 10 , wherein the commands further comprise: selecting a training data from the corpus data according to a predetermined setting, wherein the training data is one of training results of different languages, dialects or different pronunciation habits. | 0.777174 |
9,678,518 | 9 | 12 | 9. The thermostat of claim 1 , wherein the thermostat is further configured to receive an appliance error from the at least one appliance, generate at least one of a service request and a maintenance request, send a push notification to the remote controller, in response to at least one of the received appliance error, the generated service request, and the maintenance request, and wherein the thermostat is further configured to generate status information and to send the status information to the remote controller. | 9. The thermostat of claim 1 , wherein the thermostat is further configured to receive an appliance error from the at least one appliance, generate at least one of a service request and a maintenance request, send a push notification to the remote controller, in response to at least one of the received appliance error, the generated service request, and the maintenance request, and wherein the thermostat is further configured to generate status information and to send the status information to the remote controller. 12. The thermostat of claim 9 , wherein a controller user interface is configured to: receive remote controller data from a user through the controller user interface; and transfer the received status information to the maintenance person in response to an input by the user on the controller user interface. | 0.832061 |
7,907,705 | 19 | 22 | 19. A computer readable storage medium comprising instructions embodied thereon to perform a method for capturing information from a live conversation between an operator and a customer, comprising: designating a context for the live conversation between the operator and the customer wherein the context is a form viewed on a computer screen and actively in use by the operator; setting, by the operator during the live conversation, a visual cue by physically moving a cursor to an information field in the form; monitoring the live conversation in response to setting the visual cue, wherein the visual cue triggers the conversion of the live conversation to text; recognizing at least one portion of the live conversation as a text portion after converting the live conversation to text; interpreting one or more cues in the live conversation, wherein the one or more cues comprises at least the visual cue; relating the one or more cues to the information field associated with the context for the live conversation; and storing information obtained from the text portion of the live conversation into the information field, wherein the information obtained from the text portion comprises at least one word spoken after the one or more cues. | 19. A computer readable storage medium comprising instructions embodied thereon to perform a method for capturing information from a live conversation between an operator and a customer, comprising: designating a context for the live conversation between the operator and the customer wherein the context is a form viewed on a computer screen and actively in use by the operator; setting, by the operator during the live conversation, a visual cue by physically moving a cursor to an information field in the form; monitoring the live conversation in response to setting the visual cue, wherein the visual cue triggers the conversion of the live conversation to text; recognizing at least one portion of the live conversation as a text portion after converting the live conversation to text; interpreting one or more cues in the live conversation, wherein the one or more cues comprises at least the visual cue; relating the one or more cues to the information field associated with the context for the live conversation; and storing information obtained from the text portion of the live conversation into the information field, wherein the information obtained from the text portion comprises at least one word spoken after the one or more cues. 22. The computer readable storage medium of claim 19 , wherein at least one of the one or more cues is a pre-defined verbal cue spoken by the operator. | 0.81851 |
7,555,713 | 1 | 4 | 1. A system having a CPU and a demonstrating device, a plurality of document types, a plurality of structure templates for modeling a plurality of structures, a plurality of extracting procedures, a plurality of modifying procedures, and a plurality of presenting formats, for helping a reader to read a document efficiently by extracting a plurality of contents from said document, generating a plurality of revised contents by modifying said plurality of contents, and presenting said plurality of revised contents on said demonstrating device with a particular presenting format selected from said plurality of presenting formats, wherein each structure template has a plurality of sub-structure templates and corresponds to a particular document type, wherein each document type corresponds to a particular class of documents categorized according to a plurality of requirements of a plurality of readers, wherein each sub-structure template marks a corresponding content, said system comprising: means for identifying a document type of said document from said plurality of document types by using at least one method selected from a group comprising source identification, author identification, title identification, topic identification, vocabulary identification, 4WH identification and author specification; means for determining a particular structure template from said plurality of structure templates according to said document type; means for building a structure with a plurality of sub-structures by instancing said particular structure template; means for extracting said plurality of contents from said document according to said plurality of extracting procedures, wherein said plurality of extracting procedures extract information according to a plurality of preferences of said reader; means for generating a plurality of revised contents by applying said plurality of modifying procedures on said plurality of contents, wherein said plurality of modifying procedures amend information according to said plurality of preferences of said reader; means for filling said plurality of sub-structures by said plurality of revised contents; means for organizing said structure into a structured document; and means for presenting said structure document through said demonstrating device according to said particular presenting format, whereby said structured document is significantly different from said document with information modified according to said plurality of preferences of said reader; and whereby said system extracts said plurality of contents from said document by running said plurality of extracting procedures on said CPU, organizes said plurality of contents in said structure, modifying said plurality of contents by said plurality of modifying procedures, and presents said plurality of revised contents on said demonstrating device according to said particular presenting format. | 1. A system having a CPU and a demonstrating device, a plurality of document types, a plurality of structure templates for modeling a plurality of structures, a plurality of extracting procedures, a plurality of modifying procedures, and a plurality of presenting formats, for helping a reader to read a document efficiently by extracting a plurality of contents from said document, generating a plurality of revised contents by modifying said plurality of contents, and presenting said plurality of revised contents on said demonstrating device with a particular presenting format selected from said plurality of presenting formats, wherein each structure template has a plurality of sub-structure templates and corresponds to a particular document type, wherein each document type corresponds to a particular class of documents categorized according to a plurality of requirements of a plurality of readers, wherein each sub-structure template marks a corresponding content, said system comprising: means for identifying a document type of said document from said plurality of document types by using at least one method selected from a group comprising source identification, author identification, title identification, topic identification, vocabulary identification, 4WH identification and author specification; means for determining a particular structure template from said plurality of structure templates according to said document type; means for building a structure with a plurality of sub-structures by instancing said particular structure template; means for extracting said plurality of contents from said document according to said plurality of extracting procedures, wherein said plurality of extracting procedures extract information according to a plurality of preferences of said reader; means for generating a plurality of revised contents by applying said plurality of modifying procedures on said plurality of contents, wherein said plurality of modifying procedures amend information according to said plurality of preferences of said reader; means for filling said plurality of sub-structures by said plurality of revised contents; means for organizing said structure into a structured document; and means for presenting said structure document through said demonstrating device according to said particular presenting format, whereby said structured document is significantly different from said document with information modified according to said plurality of preferences of said reader; and whereby said system extracts said plurality of contents from said document by running said plurality of extracting procedures on said CPU, organizes said plurality of contents in said structure, modifying said plurality of contents by said plurality of modifying procedures, and presents said plurality of revised contents on said demonstrating device according to said particular presenting format. 4. The system in claim 1 , wherein said document is a paper-based document, said system further comprising means for converting said paper-based document into an electronic document, means for separating figures from text, means for convening texts in an image format into a computer readable format, means for examining said structured document from a plurality of aspects, means for presenting said structured document horizontally, and means for presenting said structured document vertically. | 0.83969 |
9,536,049 | 12 | 14 | 12. One or more non-transitory computer-readable media as recited in claim 1 , wherein the acts further comprise, in response to receiving the input: parsing the input to identify one or more concepts expressed therein; wherein the intent is determined based at least in part on the one or more concepts. | 12. One or more non-transitory computer-readable media as recited in claim 1 , wherein the acts further comprise, in response to receiving the input: parsing the input to identify one or more concepts expressed therein; wherein the intent is determined based at least in part on the one or more concepts. 14. One or more non-transitory computer-readable media as recited in claim 12 , wherein the determining of the intent comprises mapping the one or more concepts to one of multiple different intents associated with the one or more concepts based at least in part on at least one of the first context or the second context. | 0.884698 |
7,933,794 | 1 | 3 | 1. A method for processing information, comprising: in a system comprising one or more processors, providing an active dependency integration unit, comprising a first program module that receives as input first events for processing together with a definition of dependencies between business components in a business model in order to monitor a propagated impact between the business components; providing in the system a situation awareness unit, comprising a second program module that detects situations comprising specified combinations of second events and conditions; receiving in the active dependency integration unit a first event relating to at least a first business component; responsively to the first event and to the dependencies, propagating a change to at least a second business component; passing a second event indicative of the change to the situation awareness unit; responsively to the second event, detecting a situation in the situation awareness unit; responsively to the situation, conveying a third event from the situation awareness unit to the active dependency integration unit; and outputting a functional state of the business model responsively to at least the third event. | 1. A method for processing information, comprising: in a system comprising one or more processors, providing an active dependency integration unit, comprising a first program module that receives as input first events for processing together with a definition of dependencies between business components in a business model in order to monitor a propagated impact between the business components; providing in the system a situation awareness unit, comprising a second program module that detects situations comprising specified combinations of second events and conditions; receiving in the active dependency integration unit a first event relating to at least a first business component; responsively to the first event and to the dependencies, propagating a change to at least a second business component; passing a second event indicative of the change to the situation awareness unit; responsively to the second event, detecting a situation in the situation awareness unit; responsively to the situation, conveying a third event from the situation awareness unit to the active dependency integration unit; and outputting a functional state of the business model responsively to at least the third event. 3. The method according to claim 1 , further including receiving as input rules that describe how a given event affects a specified business component. | 0.882582 |
Subsets and Splits
No saved queries yet
Save your SQL queries to embed, download, and access them later. Queries will appear here once saved.