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5,539,862 | 6 | 9 | 6. A system for knowledge based design to facilitate the design of an object, comprising: storage means for storing a plurality of stereotype knowledge bases based on the design, each of said stereotype knowledge bases being modifiable according to at least one associated option; modifying means coupled to said storage means for selecting one of said stereotype knowledge bases based on the design in response to an instruction from a user; said modifying means further including means for modifying said one of said stereotype knowledge bases according to said at least one associated option in response to said instruction from the user; first generating means coupled to said modifying means for generating a plurality of design model elements by applying scripts in response to said modified one of said stereotype knowledge bases; said modifying means further operable to incorporate changes in said design model elements in response to said instruction from said user and to select another of said stereotype knowledge bases in response to an additional instruction from said user; and said first generating means further operable to regenerate said design model elements by applying additional scripts in response to said another of said stereotype knowledge bases so that said changes are retained by said regenerated design model elements. | 6. A system for knowledge based design to facilitate the design of an object, comprising: storage means for storing a plurality of stereotype knowledge bases based on the design, each of said stereotype knowledge bases being modifiable according to at least one associated option; modifying means coupled to said storage means for selecting one of said stereotype knowledge bases based on the design in response to an instruction from a user; said modifying means further including means for modifying said one of said stereotype knowledge bases according to said at least one associated option in response to said instruction from the user; first generating means coupled to said modifying means for generating a plurality of design model elements by applying scripts in response to said modified one of said stereotype knowledge bases; said modifying means further operable to incorporate changes in said design model elements in response to said instruction from said user and to select another of said stereotype knowledge bases in response to an additional instruction from said user; and said first generating means further operable to regenerate said design model elements by applying additional scripts in response to said another of said stereotype knowledge bases so that said changes are retained by said regenerated design model elements. 9. The system of claim 6 wherein each of said scripts forms a part of an associated stereotype rule. | 0.902344 |
7,921,106 | 1 | 4 | 1. A computer-implemented apparatus that enhances search result listings, comprising: a processor operatively coupled to a computer readable medium having stored thereon the following computer executable components: an attribute value ranking component comprising a search engine search result list sorted by search results rank, and further sorted by attribute value as a primary sort and rank as a secondary sort, wherein an attribute value rank is calculated for each of the attribute values; grouped search results comprising the search result list resorted by the calculated attribute value ranks, and further resorted by the attribute values, and still further resorted by the search results rank; a search result display component that provides search result groupings based on the group-by ranking for interaction with a user; and computer-readable storage medium comprising data structures and code for causing a computer to execute the attribute value ranking and search result display components, wherein the object oriented search result list references a plurality of information pages each comprising an object block representing an object classified as an object type having attributes for which the object block contains elements identified as attribute values, wherein the attribute pertains to a source of a respective information page. | 1. A computer-implemented apparatus that enhances search result listings, comprising: a processor operatively coupled to a computer readable medium having stored thereon the following computer executable components: an attribute value ranking component comprising a search engine search result list sorted by search results rank, and further sorted by attribute value as a primary sort and rank as a secondary sort, wherein an attribute value rank is calculated for each of the attribute values; grouped search results comprising the search result list resorted by the calculated attribute value ranks, and further resorted by the attribute values, and still further resorted by the search results rank; a search result display component that provides search result groupings based on the group-by ranking for interaction with a user; and computer-readable storage medium comprising data structures and code for causing a computer to execute the attribute value ranking and search result display components, wherein the object oriented search result list references a plurality of information pages each comprising an object block representing an object classified as an object type having attributes for which the object block contains elements identified as attribute values, wherein the attribute pertains to a source of a respective information page. 4. The computer-implemented apparatus of claim 1 , wherein the attribute value ranking component limits the group-by ranking to a top-k number of object oriented search results, where k is an integer. | 0.647887 |
7,962,328 | 16 | 20 | 16. An apparatus comprising: discriminant representation means for providing, to a user, representations of a plurality of discriminants of meanings of a plurality of symbols in a natural language, wherein each of the plurality of discriminants is associated with a corresponding finite set of mutually exclusive answers to the discriminant, and wherein the plurality of discriminants are orthogonal to each other; means for receiving, from the user, input representing a plurality of answers to the plurality of discriminants, wherein each of the plurality of answers from the user is selected from the finite set of mutually exclusive answers to the corresponding discriminant, wherein the means for receiving comprises: means for receiving first input from the user representing a first answer to a first one of the plurality of discriminants; and means for receiving second input, independent of the first input, from the user representing a second answer to a second one of the plurality of discriminants; and means for generating, in response to the input, a data structure tangibly stored in a computer-readable memory, the data structure comprising data representing the plurality of answers from the user, including the first answer and the second answer, and thereby representing a meaning of one of the plurality of symbols in the natural language; wherein the plurality of discriminants includes at least one Realm-related discriminant and one discriminant for distinguishing between composite and characteristic meanings in the natural language, wherein Realm-related discriminants include a discriminant for distinguishing between natural and artificial meanings in the natural language and a discriminant for distinguishing between concrete and information meanings in the natural language. | 16. An apparatus comprising: discriminant representation means for providing, to a user, representations of a plurality of discriminants of meanings of a plurality of symbols in a natural language, wherein each of the plurality of discriminants is associated with a corresponding finite set of mutually exclusive answers to the discriminant, and wherein the plurality of discriminants are orthogonal to each other; means for receiving, from the user, input representing a plurality of answers to the plurality of discriminants, wherein each of the plurality of answers from the user is selected from the finite set of mutually exclusive answers to the corresponding discriminant, wherein the means for receiving comprises: means for receiving first input from the user representing a first answer to a first one of the plurality of discriminants; and means for receiving second input, independent of the first input, from the user representing a second answer to a second one of the plurality of discriminants; and means for generating, in response to the input, a data structure tangibly stored in a computer-readable memory, the data structure comprising data representing the plurality of answers from the user, including the first answer and the second answer, and thereby representing a meaning of one of the plurality of symbols in the natural language; wherein the plurality of discriminants includes at least one Realm-related discriminant and one discriminant for distinguishing between composite and characteristic meanings in the natural language, wherein Realm-related discriminants include a discriminant for distinguishing between natural and artificial meanings in the natural language and a discriminant for distinguishing between concrete and information meanings in the natural language. 20. The apparatus of claim 16 , wherein the means for generating comprises means for generating the data structure to include a plurality of fields, wherein each of the plurality of fields represents a corresponding one of the plurality of answers. | 0.831978 |
6,101,461 | 6 | 9 | 6. A command inputting method used when inputting characters using software for Kana-to-Chinese character conversion according to claim 3 further comprising the steps of: generating second Chinese character information that specifies a series of processing steps for the first Chinese character information in said Chinese character dictionary; and changing a command for the second Chinese character information in said Chinese character dictionary to a macro command. | 6. A command inputting method used when inputting characters using software for Kana-to-Chinese character conversion according to claim 3 further comprising the steps of: generating second Chinese character information that specifies a series of processing steps for the first Chinese character information in said Chinese character dictionary; and changing a command for the second Chinese character information in said Chinese character dictionary to a macro command. 9. A command inputting method used when inputting characters using software for Kana-to-Chinese character conversion according to claim 6; wherein different colors or attributes are used in displaying a command, a macro command, and a Chinese character, respectively, when listed in a list in said listing step. | 0.918544 |
8,688,535 | 1 | 2 | 1. A method for managing user accesses of merchandise information, comprising: generating journal files over a predetermined period of time, wherein a journal file includes merchandise information associated with an accessed webpage; determining, for a merchandise category, information related to an attribute associated with the merchandise category based at least in part on the generated journal files, wherein the information related to an attribute includes at least a first type associated with the attribute; aggregating information associated with the attribute from journal files associated with the merchandise category, wherein aggregating information includes generating a quantity associated with the first type associated with the attribute based at least in part on a number of times the first type associated with the attribute appears in the journal files, wherein the aggregated information is to be included in a model information group associated with the merchandise category; and performing a subsequent search of merchandise information using information associated with the model information group, wherein performing the subsequent search includes determining whether a matching merchandise category can be found in response to a query keyword associated with the subsequent search; in the event that the matching merchandise category can be found, extracting attribute information from the model information group associated with the merchandise category; in the event that the matching merchandise category cannot be found, searching a merchandise category tree using the query keyword and returning information from one or more matching nodes of the merchandise category tree. | 1. A method for managing user accesses of merchandise information, comprising: generating journal files over a predetermined period of time, wherein a journal file includes merchandise information associated with an accessed webpage; determining, for a merchandise category, information related to an attribute associated with the merchandise category based at least in part on the generated journal files, wherein the information related to an attribute includes at least a first type associated with the attribute; aggregating information associated with the attribute from journal files associated with the merchandise category, wherein aggregating information includes generating a quantity associated with the first type associated with the attribute based at least in part on a number of times the first type associated with the attribute appears in the journal files, wherein the aggregated information is to be included in a model information group associated with the merchandise category; and performing a subsequent search of merchandise information using information associated with the model information group, wherein performing the subsequent search includes determining whether a matching merchandise category can be found in response to a query keyword associated with the subsequent search; in the event that the matching merchandise category can be found, extracting attribute information from the model information group associated with the merchandise category; in the event that the matching merchandise category cannot be found, searching a merchandise category tree using the query keyword and returning information from one or more matching nodes of the merchandise category tree. 2. The method of claim 1 , wherein information related to an attribute includes one or more of the following: merchandise brand information, merchandise model number information, merchandise color information, and merchandise category information. | 0.502016 |
8,141,065 | 7 | 12 | 7. An apparatus comprising a processor for dynamically instantiating a portion of a call flow graph having a plurality of states and a plurality of state transitions, the apparatus comprises: means for executing the graph, wherein the graph comprises a defined portion and an undefined portion, wherein a plurality of tokens traverse the graph executing functions; means for suspending one of the tokens in response to the one of the tokens detecting the undefined portion of the graph; means for generating a new portion of the graph for the undefined portion of the graph, said means for generating the new portion of the graph comprising: means for generating at least one definition file for the undefined portion of the graph; and means for executing the at least one definition file to form thereby the new portion of the graph; means for replacing the undefined portion of the graph with the new portion of the graph; and means for releasing the suspended token. | 7. An apparatus comprising a processor for dynamically instantiating a portion of a call flow graph having a plurality of states and a plurality of state transitions, the apparatus comprises: means for executing the graph, wherein the graph comprises a defined portion and an undefined portion, wherein a plurality of tokens traverse the graph executing functions; means for suspending one of the tokens in response to the one of the tokens detecting the undefined portion of the graph; means for generating a new portion of the graph for the undefined portion of the graph, said means for generating the new portion of the graph comprising: means for generating at least one definition file for the undefined portion of the graph; and means for executing the at least one definition file to form thereby the new portion of the graph; means for replacing the undefined portion of the graph with the new portion of the graph; and means for releasing the suspended token. 12. The apparatus of claim 7 , wherein at least one other token traverses the defined portion of the graph at least while the new portion of the graph is defined. | 0.787958 |
9,691,028 | 8 | 10 | 8. A data processing apparatus coupled to a network, comprising: a processor; a display unit coupled to the processor; and a memory configured to store one or more applications that include instructions which, when executed by the processor, cause the processor to perform operations for processing numerical data, including the steps of: editing, based on input editing information, a search rule that sets a search condition for searching for the numerical data and includes a specific data value at a specific point in time, a fixed time interval during which the specific data value is maintained and an error bound to be added to and subtracted from the fixed time interval to define upper and lower limits of the fixed time interval; searching for the numerical data in accordance with the edited search rule to generate a search result; visualizing the search result based on the numerical data on the display unit; and transmitting individual interpretations of a first user and a second user on the search result to terminals of a first user and a second user through the network so that the first user and the second user share the individual interpretations with each other. | 8. A data processing apparatus coupled to a network, comprising: a processor; a display unit coupled to the processor; and a memory configured to store one or more applications that include instructions which, when executed by the processor, cause the processor to perform operations for processing numerical data, including the steps of: editing, based on input editing information, a search rule that sets a search condition for searching for the numerical data and includes a specific data value at a specific point in time, a fixed time interval during which the specific data value is maintained and an error bound to be added to and subtracted from the fixed time interval to define upper and lower limits of the fixed time interval; searching for the numerical data in accordance with the edited search rule to generate a search result; visualizing the search result based on the numerical data on the display unit; and transmitting individual interpretations of a first user and a second user on the search result to terminals of a first user and a second user through the network so that the first user and the second user share the individual interpretations with each other. 10. The data processing apparatus of claim 8 , further comprising: coding the search rule; and compiling the coded search rule. | 0.877649 |
10,121,466 | 9 | 10 | 9. A method for re-training a speaker-independent speech recognition system with respect to a word of an application vocabulary, wherein a generic voice template is assigned to said word in the application vocabulary, the method comprising: acquiring from a user a speech sample of said word using the speaker-independent speech recognition system; comparing, via at least one processor, the speech sample to generic voice templates in the application vocabulary; and if the speech sample matches more than one of the generic voice templates in the application vocabulary, then: prompting, via the at least one processor, the user to create a custom voice template for a substitute word, training, via the at least one processor, the speaker-independent speech recognition system on the substitute word to create the custom voice template for the substitute word, and replacing, via the at least one processor, in the application vocabulary the generic voice template for said word with the custom voice template for the substitute word; and otherwise, if the speech sample matches the generic voice template for said word, using, via the at least one processor, the generic voice template for the word; wherein, during the re-training, the comparison of the speech sample of said word to generic voice templates in the application vocabulary is performed until the custom voice template for the substitute word which is different from the generic voice templates and having no template similarity with the generic voice templates is created; wherein the re-training is initiated after an initial enrollment training performed for the speech recognition system before use based on an outcome of a performance evaluation performed periodically by the speech recognition system; and wherein the performance evaluation is associated with recognition performance for the word. | 9. A method for re-training a speaker-independent speech recognition system with respect to a word of an application vocabulary, wherein a generic voice template is assigned to said word in the application vocabulary, the method comprising: acquiring from a user a speech sample of said word using the speaker-independent speech recognition system; comparing, via at least one processor, the speech sample to generic voice templates in the application vocabulary; and if the speech sample matches more than one of the generic voice templates in the application vocabulary, then: prompting, via the at least one processor, the user to create a custom voice template for a substitute word, training, via the at least one processor, the speaker-independent speech recognition system on the substitute word to create the custom voice template for the substitute word, and replacing, via the at least one processor, in the application vocabulary the generic voice template for said word with the custom voice template for the substitute word; and otherwise, if the speech sample matches the generic voice template for said word, using, via the at least one processor, the generic voice template for the word; wherein, during the re-training, the comparison of the speech sample of said word to generic voice templates in the application vocabulary is performed until the custom voice template for the substitute word which is different from the generic voice templates and having no template similarity with the generic voice templates is created; wherein the re-training is initiated after an initial enrollment training performed for the speech recognition system before use based on an outcome of a performance evaluation performed periodically by the speech recognition system; and wherein the performance evaluation is associated with recognition performance for the word. 10. The method according to claim 9 , wherein prompting the user to create a custom voice template for a substitute word comprises a list of possible substitute words. | 0.929237 |
9,235,410 | 7 | 12 | 7. A non-transitory computer readable storage medium comprising instructions that, when executed by a processing device, cause the processing device to: receive a first software release comprising a set of software packages; parse the first software release to identify modeling information comprising package information, package dependency information, and function dependency information associated with each software package in the set of software packages, wherein the function dependency information identifies a relationship between a plurality of functions performed by the set of software packages in the first software release; generate, by the processing device, a first graph model representing the first modeling information, wherein the first graph model comprises a package node for each software package in the set of software packages and a function node for each function in the set of software packages of the first software release; generate, by the processing device, a second graph model representing second modeling information associated with a second software release comprising a second set of software packages, wherein the second graph model comprises a package node for each software package in the second set of software packages and a function node for each function in the second set of software packages; store the first graph model associated with the first software release and the second graph model associated with the second software release; and compare the first graph model and the second graph model to identify a change producing an incompatibility in an integration of the second software release in view of a policy. | 7. A non-transitory computer readable storage medium comprising instructions that, when executed by a processing device, cause the processing device to: receive a first software release comprising a set of software packages; parse the first software release to identify modeling information comprising package information, package dependency information, and function dependency information associated with each software package in the set of software packages, wherein the function dependency information identifies a relationship between a plurality of functions performed by the set of software packages in the first software release; generate, by the processing device, a first graph model representing the first modeling information, wherein the first graph model comprises a package node for each software package in the set of software packages and a function node for each function in the set of software packages of the first software release; generate, by the processing device, a second graph model representing second modeling information associated with a second software release comprising a second set of software packages, wherein the second graph model comprises a package node for each software package in the second set of software packages and a function node for each function in the second set of software packages; store the first graph model associated with the first software release and the second graph model associated with the second software release; and compare the first graph model and the second graph model to identify a change producing an incompatibility in an integration of the second software release in view of a policy. 12. The non-transitory computer readable storage medium of claim 7 , the processing device to search at least one of the first graph model or the second graph model using a breadth-first search. | 0.775463 |
7,913,235 | 13 | 16 | 13. A non-transitory computer readable storage medium embodying computer readable instructions, comprising: instructions executable by a computer to receive a request to assemble a specific locale source file; instructions executable by the computer to retrieve an input file including a plurality of localization values related to the specific locale source file; instructions executable by the computer to determine a first category of localization values and to select process routines based on the first category of localization values, wherein each process routine comprises a scripting function to automatically extract localization values pertaining to associated with the first category of localization values; instructions executable by the computer to selectively extract localization values associated with the first category by scripting functions of the selected process routines; instructions executable by the computer to store the extracted localization values into a memory of the computer; and instructions executable by the computer to determine a positive monetary format and a negative monetary format for inclusion in the specific locale source file when the first category is a monetary category; instructions executable by the computer to replacing a currency symbol with a corresponding alphabetic name when the currency symbol of the specific locale source file is in a graphical form; and instructions executable by the computer to assemble the extracted localization values into the specific locale source file suitable for compilation. | 13. A non-transitory computer readable storage medium embodying computer readable instructions, comprising: instructions executable by a computer to receive a request to assemble a specific locale source file; instructions executable by the computer to retrieve an input file including a plurality of localization values related to the specific locale source file; instructions executable by the computer to determine a first category of localization values and to select process routines based on the first category of localization values, wherein each process routine comprises a scripting function to automatically extract localization values pertaining to associated with the first category of localization values; instructions executable by the computer to selectively extract localization values associated with the first category by scripting functions of the selected process routines; instructions executable by the computer to store the extracted localization values into a memory of the computer; and instructions executable by the computer to determine a positive monetary format and a negative monetary format for inclusion in the specific locale source file when the first category is a monetary category; instructions executable by the computer to replacing a currency symbol with a corresponding alphabetic name when the currency symbol of the specific locale source file is in a graphical form; and instructions executable by the computer to assemble the extracted localization values into the specific locale source file suitable for compilation. 16. The non-transitory computer readable storage medium of claim 13 , further comprising instructions executable by the computer to automatically filter the plurality of localization values to provide a set of localization values associated with a specific locale of the specific locale source file. | 0.506601 |
9,424,010 | 7 | 8 | 7. The method of claim 1 , wherein the plurality of property labels includes localness labels for object oriented language methods. | 7. The method of claim 1 , wherein the plurality of property labels includes localness labels for object oriented language methods. 8. The method of claim 7 , wherein the localness labels include one or more of local, global, or glocal labels, or combinations thereof. | 0.966829 |
8,046,693 | 31 | 33 | 31. A web page stored on a storage medium, the web page comprising: page content data, a first activatable transport-control element with associated first semantic information, a second activatable transport-control element with associated second semantic information that is different from said first semantic information, the transport-control elements and their associated semantic information being intended for display by a browser along with said page content data; and control script code for causing a browser, when displaying the web page, to respond to activation of a said transport-control element both by moving the displayed page view within or between web pages and by storing or outputting data indicative of the semantic information associated with the activated element, the page-view move that is effected as a result of activation of a said transport-control element being the same whichever of said elements is activated. | 31. A web page stored on a storage medium, the web page comprising: page content data, a first activatable transport-control element with associated first semantic information, a second activatable transport-control element with associated second semantic information that is different from said first semantic information, the transport-control elements and their associated semantic information being intended for display by a browser along with said page content data; and control script code for causing a browser, when displaying the web page, to respond to activation of a said transport-control element both by moving the displayed page view within or between web pages and by storing or outputting data indicative of the semantic information associated with the activated element, the page-view move that is effected as a result of activation of a said transport-control element being the same whichever of said elements is activated. 33. A web page according to claim 31 , wherein said semantic information comprises a graphics information. | 0.889353 |
9,381,426 | 12 | 13 | 12. A system for avatar display and interaction as in claim 1 , further comprising: said avatar being real or partially real and partially synthetic. | 12. A system for avatar display and interaction as in claim 1 , further comprising: said avatar being real or partially real and partially synthetic. 13. A system for avatar display and interaction as in claim 12 , further comprising: said avatar being a real avatar, said real avatar having an optimized pan axis and an optimized tilt axis. | 0.972263 |
5,574,802 | 8 | 18 | 8. A method of logically identifying document elements in a document image, comprising the steps of: storing a set of at least one predetermined structural model, each structural model defining at least one level of a nested one-dimensional hierarchy of relationships defining separations between document elements of a corresponding model document; identifying major background regions in the document image; defining relationships between the identified major background regions of the document image; converting the defined relationships of the document image into at least one level of a nested one-dimensional hierarchy of relationships by selecting coextensive major background regions extending perpendicular to a direction of each of the at least one level of the nested one-dimensional hierarchy of relationships; selecting a top level of relationships of the at least one level of relationships of the document image as a current document image level; selecting a top level of relationships of the at least one level of relationships for the at least one stored structural model to form a set of current structural model levels; comparing the current document image level to each current structural model level of the set of current structural model levels; selecting each structural model whose current level matches the current document image level to form a set of matching structural models; determining if any additional document image levels exist; if so, selecting a next document image level as the current document image level and selecting a corresponding next level for each of the set of matching structural models as the current structural model level to reform the set of current structural models; repeating the comparing step through the next document image level selecting step until no additional document image levels exist; determining if a single selected structural model exists or a plurality of selected structural models exist; if a plurality of selected structural models exists, selecting a most similar one of the selected structural models that is most similar to the defined relationships of the document image as the single selected structural model; and identifying the document elements of the document image based on logical tags of the single selected structural model. | 8. A method of logically identifying document elements in a document image, comprising the steps of: storing a set of at least one predetermined structural model, each structural model defining at least one level of a nested one-dimensional hierarchy of relationships defining separations between document elements of a corresponding model document; identifying major background regions in the document image; defining relationships between the identified major background regions of the document image; converting the defined relationships of the document image into at least one level of a nested one-dimensional hierarchy of relationships by selecting coextensive major background regions extending perpendicular to a direction of each of the at least one level of the nested one-dimensional hierarchy of relationships; selecting a top level of relationships of the at least one level of relationships of the document image as a current document image level; selecting a top level of relationships of the at least one level of relationships for the at least one stored structural model to form a set of current structural model levels; comparing the current document image level to each current structural model level of the set of current structural model levels; selecting each structural model whose current level matches the current document image level to form a set of matching structural models; determining if any additional document image levels exist; if so, selecting a next document image level as the current document image level and selecting a corresponding next level for each of the set of matching structural models as the current structural model level to reform the set of current structural models; repeating the comparing step through the next document image level selecting step until no additional document image levels exist; determining if a single selected structural model exists or a plurality of selected structural models exist; if a plurality of selected structural models exists, selecting a most similar one of the selected structural models that is most similar to the defined relationships of the document image as the single selected structural model; and identifying the document elements of the document image based on logical tags of the single selected structural model. 18. The method of claim 8, wherein the storing step comprises the steps of: generating a top-level expression pattern of background regions for each of the at least one structural model based on corresponding structural model document image document elements; identifying pseudo-elements in the top-level expression pattern for each at least one structural model; generating a second or greater level expression pattern of background regions for each of the pseudo-elements in said each of the at least one structural model; identifying minor document element characteristics for each of the document elements of each of the at least one structural model; and generating minor relationships of background regions for each of the document elements of each of the at least one structural model. | 0.500631 |
8,260,785 | 1 | 3 | 1. A computer implemented method comprising: at a computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: storing a plurality of objects in a fact repository, wherein the objects are associated with facts, each fact having one or more terms; modifying one or more of the facts in the fact repository, including automatically, without user intervention: establishing a list of object names of objects in the fact repository, wherein the list of object names is stored as a hash table; for a respective fact having multiple terms, comparing a respective phrase-identification metric for each of a plurality of different combinations of terms in the respective fact to identify one or more candidate phrases; checking at least a subset of the candidate phrases against the list of object names, wherein checking the candidate phrases against the list of object names includes determining, for each respective candidate phrase whether a hash of the respective candidate phrase collides with a value in the hash table; and for each fact in of a plurality of respective candidate phrases that match respective object names in the list of object names, constructing a respective search link for a respective fact corresponding to the respective candidate phrase, and storing the respective search link at a location associated with the respective fact in the fact repository, wherein selection of a representation of the respective search link invokes performance of a search query against the fact repository, the search query including one or more search criteria that include the respective object name corresponding to the respective candidate phrase; and after modifying the facts in the fact repository, in accordance with a determination that one or more predefined criteria have been met, automatically repeating, without user intervention, the steps of establishing a list of object names from a plurality of name facts, identifying candidate phrases, checking candidate phrases against the list of object names and constructing and storing search links in the fact repository. | 1. A computer implemented method comprising: at a computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: storing a plurality of objects in a fact repository, wherein the objects are associated with facts, each fact having one or more terms; modifying one or more of the facts in the fact repository, including automatically, without user intervention: establishing a list of object names of objects in the fact repository, wherein the list of object names is stored as a hash table; for a respective fact having multiple terms, comparing a respective phrase-identification metric for each of a plurality of different combinations of terms in the respective fact to identify one or more candidate phrases; checking at least a subset of the candidate phrases against the list of object names, wherein checking the candidate phrases against the list of object names includes determining, for each respective candidate phrase whether a hash of the respective candidate phrase collides with a value in the hash table; and for each fact in of a plurality of respective candidate phrases that match respective object names in the list of object names, constructing a respective search link for a respective fact corresponding to the respective candidate phrase, and storing the respective search link at a location associated with the respective fact in the fact repository, wherein selection of a representation of the respective search link invokes performance of a search query against the fact repository, the search query including one or more search criteria that include the respective object name corresponding to the respective candidate phrase; and after modifying the facts in the fact repository, in accordance with a determination that one or more predefined criteria have been met, automatically repeating, without user intervention, the steps of establishing a list of object names from a plurality of name facts, identifying candidate phrases, checking candidate phrases against the list of object names and constructing and storing search links in the fact repository. 3. The method of claim 1 , wherein identifying candidate phrases in a particular fact comprises: forming a plurality of sequences of consecutive terms in the particular fact; and testing each sequence of terms to determine whether the sequence is a phrase. | 0.812317 |
5,551,055 | 1 | 2 | 1. A graphical user interface command system for use in a computer system having a display and a processor, the system displaying a control graphic on the display, said control graphic presenting information on the display, and executing a command in response to manipulation of the control graphic by a user, the system is configured to display said control graphic in a different particular manner according to associated locales respectively, and comprising: a memory for storing a command data structure, a plurality of control graphics, and a plurality of locale information for each of said control graphics; a pre-runtime mechanism operating on the processor for saving parameters in the command data structure indicative of a plurality of command executions; tracking apparatus for modifying the command data structure as the user manipulates a displayed control graphic to select and execute one of the plurality of command executions and provide for proper control execution; a locale selector for selecting one of said plurality of locale information; and display control apparatus, coupled to said memory, said pre-runtime mechanism, said tracking apparatus, and said locale selector, for generating one of said control graphics in a specific manner based on said selected locale information and wherein for different locales said control graphic has different information contents or same information contents displayed in a predetermined order. | 1. A graphical user interface command system for use in a computer system having a display and a processor, the system displaying a control graphic on the display, said control graphic presenting information on the display, and executing a command in response to manipulation of the control graphic by a user, the system is configured to display said control graphic in a different particular manner according to associated locales respectively, and comprising: a memory for storing a command data structure, a plurality of control graphics, and a plurality of locale information for each of said control graphics; a pre-runtime mechanism operating on the processor for saving parameters in the command data structure indicative of a plurality of command executions; tracking apparatus for modifying the command data structure as the user manipulates a displayed control graphic to select and execute one of the plurality of command executions and provide for proper control execution; a locale selector for selecting one of said plurality of locale information; and display control apparatus, coupled to said memory, said pre-runtime mechanism, said tracking apparatus, and said locale selector, for generating one of said control graphics in a specific manner based on said selected locale information and wherein for different locales said control graphic has different information contents or same information contents displayed in a predetermined order. 2. A command system as recited in claim 1, including processor means for storing a particular user interface element in a presentation. | 0.558824 |
8,131,550 | 14 | 18 | 14. An apparatus comprising a processor and memory including computer program code, the memory and the computer program code configured to, with the processor, cause the apparatus to at least: extract a feature indicative of a property of a vocal tract of a speaker from each of training source speech and training target speech; define sub-feature units with respect to the feature for both the training source speech and the training target speech to generate training source speech sub-feature units and training target speech sub-feature units, respectively; and perform voice conversion of source speech to target speech based on the conversion of the sub-feature units to corresponding target speech sub-feature units using a conversion model trained with respect to converting the training source speech sub-feature units to the training target speech sub-feature units. | 14. An apparatus comprising a processor and memory including computer program code, the memory and the computer program code configured to, with the processor, cause the apparatus to at least: extract a feature indicative of a property of a vocal tract of a speaker from each of training source speech and training target speech; define sub-feature units with respect to the feature for both the training source speech and the training target speech to generate training source speech sub-feature units and training target speech sub-feature units, respectively; and perform voice conversion of source speech to target speech based on the conversion of the sub-feature units to corresponding target speech sub-feature units using a conversion model trained with respect to converting the training source speech sub-feature units to the training target speech sub-feature units. 18. An apparatus according to claim 14 , wherein the source speech is selected from a plurality of synthetic voices based on the target speech. | 0.845905 |
8,359,311 | 1 | 3 | 1. A method, performed using at least one computing device, for identifying a set of resources associated with respective domains, comprising: providing context information that pertains to interaction, by a user, with a user device, the context information including textual information associated with content presented to the user by the user device; providing, for each of a plurality of individual domains, individual-domain score information that indicates relevance of the context information to a corresponding individual domain, plural instances of the individual-domain score information comprising plural-domain score information, the providing including (i) receiving data from an entity associated with corresponding individual domain, the data characterizing at least goods or services of the entity, and (ii) generating a language model that identities characteristics of the entity, based on the received data; and identifying a set of resources based on the plural-domain score information for presentation to the user, the set of resources assisting the user in performing an action within a task having plural parts. | 1. A method, performed using at least one computing device, for identifying a set of resources associated with respective domains, comprising: providing context information that pertains to interaction, by a user, with a user device, the context information including textual information associated with content presented to the user by the user device; providing, for each of a plurality of individual domains, individual-domain score information that indicates relevance of the context information to a corresponding individual domain, plural instances of the individual-domain score information comprising plural-domain score information, the providing including (i) receiving data from an entity associated with corresponding individual domain, the data characterizing at least goods or services of the entity, and (ii) generating a language model that identities characteristics of the entity, based on the received data; and identifying a set of resources based on the plural-domain score information for presentation to the user, the set of resources assisting the user in performing an action within a task having plural parts. 3. The method of claim 1 , wherein said context information also includes supplemental information that is obtained from a source other than the content that is presented to the user. | 0.831492 |
9,729,468 | 7 | 8 | 7. The method of claim 6 , further comprising selecting the concrete types of resources based on a comparison between the abstraction of the type of the resource and types of actual instances of resources in the infrastructure environment. | 7. The method of claim 6 , further comprising selecting the concrete types of resources based on a comparison between the abstraction of the type of the resource and types of actual instances of resources in the infrastructure environment. 8. The method of claim 7 , further comprising selecting the types of actual instances of resources in the infrastructure environment based on an availability of the actual instances of the resources. | 0.944691 |
8,117,223 | 16 | 18 | 16. A system comprising: a tangible computer readable medium storing instructions that when executed by one or more processors cause the system to: determine top phrases for a plurality of documents in a limited document collection, wherein determining the top phrases of a document includes: identifying phrases in the document; for each identified phrase in the document, determining an importance score for the identified phrase based on occurrences of related phrases of the identified phrase, which are also in the document; associate each top phrase with the importance score for the document; for each top phrase, determine an aggregate score of the top phrase for the limited document collection based on the top phrase's scores for individual documents of the limited document collection in which the top phrase appears; and select a set of top phrases with the highest aggregate scores; and one or more processors configured for executing the instructions stored on the computer readable storage medium. | 16. A system comprising: a tangible computer readable medium storing instructions that when executed by one or more processors cause the system to: determine top phrases for a plurality of documents in a limited document collection, wherein determining the top phrases of a document includes: identifying phrases in the document; for each identified phrase in the document, determining an importance score for the identified phrase based on occurrences of related phrases of the identified phrase, which are also in the document; associate each top phrase with the importance score for the document; for each top phrase, determine an aggregate score of the top phrase for the limited document collection based on the top phrase's scores for individual documents of the limited document collection in which the top phrase appears; and select a set of top phrases with the highest aggregate scores; and one or more processors configured for executing the instructions stored on the computer readable storage medium. 18. The system of claim 16 , wherein determining the importance score of an identified phrase in the document is based on a frequency of the related phrases in the document. | 0.805618 |
7,596,554 | 6 | 9 | 6. A machine readable storage medium storing a computer program which when executed constructs a system-independent key from a universal resource indicator for use in an index-less caching system, the computer program performing a method comprising: converting characters of the universal resource indicator to equivalent values resulting in a value string having a value string length, the value string including a file name associated with a cached resource; determining if the value string length exceeds a predetermined maximum file entry length for the caching system; and converting the value string into discrete file entries including one or more directory entries and the file name associated with the cached resource, wherein each discrete file entry contains a number of values equal to or less than the maximum file entry length. | 6. A machine readable storage medium storing a computer program which when executed constructs a system-independent key from a universal resource indicator for use in an index-less caching system, the computer program performing a method comprising: converting characters of the universal resource indicator to equivalent values resulting in a value string having a value string length, the value string including a file name associated with a cached resource; determining if the value string length exceeds a predetermined maximum file entry length for the caching system; and converting the value string into discrete file entries including one or more directory entries and the file name associated with the cached resource, wherein each discrete file entry contains a number of values equal to or less than the maximum file entry length. 9. The machine readable storage medium of claim 6 , wherein the equivalent values are alphanumeric values. | 0.790514 |
4,443,199 | 16 | 17 | 16. The teaching aid of claim 14, wherein the second set of displaceable tiles has some tiles which are individually coloured to indicate a phonetic vowel of any language and additional, individually coloured alphabet tiles are provided for non-standard alphabet sounds. | 16. The teaching aid of claim 14, wherein the second set of displaceable tiles has some tiles which are individually coloured to indicate a phonetic vowel of any language and additional, individually coloured alphabet tiles are provided for non-standard alphabet sounds. 17. The teaching aid of claim 16, wherein the additional coloured alphabet tiles are provided for sound variations of the same consonant letter. | 0.9566 |
7,752,235 | 1 | 5 | 1. An application program interface embodied on one or more computer-readable storage media, the application program interface comprising: calling a first method to create a package that defines a document, wherein the package holds together a plurality of parts which represent different aspects of the document; calling a second method to create a relationship between the package and a particular part in the package; calling a third method to identify one or more relationships between the plurality of parts in the package, wherein each relationship identifies at least one connection between an associated part and at least one other of the plurality of parts, each relationship being stored in a relationships part independent of the plurality of parts, wherein the connections are discovered by analyzing relationships associated with the plurality of parts without looking at the content of the parts; and wherein the plurality of parts facilitates at least displaying the document independent of a platform on the computer. | 1. An application program interface embodied on one or more computer-readable storage media, the application program interface comprising: calling a first method to create a package that defines a document, wherein the package holds together a plurality of parts which represent different aspects of the document; calling a second method to create a relationship between the package and a particular part in the package; calling a third method to identify one or more relationships between the plurality of parts in the package, wherein each relationship identifies at least one connection between an associated part and at least one other of the plurality of parts, each relationship being stored in a relationships part independent of the plurality of parts, wherein the connections are discovered by analyzing relationships associated with the plurality of parts without looking at the content of the parts; and wherein the plurality of parts facilitates at least displaying the document independent of a platform on the computer. 5. An application program interface as recited in claim 1 , further comprising a property that identifies a target uniform resource identifier associated with a particular relationship. | 0.502688 |
7,788,085 | 2 | 7 | 2. The method according to claim 1 , further comprising: identifying a first set of possible senses for the source string and a second set of possible senses for the target string via the computer; assessing whether replacing the source string having the first set of possible senses with the target string having the second set of possible senses is semantically coherent via the computer; and outputting a warning, via the computer, when the replacement of the source string with the target string is not semantically coherent. | 2. The method according to claim 1 , further comprising: identifying a first set of possible senses for the source string and a second set of possible senses for the target string via the computer; assessing whether replacing the source string having the first set of possible senses with the target string having the second set of possible senses is semantically coherent via the computer; and outputting a warning, via the computer, when the replacement of the source string with the target string is not semantically coherent. 7. The method according to claim 2 , further comprising: processing the textual content of the document to identify a set of expressions that may be single-word expressions or multiword expressions via the computer; identifying a sense for each expression in the set of expressions via the computer; assessing, via the computer, whether the string sense and the sense of an identified expression are semantically coherent before replacing each occurrence of the source string in the textual content of the document with the target string when the source string forms part of the identified expression; and outputting a warning, via the computer, when the replacement of the source string with the target string is not semantically coherent. | 0.840792 |
9,071,562 | 1 | 2 | 1. A computer program product for locating information on a topic within a peer-to-peer network, the computer program product comprising: one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media, the program instructions comprising: program instructions to receive, on a first peer computer within the peer-to-peer network, a request to locate a topic; program instructions to determine a second peer computer within the peer-to-peer network to query for the topic; program instructions to query an index of the second peer computer for the topic; responsive to determining the topic exists in the index of the second peer computer, program instructions to receive identification information of participants of an instant messaging conversation corresponding to the topic; program instructions to determine the received identification information originated from a currently unavailable peer computer, wherein the currently unavailable peer computer previously pushed an index with the identification information to the second peer computer; and program instructions to store, on the first peer computer, the identification information of the participants and indexing the stored identification information by the topic. | 1. A computer program product for locating information on a topic within a peer-to-peer network, the computer program product comprising: one or more non-transitory computer-readable storage media and program instructions stored on the one or more non-transitory computer-readable storage media, the program instructions comprising: program instructions to receive, on a first peer computer within the peer-to-peer network, a request to locate a topic; program instructions to determine a second peer computer within the peer-to-peer network to query for the topic; program instructions to query an index of the second peer computer for the topic; responsive to determining the topic exists in the index of the second peer computer, program instructions to receive identification information of participants of an instant messaging conversation corresponding to the topic; program instructions to determine the received identification information originated from a currently unavailable peer computer, wherein the currently unavailable peer computer previously pushed an index with the identification information to the second peer computer; and program instructions to store, on the first peer computer, the identification information of the participants and indexing the stored identification information by the topic. 2. The computer program product of claim 1 , further comprising, stored on the one or more non-transitory computer-readable storage media: program instructions to receive, at the first peer computer, a query from a third peer computer within the peer-to-peer network for a separate topic; program instructions to identify an instant messaging conversation stored on the first peer computer that corresponds to the separate topic; and program instructions to send identification information of participants of the instant messaging conversation that corresponds to the separate topic to the third peer computer. | 0.556041 |
8,166,017 | 57 | 58 | 57. The computer program product of claim 56 , wherein affecting the presentation comprises: sorting the list of pages based on the accessed ranking. | 57. The computer program product of claim 56 , wherein affecting the presentation comprises: sorting the list of pages based on the accessed ranking. 58. The computer program product of claim 57 , wherein sorting the list of pages further comprises: increasing a ranking of the page in the list if the rating exceeds a threshold; and decreasing a ranking of the page in the list if the rating does not exceed the threshold. | 0.879842 |
7,555,725 | 1 | 2 | 1. A system for providing an interactive electronic map, comprising: at least one computer programmed to cause a display device to display simultaneously thereon: a map with a portion thereof displayed highlighted; a magnified representation of the portion that is displayed highlighted; information in the magnified representation relating to one or more items associated with a geographic area represented by the map; and outside of the map being displayed and outside of the magnified representation being displayed, additional information relating to one or more of the items; the at least one computer being further programmed to cause the display device to display: in response to input to the at least one computer from a pointing device, another highlighted portion that is different from the highlighted portion, another magnified representation corresponding to the other highlighted portion and information in the other magnified representation relating to one or more items associated with a geographic area represented by the map, wherein the information displayed in the other magnified representation can be different from the information displayed in the magnified representation; and in response to input to the at least one computer from a pointing device that selects displayed additional information, indicating the information relating to the selected additional information in a magnified representation. | 1. A system for providing an interactive electronic map, comprising: at least one computer programmed to cause a display device to display simultaneously thereon: a map with a portion thereof displayed highlighted; a magnified representation of the portion that is displayed highlighted; information in the magnified representation relating to one or more items associated with a geographic area represented by the map; and outside of the map being displayed and outside of the magnified representation being displayed, additional information relating to one or more of the items; the at least one computer being further programmed to cause the display device to display: in response to input to the at least one computer from a pointing device, another highlighted portion that is different from the highlighted portion, another magnified representation corresponding to the other highlighted portion and information in the other magnified representation relating to one or more items associated with a geographic area represented by the map, wherein the information displayed in the other magnified representation can be different from the information displayed in the magnified representation; and in response to input to the at least one computer from a pointing device that selects displayed additional information, indicating the information relating to the selected additional information in a magnified representation. 2. The system of claim 1 , wherein the at least one computer is further programmed to cause the display device to display and move an image with respect to the map that is displayed including through the highlighted portion and through the magnified representation of the highlighted portion, the image being represented magnified in the magnified portion as compared to the image moved with respect to the map being displayed. | 0.501168 |
8,996,559 | 1 | 9 | 1. A method of a query editor comprising: generating a data profile comprising a set of characteristics captured at various granularities of an initial result set generated from an initial query of a database using a processor and a memory; determining what a user expects in at least one of the initial result set of the initial query and a subsequent result set of a subsequent query based on one of the data profile and a heuristically estimated data profile; enabling the user to evaluate a semantic accuracy of the subsequent query based on a likely expectation of the user as determined through the set of characteristics of the data profile; generating a social data catalog table of information about how users are interacting with at least one of the database and a sample database; populating the social data catalog table with metadata, a logical definition and description of attributes, information about usage, page views between the users, a social data network, and a statistical data profile; extracting information from external data sources and social media profiles to generate the social data catalog table of information; and crowd sourcing information from a ranked list of knowledgeable users to generate a ranked order of priority of information presented in profile pages of a curated answers system, wherein the information about usage includes related tables and join predicates as well as relevant filters associated with each table of the at least one of the database and the sample database, wherein the social data network includes a list of users who are knowledgeable about a particular object related to the another query, and wherein the metadata is at least one of a schema name, a table in a schema, a name of an attribute, a data type of the attribute, a primary key associated with the attribute, a constraint of the attribute, a functional dependency between the attributes, an index, a foreign key, a field name, a column name, a table name, and a query description. | 1. A method of a query editor comprising: generating a data profile comprising a set of characteristics captured at various granularities of an initial result set generated from an initial query of a database using a processor and a memory; determining what a user expects in at least one of the initial result set of the initial query and a subsequent result set of a subsequent query based on one of the data profile and a heuristically estimated data profile; enabling the user to evaluate a semantic accuracy of the subsequent query based on a likely expectation of the user as determined through the set of characteristics of the data profile; generating a social data catalog table of information about how users are interacting with at least one of the database and a sample database; populating the social data catalog table with metadata, a logical definition and description of attributes, information about usage, page views between the users, a social data network, and a statistical data profile; extracting information from external data sources and social media profiles to generate the social data catalog table of information; and crowd sourcing information from a ranked list of knowledgeable users to generate a ranked order of priority of information presented in profile pages of a curated answers system, wherein the information about usage includes related tables and join predicates as well as relevant filters associated with each table of the at least one of the database and the sample database, wherein the social data network includes a list of users who are knowledgeable about a particular object related to the another query, and wherein the metadata is at least one of a schema name, a table in a schema, a name of an attribute, a data type of the attribute, a primary key associated with the attribute, a constraint of the attribute, a functional dependency between the attributes, an index, a foreign key, a field name, a column name, a table name, and a query description. 9. The method of claim 1 , wherein the set of characteristics of the data profile is presented to the user of the query editor through a profile visualizer module which generates a visual representation of the data profile in at least one of a searchable format, a hierarchical format, and a navigable format. | 0.828524 |
9,743,118 | 2 | 10 | 2. The method of claim 1 , further comprising: receiving an endorsement video from another person, wherein the other person is well known and recognized among members of the plurality of community members as being knowledgeable about the at least one of the thematic content event and the genre or topic pertaining to the thematic content event that is the subject matter of the rant video generated by the first community member, and wherein the endorsement video is an endorsement for the assertion made in the rant video generated by the first community member; wherein the generated proof video further comprises the endorsement video. | 2. The method of claim 1 , further comprising: receiving an endorsement video from another person, wherein the other person is well known and recognized among members of the plurality of community members as being knowledgeable about the at least one of the thematic content event and the genre or topic pertaining to the thematic content event that is the subject matter of the rant video generated by the first community member, and wherein the endorsement video is an endorsement for the assertion made in the rant video generated by the first community member; wherein the generated proof video further comprises the endorsement video. 10. The method of claim 2 , wherein the endorsement video includes at least an audio portion with dialogue of the other person speaking, the method further comprising: generating text from the dialogue of the endorsement video; and determining an identity of the first community member based on the generated text of the dialogue of the endorsement video. | 0.948744 |
10,049,416 | 5 | 6 | 5. The method of claim 3 , wherein the job recall material is associated with a job listing, the method further comprising: responsive to a user completing the job recall activity, recommending the job listing to the user. | 5. The method of claim 3 , wherein the job recall material is associated with a job listing, the method further comprising: responsive to a user completing the job recall activity, recommending the job listing to the user. 6. The method of claim 5 , wherein the online education platform stores a plurality of job listings each associated with a plurality of learning units, and wherein recommending the job listing to the user comprises: ranking the job listings in the online education platform based on a correlation between learning units completed by the user and the plurality of learning units associated with each job listing; and recommending one or more of the job listings based on the ranking. | 0.895035 |
8,838,818 | 1 | 3 | 1. A method in a communications device comprising: the communications device accessing first features offered by an application of an application server from a plurality of application servers using a session communication protocol; the communications device obtaining a non-executable editable file that comprises (a) first information describing how to access at least one additional feature offered by the application of the application server for which the communications device was not previously configured to access and where the additional feature is specific to the application server and (b) second information describing how to represent the at least one additional feature; the communications device dynamically updating an existing Graphic User Interface ‘GUI’ so as to display a representation of the at least one additional feature offered by the application, in accordance with the second information; the communications device receiving input for selecting an additional feature of the at least one additional feature offered by the application via the GUI that has been dynamically updated; and the communications device accessing the additional feature offered by the application without having to change any compiled software on the communications device by using the session communication protocol in a manner for which the communications device was not previously configured to use or by using an extension of the session communication protocol in accordance with the first information. | 1. A method in a communications device comprising: the communications device accessing first features offered by an application of an application server from a plurality of application servers using a session communication protocol; the communications device obtaining a non-executable editable file that comprises (a) first information describing how to access at least one additional feature offered by the application of the application server for which the communications device was not previously configured to access and where the additional feature is specific to the application server and (b) second information describing how to represent the at least one additional feature; the communications device dynamically updating an existing Graphic User Interface ‘GUI’ so as to display a representation of the at least one additional feature offered by the application, in accordance with the second information; the communications device receiving input for selecting an additional feature of the at least one additional feature offered by the application via the GUI that has been dynamically updated; and the communications device accessing the additional feature offered by the application without having to change any compiled software on the communications device by using the session communication protocol in a manner for which the communications device was not previously configured to use or by using an extension of the session communication protocol in accordance with the first information. 3. The method of claim 1 wherein the application server is a media server, the at least one additional feature being at least one additional media feature, the session communication protocol being based on Session Initiated Protocol ‘SIP’ | 0.549242 |
9,178,901 | 1 | 6 | 1. A method comprising: receiving a uniform resource locator (URL) that includes one or more substrings, wherein each substring comprises a plurality of alphanumeric characters; extracting, via one or more processors, a plurality of features associated with the URL, wherein at least one first feature of the plurality of features is a domain confidence level that determines a reliability of a domain or a second level domain of the URL, wherein the reliability is based on a ratio of a number of known benign URLs hosted by the domain or the second level domain of the URL compared to a number of known malicious URLs hosted by the domain or the second level domain; determining, as at least one second feature of the plurality of features, a similarity measure between a whole or part of the URL and a brand name associated with an authentic resource or a legitimate entity; and applying one or more classification models to the at least one first feature and the at least one second feature to determine whether a resource located by the URL is an unauthentic resource. | 1. A method comprising: receiving a uniform resource locator (URL) that includes one or more substrings, wherein each substring comprises a plurality of alphanumeric characters; extracting, via one or more processors, a plurality of features associated with the URL, wherein at least one first feature of the plurality of features is a domain confidence level that determines a reliability of a domain or a second level domain of the URL, wherein the reliability is based on a ratio of a number of known benign URLs hosted by the domain or the second level domain of the URL compared to a number of known malicious URLs hosted by the domain or the second level domain; determining, as at least one second feature of the plurality of features, a similarity measure between a whole or part of the URL and a brand name associated with an authentic resource or a legitimate entity; and applying one or more classification models to the at least one first feature and the at least one second feature to determine whether a resource located by the URL is an unauthentic resource. 6. The method as recited in claim 1 , further comprising: receiving a plurality of training URLs known to be malicious URLs or benign URLs; and learning the one or more classification models using one or more machine learning algorithms based on features extracted from the plurality of training URLs. | 0.694106 |
10,073,898 | 6 | 7 | 6. A method according to claim 1 , wherein the method is for use in transferring content from a first file and a second file to the store, the method including: a) transferring at least one content instance from the first file to the store in accordance with a first mapping; and, b) transferring at least one content instance from the second file to the store in accordance with a second mapping. | 6. A method according to claim 1 , wherein the method is for use in transferring content from a first file and a second file to the store, the method including: a) transferring at least one content instance from the first file to the store in accordance with a first mapping; and, b) transferring at least one content instance from the second file to the store in accordance with a second mapping. 7. A method according to claim 6 , wherein the method includes: a) transferring at least one content instance from the first file to the store using a first processing system; b) transferring at least one content instance from the second file to the store using a second processing system. | 0.940116 |
8,866,827 | 1 | 13 | 1. In a computing environment, a method comprising: detecting barriers in a bulk synchronous program, each barrier delimiting supersteps; and compiling the supersteps into stream code kernels for execution by the graphics processing unit. | 1. In a computing environment, a method comprising: detecting barriers in a bulk synchronous program, each barrier delimiting supersteps; and compiling the supersteps into stream code kernels for execution by the graphics processing unit. 13. The method of claim 1 wherein compiling the supersteps comprises, inlining calls to functions containing barriers, performing optimizations to reduce data dependencies, separating CPU code and GPU code and generating kernels and kernel launching code, convert references to CPU variables to kernel parameters, finding values used outside a defining superstep and generating code to save and load those values, and generating temporary stream allocations. | 0.685871 |
6,064,958 | 19 | 26 | 19. An article of manufacture, comprising: a computer usable medium having computer readable program code means embodied therein for causing a computer to function as a pattern recognition system, the computer readable program code means including: first computer readable program code means for causing said computer to calculate a probability of each probabilistic model expressing features of each recognition category with respect to each input feature vector derived from each input signal, wherein the probabilistic model represents a feature parameter subspace in which feature vectors of each recognition category exist and the feature parameter subspace is expressed by using mixture distributions of one-dimensional discrete distributions with arbitrary distribution shapes which are arranged in respective dimensions; and second computer readable program code means for causing said computer to output a recognition category expressed by a probabilistic model with a highest probability among a plurality of probabilistic models as a recognition result. | 19. An article of manufacture, comprising: a computer usable medium having computer readable program code means embodied therein for causing a computer to function as a pattern recognition system, the computer readable program code means including: first computer readable program code means for causing said computer to calculate a probability of each probabilistic model expressing features of each recognition category with respect to each input feature vector derived from each input signal, wherein the probabilistic model represents a feature parameter subspace in which feature vectors of each recognition category exist and the feature parameter subspace is expressed by using mixture distributions of one-dimensional discrete distributions with arbitrary distribution shapes which are arranged in respective dimensions; and second computer readable program code means for causing said computer to output a recognition category expressed by a probabilistic model with a highest probability among a plurality of probabilistic models as a recognition result. 26. The article of manufacture of claim 19, further comprising: a third computer readable program code means for causing said computer to estimate parameters of the discrete distributions from training data, by first training a continuous distribution type model with a number of mixture component distributions greater than a desired number of distributions to be mixed in the mixture distribution, then merging continuous distributions of the continuous distribution type model until a number of mixture component distributions becomes equal to the desired number of distributions, and then training a probabilistic model obtained by discretizing each continuous distribution of the continuous distribution type model after merging as an initial model. | 0.617259 |
7,707,161 | 11 | 14 | 11. The method of claim 1 wherein binding additional hyperlinks to first-level concept objects and further processing the additional-hyperlink-bound first-level concept objects to produce a set of concept objects stored in a concept-object database further comprises: binding to the first-level concept objects additional, related hyperlink-based objects; processing the first-level concept objects with respect to the hyperlink-based objects bound to the first-level concept objects; determining which of the first-level concept objects to promote to concept objects; and storing the first-level concept objects determined to be promoted to concept objects in a concept-object database. | 11. The method of claim 1 wherein binding additional hyperlinks to first-level concept objects and further processing the additional-hyperlink-bound first-level concept objects to produce a set of concept objects stored in a concept-object database further comprises: binding to the first-level concept objects additional, related hyperlink-based objects; processing the first-level concept objects with respect to the hyperlink-based objects bound to the first-level concept objects; determining which of the first-level concept objects to promote to concept objects; and storing the first-level concept objects determined to be promoted to concept objects in a concept-object database. 14. The method of claim 11 wherein determining whether a first-level concept object can be promotes to a concept object further comprises: determining the number of hyperlink-based objects bound to the first-level concept object; determining patterns and distributions of hyperlinks encoded by hyperlink-based objects bound to the first-level concept object; determining interrelationships between hyperlink-based objects bound to the first-level concept object; and determining whether the first-level concept object can be promotes to a concept object based on the determined number of hyperlink-based objects bound to the first-level concept object, the determined patterns and distributions of hyperlinks encoded by hyperlink-based objects bound to the first-level concept object, and the determined interrelationships between hyperlink-based objects bound to the first-level concept object. | 0.711848 |
8,429,604 | 14 | 18 | 14. Computer-executable software code stored to a non-transitory computer-readable medium, which when executed by a computer causes the computer to perform a method comprising: receiving a request to extract behavioral code from a software code file that comprises said behavioral code and structural code; responsive to the request, extracting from the software code file at least a portion of the behavioral code into a separate file, and generating binding code for referencing the extracted behavioral code to maintain run-time behavior of the software code file consistent with its run-time behavior before said extracting; inserting, into the software code file, said binding code for referencing the extracted behavioral code; and wherein said extracting comprises enabling, by a user interface, selection of one or more of identified behavioral code that is to be extracted from the software code file into the separate file; and extracting the selected one or more of the identified behavioral code from the software code file into the separate file. | 14. Computer-executable software code stored to a non-transitory computer-readable medium, which when executed by a computer causes the computer to perform a method comprising: receiving a request to extract behavioral code from a software code file that comprises said behavioral code and structural code; responsive to the request, extracting from the software code file at least a portion of the behavioral code into a separate file, and generating binding code for referencing the extracted behavioral code to maintain run-time behavior of the software code file consistent with its run-time behavior before said extracting; inserting, into the software code file, said binding code for referencing the extracted behavioral code; and wherein said extracting comprises enabling, by a user interface, selection of one or more of identified behavioral code that is to be extracted from the software code file into the separate file; and extracting the selected one or more of the identified behavioral code from the software code file into the separate file. 18. The computer-executable software code of claim 14 wherein said structural code comprises markup language code, and wherein said behavioral code comprises at least one of scripting language code and event handler code defined in a markup language. | 0.645892 |
7,765,209 | 1 | 3 | 1. A method performed by one or more server devices, the method comprising: fetching, by one or more processors associated with the one or more server devices, first information from a post to a blog that includes a plurality of posts; extracting, by one or more processors associated with the one or more server devices, second information, associated with the blog, from a source different than the posts included in the blog; creating, by one or more processors associated with the one or more server devices, a hybrid document by combining the first information and the second information; and using, by one or more processors associated with the one or more server devices, the hybrid document to determine a relevance of the post to a search query. | 1. A method performed by one or more server devices, the method comprising: fetching, by one or more processors associated with the one or more server devices, first information from a post to a blog that includes a plurality of posts; extracting, by one or more processors associated with the one or more server devices, second information, associated with the blog, from a source different than the posts included in the blog; creating, by one or more processors associated with the one or more server devices, a hybrid document by combining the first information and the second information; and using, by one or more processors associated with the one or more server devices, the hybrid document to determine a relevance of the post to a search query. 3. The method of claim 1 where the extracting the second information includes: extracting, from a feed, at least one of a title of the blog, an author of the blog, or a profile of the author of the blog. | 0.813076 |
9,063,653 | 1 | 4 | 1. An input method for a communication device having a processor, the method comprising: receiving an input character string; ranking, by the processor, a predicted character string associated with the input character string, wherein the ranking depends on whether the input character string is a substring of the predicted character string and at least on one of a typing speed and a typing confidence, wherein the typing speed reflects a speed at which the character string is input, and wherein the typing confidence reflects a confidence in a detected input associated with the input character string; and displaying the ranked predicted character string. | 1. An input method for a communication device having a processor, the method comprising: receiving an input character string; ranking, by the processor, a predicted character string associated with the input character string, wherein the ranking depends on whether the input character string is a substring of the predicted character string and at least on one of a typing speed and a typing confidence, wherein the typing speed reflects a speed at which the character string is input, and wherein the typing confidence reflects a confidence in a detected input associated with the input character string; and displaying the ranked predicted character string. 4. The method of claim 1 , wherein the typing speed comprises the average typing speed across a predetermined number of most recently typed characters. | 0.803385 |
7,783,630 | 1 | 6 | 1. A method of determining a relevancy ranking score, comprising: receiving an indication that tuning a relevancy ranking score algorithm to a selected preference is desired, wherein the relevancy ranking score comprises a sum of three or more feature scores each multiplied by a separate weight, wherein the three or more feature scores comprise a scope or depth score, an accuracy or validity score, a clarity score, a currency score, or a source score, and wherein the scope or depth score comprises a score indicating satisfied constraints, and wherein the accuracy or validity score comprises a score indicating constraints improving query precision, and wherein the clarity score comprises a score indicating information presented in a clear manner, and wherein the currency score comprises a score indicating more recent results, and wherein the source score comprises a score indicating source quality, wherein presented in the clear manner for the clarity score comprises having a higher score in an event in which a title, an abstract, or a date is present; and updating, using a processor, the relevancy ranking score algorithm based at least in part on the selected preference, wherein the relevancy ranking score of a search result resulting from a search query is based at least in part on one or more constraints of the search query. | 1. A method of determining a relevancy ranking score, comprising: receiving an indication that tuning a relevancy ranking score algorithm to a selected preference is desired, wherein the relevancy ranking score comprises a sum of three or more feature scores each multiplied by a separate weight, wherein the three or more feature scores comprise a scope or depth score, an accuracy or validity score, a clarity score, a currency score, or a source score, and wherein the scope or depth score comprises a score indicating satisfied constraints, and wherein the accuracy or validity score comprises a score indicating constraints improving query precision, and wherein the clarity score comprises a score indicating information presented in a clear manner, and wherein the currency score comprises a score indicating more recent results, and wherein the source score comprises a score indicating source quality, wherein presented in the clear manner for the clarity score comprises having a higher score in an event in which a title, an abstract, or a date is present; and updating, using a processor, the relevancy ranking score algorithm based at least in part on the selected preference, wherein the relevancy ranking score of a search result resulting from a search query is based at least in part on one or more constraints of the search query. 6. The method of claim 1 , wherein updating the relevancy ranking score algorithm includes adding a constant to an element of the relevancy ranking score algorithm. | 0.531429 |
8,083,775 | 1 | 3 | 1. A medical device comprising: a bone screw having a longitudinal axis, a proximal end and a distal end; the distal end of the bone screw adapted to engage a vertebra; a housing at the proximal end of the bone screw; a bore in the housing aligned with the longitudinal axis of the bone screw, the bore having an open end and the bore terminating in a spherical pocket; a post having a ball-shaped retainer at a first end, the post being positioned in the bore of the housing such that the ball-shaped retainer is trapped within the spherical pocket allowing the post to pivot about a pivot point at the center of the ball-shaped retainer, and a second end of the post extends through the open end of the bore; a compliant member positioned in the bore between the housing and post to flexibly align the post with the bore and the longitudinal axis of the bone screw; and a bone screw thread which extends along said bone screw and a portion of said housing, said bone screw thread extending more proximally along the housing than the pivot point at the center of the ball-shaped retainer such that, upon implantation, the bone screw and the portion of the housing are adapted to be implanted in a bone and the pivot point is adapted to be positioned within the bone. | 1. A medical device comprising: a bone screw having a longitudinal axis, a proximal end and a distal end; the distal end of the bone screw adapted to engage a vertebra; a housing at the proximal end of the bone screw; a bore in the housing aligned with the longitudinal axis of the bone screw, the bore having an open end and the bore terminating in a spherical pocket; a post having a ball-shaped retainer at a first end, the post being positioned in the bore of the housing such that the ball-shaped retainer is trapped within the spherical pocket allowing the post to pivot about a pivot point at the center of the ball-shaped retainer, and a second end of the post extends through the open end of the bore; a compliant member positioned in the bore between the housing and post to flexibly align the post with the bore and the longitudinal axis of the bone screw; and a bone screw thread which extends along said bone screw and a portion of said housing, said bone screw thread extending more proximally along the housing than the pivot point at the center of the ball-shaped retainer such that, upon implantation, the bone screw and the portion of the housing are adapted to be implanted in a bone and the pivot point is adapted to be positioned within the bone. 3. The medical device of claim 1 , wherein the bone screw is adapted for insertion in a pedicle of a vertebra such that, upon implantation, the bone screw and the portion of the housing are adapted to be implanted in the pedicle and the pivot point is adapted to be positioned within the pedicle, without obstruction of pivoting of the post. | 0.501462 |
9,489,657 | 1 | 4 | 1. A computer-implemented method, comprising: receiving over a communications network a plurality of chat messages from two or more different chat rooms; analyzing the plurality of messages to extract a summary of activity taking place in the two or more chat rooms, wherein the summary of activity further includes a chat room summary to be presented on a distinct region of the display for each of the two or more chat rooms, the distinct region of a plurality of the chat room summaries each including a plurality of subregions, a first subregion presenting one or more infographics reflecting an amount of participant activity in its respective chat room, wherein the infographics provide a real-time indication of a participant's activity in its respective chat room; and causing the summary of activity to be presented on a display. | 1. A computer-implemented method, comprising: receiving over a communications network a plurality of chat messages from two or more different chat rooms; analyzing the plurality of messages to extract a summary of activity taking place in the two or more chat rooms, wherein the summary of activity further includes a chat room summary to be presented on a distinct region of the display for each of the two or more chat rooms, the distinct region of a plurality of the chat room summaries each including a plurality of subregions, a first subregion presenting one or more infographics reflecting an amount of participant activity in its respective chat room, wherein the infographics provide a real-time indication of a participant's activity in its respective chat room; and causing the summary of activity to be presented on a display. 4. The computer-implemented method of claim 1 in which the one or more infographics further includes a timeline representing an historical amount of participant activity over a prescribed period of time. | 0.768793 |
9,959,869 | 12 | 13 | 12. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, receiving text data representing at least a portion of an utterance; receiving hint data associated with the utterance; determining first ranking data using the text data and the hint data, wherein the first ranking data represents a relative rank of a first natural language understanding (“NLU”) component of a plurality of NLU components, wherein the first NLU component is associated with a first domain; determining second ranking data using the text data and the hint data, wherein the second ranking data represents a relative rank of a second NLU component of the plurality of NLU components, wherein the second NLU component is associated with a second domain; selecting the first NLU component based at least partly on the first ranking data and the second ranking data; and generating a response to the utterance using the first NLU component and the text data. | 12. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, receiving text data representing at least a portion of an utterance; receiving hint data associated with the utterance; determining first ranking data using the text data and the hint data, wherein the first ranking data represents a relative rank of a first natural language understanding (“NLU”) component of a plurality of NLU components, wherein the first NLU component is associated with a first domain; determining second ranking data using the text data and the hint data, wherein the second ranking data represents a relative rank of a second NLU component of the plurality of NLU components, wherein the second NLU component is associated with a second domain; selecting the first NLU component based at least partly on the first ranking data and the second ranking data; and generating a response to the utterance using the first NLU component and the text data. 13. The computer-implemented method of claim 12 , wherein receiving the hint data comprises receiving data indicating a likely domain with which the text data is associated. | 0.852137 |
9,990,432 | 1 | 13 | 1. A method, comprising the steps of: receiving, by a server computer communicatively coupled to a network and comprising at least one processor executing specific computer-executable instructions within a memory, via a first graphical user interface (GUI) for a multi-lingual domain name search engine displayed on a client computer, a domain name search string; tokenizing, by the server computer, the domain name search string; identifying, by the server computer, a search string token within the domain name search string as a concept seed; executing, by the server computer, a first database command to create a data record storing the search string token in association with a concept id; executing, by the server computer, a crawl of: a domain name search log, or at least one domain name system (DNS) zone file; tokenizing, by the server computer, at least one domain name text string within the domain name search log or the at least one DNS zone file; identifying, by the server computer, within the at least one domain name text string, at least one synonym or translation of the search string token; executing, by the server computer, a second database command to create at least one data record storing: the at least one synonym or translation of the search string token; the concept id; and at least one language associated with the at least one synonym or translation; identifying, by the server computer, based on the search string token in the domain name search string, at least one concept comprising a collection of the at least one data record sharing the concept id; generating, by the server computer, a second GUI including a displayed list recommending at least one available domain name comprising the at least one concept in the at least one language, the displayed list being ordered according to a frequency of use of the at least one concept; and transmitting, by the server computer, the second GUI to the client computer for display. | 1. A method, comprising the steps of: receiving, by a server computer communicatively coupled to a network and comprising at least one processor executing specific computer-executable instructions within a memory, via a first graphical user interface (GUI) for a multi-lingual domain name search engine displayed on a client computer, a domain name search string; tokenizing, by the server computer, the domain name search string; identifying, by the server computer, a search string token within the domain name search string as a concept seed; executing, by the server computer, a first database command to create a data record storing the search string token in association with a concept id; executing, by the server computer, a crawl of: a domain name search log, or at least one domain name system (DNS) zone file; tokenizing, by the server computer, at least one domain name text string within the domain name search log or the at least one DNS zone file; identifying, by the server computer, within the at least one domain name text string, at least one synonym or translation of the search string token; executing, by the server computer, a second database command to create at least one data record storing: the at least one synonym or translation of the search string token; the concept id; and at least one language associated with the at least one synonym or translation; identifying, by the server computer, based on the search string token in the domain name search string, at least one concept comprising a collection of the at least one data record sharing the concept id; generating, by the server computer, a second GUI including a displayed list recommending at least one available domain name comprising the at least one concept in the at least one language, the displayed list being ordered according to a frequency of use of the at least one concept; and transmitting, by the server computer, the second GUI to the client computer for display. 13. The system of claim 1 , further comprising a tokenizer configured to: tokenize the domain name search string into a sequence of tokens corresponding to the at least one concept; and detect the at least one language. | 0.75 |
9,311,528 | 41 | 56 | 41. A computer system having a touch interface and a graphical user interface, wherein the computer system includes a computer memory encoded with executable instructions for causing the computer system to generate a graphical user interface, the graphical user interface comprising: a main window displayed on a touch sensing touch screen including an indication of a gesture to be performed on the touch screen, the main window configured for detecting a practice gesture; and a touch monitor window graphically distinct from and in an area of the touch screen non-overlapping with the main window, the touch monitor window including an interactive feedback mechanism displayed on the touch screen, the interactive feedback mechanism including an indication of an accuracy of the practice gesture currently being performed. | 41. A computer system having a touch interface and a graphical user interface, wherein the computer system includes a computer memory encoded with executable instructions for causing the computer system to generate a graphical user interface, the graphical user interface comprising: a main window displayed on a touch sensing touch screen including an indication of a gesture to be performed on the touch screen, the main window configured for detecting a practice gesture; and a touch monitor window graphically distinct from and in an area of the touch screen non-overlapping with the main window, the touch monitor window including an interactive feedback mechanism displayed on the touch screen, the interactive feedback mechanism including an indication of an accuracy of the practice gesture currently being performed. 56. A mobile telephone having a touch interface and a graphical user interface, wherein the mobile telephone includes the computer system of claim 41 . | 0.846232 |
10,042,748 | 21 | 22 | 21. The method of claim 1 , where the second set of data is collected during a game play session and the game player type for the game player is previously identified. | 21. The method of claim 1 , where the second set of data is collected during a game play session and the game player type for the game player is previously identified. 22. The method of claim 21 , wherein determining the at least one game player type for the current game player includes factoring in the previously identified game player type. | 0.969739 |
8,620,958 | 1 | 2 | 1. A processor-implemented method for generating and utilizing a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, the processor-implemented method comprising: associating, by a processor, a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; associating, by the processor, the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; constructing, by the processor, a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same non-contextual data object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different context objects; receiving, from a requester, a request for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and returning, to the requester, said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library. | 1. A processor-implemented method for generating and utilizing a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, the processor-implemented method comprising: associating, by a processor, a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; associating, by the processor, the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; constructing, by the processor, a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same non-contextual data object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different context objects; receiving, from a requester, a request for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and returning, to the requester, said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library. 2. The processor-implemented method of claim 1 , further comprising: data mining, by the processor, a data structure for the non-contextual data object and the context object, wherein said data mining locates said at least one specific data store that comprises data contained in the non-contextual data object and the context object. | 0.743472 |
9,535,900 | 15 | 21 | 15. A computer program product residing on a non-transitory computer readable storage medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising: identifying content in a document of a received communication, wherein the content includes a language expression; determining a context of the language expression from a defined range of the content in the document; and generating an action item, including rendering a menu of action items, the action items including one or more of generating a reply to email, a new email, a new task, a new meeting and a chat session, generating the action item associated with the language expression based upon, at least in part, the context of the language expression, wherein the action item, when executed by a user, includes one or more excerpts from material referenced by the content in the document, the material referenced by the content in the document being distinct from the document. | 15. A computer program product residing on a non-transitory computer readable storage medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising: identifying content in a document of a received communication, wherein the content includes a language expression; determining a context of the language expression from a defined range of the content in the document; and generating an action item, including rendering a menu of action items, the action items including one or more of generating a reply to email, a new email, a new task, a new meeting and a chat session, generating the action item associated with the language expression based upon, at least in part, the context of the language expression, wherein the action item, when executed by a user, includes one or more excerpts from material referenced by the content in the document, the material referenced by the content in the document being distinct from the document. 21. The computer program product of claim 15 further comprising annotating the defined range of the content in the document. | 0.621951 |
9,075,793 | 1 | 2 | 1. A system to provide an autocomplete recommended word, the system comprising: a recommended word database configured to store at least one first recommended word list, the at least one first recommended word list comprising at least one word in a first language; a recommended word indexer module configured to convert at least one first word in the at least one first recommended word list to at least one converted word, and to index the converted word according to at least one index unit, the at least one index unit comprising at least one of a consonant/vowel unit and a syllable unit, wherein the at least one converted word comprises a pronunciation in the first language of the at least one first word spelled using a second language different from the first language and the at least one index unit comprises a pronunciation of the at least one consonant/vowel unit and syllable unit spelled using the second language; a recommended word index database configured to store the at least one converted word in association with the at least one index unit; and a query autocompletion server configured to receive a query comprising a subject index unit comprising one of the at least one index unit, to determine at least one autocomplete recommended word, and to transmit the at least one autocomplete recommended word to a web server, wherein the at least one autocomplete recommended word comprises at least one first word that corresponds to at least one converted word that is indexed according to the subject index unit; wherein the at least one converted word has a different meaning in the second language than the at least one word in the first language. | 1. A system to provide an autocomplete recommended word, the system comprising: a recommended word database configured to store at least one first recommended word list, the at least one first recommended word list comprising at least one word in a first language; a recommended word indexer module configured to convert at least one first word in the at least one first recommended word list to at least one converted word, and to index the converted word according to at least one index unit, the at least one index unit comprising at least one of a consonant/vowel unit and a syllable unit, wherein the at least one converted word comprises a pronunciation in the first language of the at least one first word spelled using a second language different from the first language and the at least one index unit comprises a pronunciation of the at least one consonant/vowel unit and syllable unit spelled using the second language; a recommended word index database configured to store the at least one converted word in association with the at least one index unit; and a query autocompletion server configured to receive a query comprising a subject index unit comprising one of the at least one index unit, to determine at least one autocomplete recommended word, and to transmit the at least one autocomplete recommended word to a web server, wherein the at least one autocomplete recommended word comprises at least one first word that corresponds to at least one converted word that is indexed according to the subject index unit; wherein the at least one converted word has a different meaning in the second language than the at least one word in the first language. 2. The system of claim 1 , wherein the web server is configured to receive the query from a web browser, to transfer the query to the query autocompletion server, to receive the at least one autocomplete recommended word from the query autocompletion server, and to transmit the at least one autocomplete recommended word to the web browser. | 0.683673 |
9,813,879 | 23 | 28 | 23. The mobile face-to-face interaction monitoring method according to claim 20 , wherein: the creating the volume topography based on the sound signals is performed during a training period; and the determining the turn by using the volume topography comprises determining current turn by matching current sound signals with the volume topography, after the training period. | 23. The mobile face-to-face interaction monitoring method according to claim 20 , wherein: the creating the volume topography based on the sound signals is performed during a training period; and the determining the turn by using the volume topography comprises determining current turn by matching current sound signals with the volume topography, after the training period. 28. The mobile face-to-face interaction monitoring method according to claim 23 , further comprising: recreating the volume topography when there is a change in the conversation group and the surrounding area. | 0.950591 |
9,563,850 | 15 | 16 | 15. The system of claim 12 , wherein the initiate transmission of the identified and ranked two or more geographical locations to comprise highlight the identified and ranked two or more geographical locations by a provision of a color code on a heat map and wherein the heat map is to be overlaid on the world map. | 15. The system of claim 12 , wherein the initiate transmission of the identified and ranked two or more geographical locations to comprise highlight the identified and ranked two or more geographical locations by a provision of a color code on a heat map and wherein the heat map is to be overlaid on the world map. 16. The system of claim 15 , wherein the color code is to define a ranking order of the identified and ranked two or more geographical locations. | 0.956794 |
9,672,525 | 9 | 12 | 9. A tangible, non-transitory, storage medium storing processor-executable instructions which, when executed by at least one processor, cause the at least one processor to: receive a request for an advertisement to be displayed on a Web page; receive information about the Web page, wherein the information is received from a source other than the Web page, and the information is not included in content of the Web page, the Web page including at least one advertising area for an advertisement; generate an advertisement and additional content that is based on a source that differs from a source of the advertisement, the advertisement and the additional content being generated using the information about the Web page, the information received from the source other than the Web page, and information received from the source that differs from the source of the advertisement, wherein generating the additional content includes generating the additional content about a product or a service that is represented in the advertisement or a link to a webpage having content related to the product or the service; and serve the generated advertisement in the advertising area or in proximity to the advertising area, to induce display of the generated advertisement and the generated additional content related to the information, received from the source other than the Web page, about the Web page, in association with the Web page, on a user device, wherein serving the generated advertisement in the advertising area or in proximity to the advertising area comprises encapsulating the generated additional content within the generated advertisement. | 9. A tangible, non-transitory, storage medium storing processor-executable instructions which, when executed by at least one processor, cause the at least one processor to: receive a request for an advertisement to be displayed on a Web page; receive information about the Web page, wherein the information is received from a source other than the Web page, and the information is not included in content of the Web page, the Web page including at least one advertising area for an advertisement; generate an advertisement and additional content that is based on a source that differs from a source of the advertisement, the advertisement and the additional content being generated using the information about the Web page, the information received from the source other than the Web page, and information received from the source that differs from the source of the advertisement, wherein generating the additional content includes generating the additional content about a product or a service that is represented in the advertisement or a link to a webpage having content related to the product or the service; and serve the generated advertisement in the advertising area or in proximity to the advertising area, to induce display of the generated advertisement and the generated additional content related to the information, received from the source other than the Web page, about the Web page, in association with the Web page, on a user device, wherein serving the generated advertisement in the advertising area or in proximity to the advertising area comprises encapsulating the generated additional content within the generated advertisement. 12. The tangible, non-transitory, storage medium of claim 9 wherein the information received from the source other than the Web page include a link to another Web page. | 0.550802 |
10,156,983 | 1 | 8 | 1. A method of character recognition, the character having a main stroke defining a main form of the character and optional secondary strokes external to the main form of the character, the method comprising: removing one or more duplicate successive points of a plurality of points in a handwritten character to form an enhanced handwritten character; spacing the plurality of points of the enhanced handwritten character a uniform distance apart; detecting, via circuitry, one or more primary strokes corresponding to the main form of the character and one or more ancillary strokes of the enhanced handwritten character; generating a primary merged stroke from the one or more primary strokes; extracting, via the circuitry, one or more raw point-based features from local features of the primary merged stroke, wherein the raw point-based features are geometric characteristics selected from the group consisting of an axis coordinate, a relative position, an aspect ratio, a slope and an angle; extracting, via the circuitry, one or more statistical features from statistics in the form of such a histogram, mean, mode, maximum, minimum, variance, and standard deviation from the raw point-based features computed over the one or more raw point-based features to form one or more primary merged stroke features; extracting, via the circuitry, one or more features from the ancillary strokes to form one or more ancillary stroke features; training one or more stroke models on features of the main stroke and features of the secondary strokes and classifying data from the one or more primary merged stroke features and the one or more ancillary stroke features using the trained one or more stroke models; determining, via the circuitry, a set of main stroke candidates and a set of secondary stroke candidates from the data classified by the one or more stroke models; computing, via the circuitry, likelihood values indicative of whether respective main strokes of the set of main stroke candidates combined with respective secondary strokes from the set of secondary stroke candidates form the character; and determining, via the circuitry, the character from the likelihood values. | 1. A method of character recognition, the character having a main stroke defining a main form of the character and optional secondary strokes external to the main form of the character, the method comprising: removing one or more duplicate successive points of a plurality of points in a handwritten character to form an enhanced handwritten character; spacing the plurality of points of the enhanced handwritten character a uniform distance apart; detecting, via circuitry, one or more primary strokes corresponding to the main form of the character and one or more ancillary strokes of the enhanced handwritten character; generating a primary merged stroke from the one or more primary strokes; extracting, via the circuitry, one or more raw point-based features from local features of the primary merged stroke, wherein the raw point-based features are geometric characteristics selected from the group consisting of an axis coordinate, a relative position, an aspect ratio, a slope and an angle; extracting, via the circuitry, one or more statistical features from statistics in the form of such a histogram, mean, mode, maximum, minimum, variance, and standard deviation from the raw point-based features computed over the one or more raw point-based features to form one or more primary merged stroke features; extracting, via the circuitry, one or more features from the ancillary strokes to form one or more ancillary stroke features; training one or more stroke models on features of the main stroke and features of the secondary strokes and classifying data from the one or more primary merged stroke features and the one or more ancillary stroke features using the trained one or more stroke models; determining, via the circuitry, a set of main stroke candidates and a set of secondary stroke candidates from the data classified by the one or more stroke models; computing, via the circuitry, likelihood values indicative of whether respective main strokes of the set of main stroke candidates combined with respective secondary strokes from the set of secondary stroke candidates form the character; and determining, via the circuitry, the character from the likelihood values. 8. The method of claim 1 , further comprising: utilizing a Dynamic Bayes Network-based Hidden Markov Model classifier for primary merged stroke classification. | 0.839718 |
8,554,723 | 14 | 15 | 14. A system of matching users to other users, the system comprising: at least one data store for storing event data comprising order data reflective of items ordered from an electronic catalog by each of a plurality of users; and at least one computing device including a processor in communication with the at least one data store, the at least one computing device operable to: programmatically generate 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 and based at least in part on the score, programmatically determine whether to recommend the second user to the first user. | 14. A system of matching users to other users, the system comprising: at least one data store for storing event data comprising order data reflective of items ordered from an electronic catalog by each of a plurality of users; and at least one computing device including a processor in communication with the at least one data store, the at least one computing device operable to: programmatically generate 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 and based at least in part on the score, programmatically determine whether to recommend the second user to the first user. 15. The system of claim 14 , wherein the score reflects a degree to which the first plurality of items and the second plurality of items are related. | 0.843816 |
9,015,081 | 1 | 4 | 1. A computer-based method for predicting escalations, comprising: extracting an escalation feature from a webpage; running the escalation feature through a classifier; generating an escalation likelihood result from running the escalation feature through the classifier, the escalation likelihood result comprising at least one of: an estimation that a subsequent search query will comprise an escalation when compared to a previous search query; or an estimation that a subsequent webpage selection will comprise an escalation when compared to a previous webpage selection; and generating a resource utilization intent (RUI) likelihood result from running the escalation feature through the classifier, the RUI likelihood result comprising an estimation that a second subsequent search query will comprise a resource identification query, where a resource identified by the resource identification query comprises at least one of a service or a good related to a prior search query. | 1. A computer-based method for predicting escalations, comprising: extracting an escalation feature from a webpage; running the escalation feature through a classifier; generating an escalation likelihood result from running the escalation feature through the classifier, the escalation likelihood result comprising at least one of: an estimation that a subsequent search query will comprise an escalation when compared to a previous search query; or an estimation that a subsequent webpage selection will comprise an escalation when compared to a previous webpage selection; and generating a resource utilization intent (RUI) likelihood result from running the escalation feature through the classifier, the RUI likelihood result comprising an estimation that a second subsequent search query will comprise a resource identification query, where a resource identified by the resource identification query comprises at least one of a service or a good related to a prior search query. 4. The method of claim 1 , the subsequent search query the same as the second subsequent search query. | 0.895706 |
8,140,463 | 2 | 14 | 2. A system as recited in claim 1 , wherein said analysis engine comprising: a metadata generator; an information aggregation heuristics unit; an information retrieval harness; and a database; wherein said analysis engine identifies said object; wherein said analysis engine identifies said first metadata; wherein said analysis engine identifies said one or more taxonomies; wherein said analysis engine identifies information aggregation heuristics; wherein said analysis engine identifies one or more information retrieval routines that are used; wherein said analysis engine identifies contextual information that is used; wherein said analysis engine identifies third metadata for said one or more sub-objects that are previously stored in said database; wherein said information retrieval harness collects data from a plurality of said one or more information retrieval routines; wherein said information retrieval harness passes collected said data to said information aggregation heuristics unit; wherein said information aggregation heuristics unit processes said data and sends the processed data to said metadata generator; wherein said metadata generator generates said second metadata according to configured or stored taxonomies, metadata schema, organizational policies, and semantic spaces, and sends it to said service layer; and wherein said configuration module stores said one or more information retrieval routines, said taxonomies, said organizational policies, said metadata schema, and said semantic spaces used by said analysis engine and said information retrieval routines. | 2. A system as recited in claim 1 , wherein said analysis engine comprising: a metadata generator; an information aggregation heuristics unit; an information retrieval harness; and a database; wherein said analysis engine identifies said object; wherein said analysis engine identifies said first metadata; wherein said analysis engine identifies said one or more taxonomies; wherein said analysis engine identifies information aggregation heuristics; wherein said analysis engine identifies one or more information retrieval routines that are used; wherein said analysis engine identifies contextual information that is used; wherein said analysis engine identifies third metadata for said one or more sub-objects that are previously stored in said database; wherein said information retrieval harness collects data from a plurality of said one or more information retrieval routines; wherein said information retrieval harness passes collected said data to said information aggregation heuristics unit; wherein said information aggregation heuristics unit processes said data and sends the processed data to said metadata generator; wherein said metadata generator generates said second metadata according to configured or stored taxonomies, metadata schema, organizational policies, and semantic spaces, and sends it to said service layer; and wherein said configuration module stores said one or more information retrieval routines, said taxonomies, said organizational policies, said metadata schema, and said semantic spaces used by said analysis engine and said information retrieval routines. 14. A system as stated in claim 2 , wherein said system requests are triggered by user actions, including importing or publishing content. | 0.954395 |
9,292,821 | 1 | 2 | 1. A method of consuming a Component Business Model (CBM) Heat Map for Services Oriented Architecture (SOA) based solution development, the method comprising the steps of: identifying a CBM Heat Map; at a first converting step, automatically converting the tabular representation of the CBM Heat Map to a Unified Modeling Language (UML) representation; and subsequent to the first converting step, at a second converting step, converting the UML representation of the CBM Heat Map to a first iteration of input for SOA solution development; wherein the first converting step comprises the steps of: (i) retrieving a plurality of CBM elements; (ii) processing the plurality of CBM elements; (iii) identifying a plurality of UML elements that respectively correspond to the plurality of CBM elements; and (iv) forming the plurality of UML elements into the UML representation of the CBM heat map. | 1. A method of consuming a Component Business Model (CBM) Heat Map for Services Oriented Architecture (SOA) based solution development, the method comprising the steps of: identifying a CBM Heat Map; at a first converting step, automatically converting the tabular representation of the CBM Heat Map to a Unified Modeling Language (UML) representation; and subsequent to the first converting step, at a second converting step, converting the UML representation of the CBM Heat Map to a first iteration of input for SOA solution development; wherein the first converting step comprises the steps of: (i) retrieving a plurality of CBM elements; (ii) processing the plurality of CBM elements; (iii) identifying a plurality of UML elements that respectively correspond to the plurality of CBM elements; and (iv) forming the plurality of UML elements into the UML representation of the CBM heat map. 2. The method of claim 1 wherein the second converting step is performed using service oriented modeling and architecture (SOMA). | 0.848946 |
8,473,489 | 1 | 5 | 1. A method performed by a system comprising one or more computers, the method comprising: determining that a first search query includes a respective text reference to each of one or more predetermined attributes, wherein each attribute is associated with a first entity type; generating a second search query including the first search query and one or more terms that refer to the first entity type; and evaluating search results obtained for the second search query to select one or more names of entities of the first entity type to include in a response to the first search query, wherein each search result identifies a respective search result resource, and wherein evaluating the search results comprises: identifying occurrences of references to entities of the first entity type in the same search result resource as one or more terms from the first search query; and selecting the names of entities based on the identified occurrences. | 1. A method performed by a system comprising one or more computers, the method comprising: determining that a first search query includes a respective text reference to each of one or more predetermined attributes, wherein each attribute is associated with a first entity type; generating a second search query including the first search query and one or more terms that refer to the first entity type; and evaluating search results obtained for the second search query to select one or more names of entities of the first entity type to include in a response to the first search query, wherein each search result identifies a respective search result resource, and wherein evaluating the search results comprises: identifying occurrences of references to entities of the first entity type in the same search result resource as one or more terms from the first search query; and selecting the names of entities based on the identified occurrences. 5. The method of claim 1 , further comprising: identifying resources that include one or more references to entities of the first entity type; and annotating each of the identified resources with an annotation in an index database to indicate that the resource includes one or more references to entities of the first entity type. | 0.658385 |
9,251,166 | 17 | 20 | 17. A non-transitory machine-readable storage medium having machine executable instructions embedded thereon, which when executed by a processor of a machine, cause the machine to perform operations comprising: retrieving a plurality of search queries; generating a plurality of search query nodes that represent one or more of the plurality of search queries; creating a visual representation of the search query nodes where one or more connections between the search query nodes indicate one or more relationships between two or more of the plurality of search queries; partitioning the visual representation into a plurality of tiles, each tile representing a defined portion of a rendering of the visual representation, each tile configured to be accessed independently of one or more other tiles of the plurality of tiles; and selecting a tile containing one of the plurality of search query nodes corresponding to the submitted search query, from the plurality of tiles, and one or more tiles surrounding the identified tile. | 17. A non-transitory machine-readable storage medium having machine executable instructions embedded thereon, which when executed by a processor of a machine, cause the machine to perform operations comprising: retrieving a plurality of search queries; generating a plurality of search query nodes that represent one or more of the plurality of search queries; creating a visual representation of the search query nodes where one or more connections between the search query nodes indicate one or more relationships between two or more of the plurality of search queries; partitioning the visual representation into a plurality of tiles, each tile representing a defined portion of a rendering of the visual representation, each tile configured to be accessed independently of one or more other tiles of the plurality of tiles; and selecting a tile containing one of the plurality of search query nodes corresponding to the submitted search query, from the plurality of tiles, and one or more tiles surrounding the identified tile. 20. The machine-readable storage medium of claim 17 , wherein the creating of the visual representation includes generating edges between representations of search queries based on the relationships between queries of the plurality of search queries. | 0.736842 |
9,836,301 | 12 | 18 | 12. A non-transitory computer readable medium having stored thereon machine readable instructions for component discovery, the machine readable instructions, when executed, cause a processor to: determine business classes by excluding packages and classes in source code; extract code features from the business classes by extracting packaging information for each of the business classes, wherein extracting packaging information for each of the business classes includes extracting concept words embedded in business class names, extracting a packaging hierarchy as a string, and extracting a substring that describes the packaging hierarchy; estimate similarity for business class pairs based on the extracted features; cluster the business classes based on the similarity, wherein clusters generated by the clustering represent components of the source code; and determine interfaces for the components based on the clustering by identifying public methods of the business classes in a cluster of the generated clusters that are called by the business classes of other clusters from the generated clusters. | 12. A non-transitory computer readable medium having stored thereon machine readable instructions for component discovery, the machine readable instructions, when executed, cause a processor to: determine business classes by excluding packages and classes in source code; extract code features from the business classes by extracting packaging information for each of the business classes, wherein extracting packaging information for each of the business classes includes extracting concept words embedded in business class names, extracting a packaging hierarchy as a string, and extracting a substring that describes the packaging hierarchy; estimate similarity for business class pairs based on the extracted features; cluster the business classes based on the similarity, wherein clusters generated by the clustering represent components of the source code; and determine interfaces for the components based on the clustering by identifying public methods of the business classes in a cluster of the generated clusters that are called by the business classes of other clusters from the generated clusters. 18. The non-transitory computer readable medium according to claim 12 , further comprising machine readable instructions that when executed by the processor further cause the processor to: cluster a plurality of application portfolios that each includes a plurality of applications that use different types of source code including the source code. | 0.709516 |
7,536,634 | 10 | 11 | 10. A method as set forth in claim 1 , wherein said step of establishing is implemented in a start-up mode for configuration of logic of said machine-based tool so as to convert data based on contextual cues inferred from an understanding of said subject matter area. | 10. A method as set forth in claim 1 , wherein said step of establishing is implemented in a start-up mode for configuration of logic of said machine-based tool so as to convert data based on contextual cues inferred from an understanding of said subject matter area. 11. A method as set forth in claim 10 , wherein said first schema is operative to enable proper conversion of a set of data which was not specifically addressed in said configuration. | 0.939404 |
8,402,019 | 1 | 9 | 1. A method for determining a particular document that initiated a topic of interest in a collection of documents, each of the documents having contents and a time it was created, comprising: ranking the documents in the collection based on the respective times that the documents were created; ranking the documents based on how similar their respective contents are to the topic of interest; ranking the documents based on originality of their respective contents; ranking the documents based on a type of source each respective document originated from; producing a composite ranking of the documents based on the time, the contents, the originality rankings, and the type of source; and determining the particular document that initiated the topic of interest from the composite ranking. | 1. A method for determining a particular document that initiated a topic of interest in a collection of documents, each of the documents having contents and a time it was created, comprising: ranking the documents in the collection based on the respective times that the documents were created; ranking the documents based on how similar their respective contents are to the topic of interest; ranking the documents based on originality of their respective contents; ranking the documents based on a type of source each respective document originated from; producing a composite ranking of the documents based on the time, the contents, the originality rankings, and the type of source; and determining the particular document that initiated the topic of interest from the composite ranking. 9. The method of claim 1 , further comprising: ranking the documents based on a number of hyperlinks in each one of the documents, wherein the composite ranking is also based on the hyperlinks ranking. | 0.758993 |
8,321,841 | 1 | 4 | 1. A method executed by a processor for validating a service oriented architecture (SOA) oriented application, the method comprising: transforming a business process model for an SOA oriented application into a directed and connected graph; further transforming a plurality of service groupings for the business process model into corresponding directed and connected, acyclic graphs; computing all paths from root node to leaf node in the graph for the business process model; and, invalidating the business process model in response to either identifying a loop or cycle in the graph for the business process model, or identifying a shared vertex amongst the graphs for the service groupings. | 1. A method executed by a processor for validating a service oriented architecture (SOA) oriented application, the method comprising: transforming a business process model for an SOA oriented application into a directed and connected graph; further transforming a plurality of service groupings for the business process model into corresponding directed and connected, acyclic graphs; computing all paths from root node to leaf node in the graph for the business process model; and, invalidating the business process model in response to either identifying a loop or cycle in the graph for the business process model, or identifying a shared vertex amongst the graphs for the service groupings. 4. The method of claim 1 , further comprises: computing an intersection between each path and a service grouping; determining whether or not each intersection includes multiple vertices; and, invalidating the service grouping when any intersection includes multiple vertices that are not connected. | 0.782164 |
7,822,605 | 24 | 33 | 24. An apparatus for determining whether a speaker uttering a tested utterance belongs to a predetermined set comprising an at least one known speaker, wherein an at least one training utterance is available for each of the at least one known speaker, the apparatus comprising: a feature extraction component for extracting a feature group of the tested utterance or of each of the at least one training utterance; a fast scoring component for scoring a part of the feature group associated with part of the tested utterance against an at least one model for obtaining a fast intermediate score, determining an at least one fast model score using the fast intermediate score, and selecting an at least one probable model associated with a fast intermediate score which is higher than other fast intermediate scores; a frame scoring component for scoring the feature group against an at least one probable model, to obtain an at least one intermediate score; a total model scoring component for determining an at least one model score using the at least one intermediate score; and a maximal score determination component for selecting a maximal score from the at least one model score. | 24. An apparatus for determining whether a speaker uttering a tested utterance belongs to a predetermined set comprising an at least one known speaker, wherein an at least one training utterance is available for each of the at least one known speaker, the apparatus comprising: a feature extraction component for extracting a feature group of the tested utterance or of each of the at least one training utterance; a fast scoring component for scoring a part of the feature group associated with part of the tested utterance against an at least one model for obtaining a fast intermediate score, determining an at least one fast model score using the fast intermediate score, and selecting an at least one probable model associated with a fast intermediate score which is higher than other fast intermediate scores; a frame scoring component for scoring the feature group against an at least one probable model, to obtain an at least one intermediate score; a total model scoring component for determining an at least one model score using the at least one intermediate score; and a maximal score determination component for selecting a maximal score from the at least one model score. 33. The apparatus of claim 24 further comprising a decision component for determining according to the maximal score whether the speaker uttering the tested utterance belongs to the predetermined set. | 0.828179 |
9,330,119 | 15 | 20 | 15. A computer-implemented method comprising: identifying a first partition of data with a fact category, a second partition of data with an information category, a third partition of data with a hypothesis category, and a fourth partition of data with a directive category; identifying a first partition of transformative actions with a classification category, a second partition of transformative actions with an assessment category, a third partition of transformative actions with a resolution category, and a fourth partition of transformative actions with an enactment category; invoking a first action to produce a second set of data from the information category; invoking a second action to produce a third set of data from the hypothesis category; invoking a third action to produce a fourth set of data from the directive category; invoking a fourth action to produce a fifth set of data from the fact category; invoking a classification action on a first set of facts to produce a first set of information; invoking an assessment action on the first set of information to produce a first set of hypotheses; invoking a resolution action on the first set of hypotheses to produce a first set of directives; invoking an enactment action on the first set of directives to modify system behavior and to produce a second set of facts that differs from the first set of facts; wherein invoking the classification action comprises applying a set of functions that maps a particular feature vector to an observation, a prediction, a norm, or an objective in the first set of information; and wherein the particular feature vector is a vector that includes a feature object. | 15. A computer-implemented method comprising: identifying a first partition of data with a fact category, a second partition of data with an information category, a third partition of data with a hypothesis category, and a fourth partition of data with a directive category; identifying a first partition of transformative actions with a classification category, a second partition of transformative actions with an assessment category, a third partition of transformative actions with a resolution category, and a fourth partition of transformative actions with an enactment category; invoking a first action to produce a second set of data from the information category; invoking a second action to produce a third set of data from the hypothesis category; invoking a third action to produce a fourth set of data from the directive category; invoking a fourth action to produce a fifth set of data from the fact category; invoking a classification action on a first set of facts to produce a first set of information; invoking an assessment action on the first set of information to produce a first set of hypotheses; invoking a resolution action on the first set of hypotheses to produce a first set of directives; invoking an enactment action on the first set of directives to modify system behavior and to produce a second set of facts that differs from the first set of facts; wherein invoking the classification action comprises applying a set of functions that maps a particular feature vector to an observation, a prediction, a norm, or an objective in the first set of information; and wherein the particular feature vector is a vector that includes a feature object. 20. The method of claim 15 , further comprising: matching a first profile vector for a particular actor to a second profile vector to select the particular actor from a plurality of actors to perform at least one of the classification action, the assessment action, the resolution action, or the enactment action; wherein the first profile vector is computed based at least in part on tacit knowledge, a social network, and specified preferences; wherein the second profile vector is computed based at least in part on functions that map classifications, assessments, resolutions, and enactments to the second profile vector. | 0.666844 |
9,697,867 | 5 | 6 | 5. The system of claim 1 , further comprising a storage device communicably coupled to the adaptive narrative presentation circuit, the storage device including: a data store that includes data indicative of intrinsic parameters logically associated with each of a number of objects. | 5. The system of claim 1 , further comprising a storage device communicably coupled to the adaptive narrative presentation circuit, the storage device including: a data store that includes data indicative of intrinsic parameters logically associated with each of a number of objects. 6. The system of claim 5 the adaptive narration presentation circuit to further: optically identify the object based at least in part on at least one intrinsic parameter of the object including at least one of: a shape of the object, a color of the object, a proportion of the object, or an anatomical feature of the object. | 0.883871 |
8,626,588 | 12 | 14 | 12. A computer-implemented method comprising: a) receiving, with an advertising system including at least one computer, relevance information for an advertisement; b) determining, with the advertising system, at least one audio document using the received relevance information; c) generating, with the advertising system, information about the at least one audio document for presentation to an advertiser associated with the advertisement; and d) receiving, with the advertising system, from the advertiser, an offer to have its advertisement served with the at least one audio document accepted by the advertiser. | 12. A computer-implemented method comprising: a) receiving, with an advertising system including at least one computer, relevance information for an advertisement; b) determining, with the advertising system, at least one audio document using the received relevance information; c) generating, with the advertising system, information about the at least one audio document for presentation to an advertiser associated with the advertisement; and d) receiving, with the advertising system, from the advertiser, an offer to have its advertisement served with the at least one audio document accepted by the advertiser. 14. The computer-implemented method of claim 12 wherein the audio document is a radio procram. | 0.929641 |
6,073,096 | 9 | 15 | 9. A method of building class-specific cluster systems comprising the steps of: providing a speaker dependent system for each of a plurality of training speakers; partitioning an acoustic space according to classes, each class being characterized by a set of acoustic features; grouping the speaker dependent systems with the acoustic spaces according to classes to build acoustic spaces with common features from all the speaker dependent systems; and clustering the grouped acoustic spaces with common features to form cluster systems based on acoustic characteristics of the speakers, the acoustic characteristics including class-specific characteristics. | 9. A method of building class-specific cluster systems comprising the steps of: providing a speaker dependent system for each of a plurality of training speakers; partitioning an acoustic space according to classes, each class being characterized by a set of acoustic features; grouping the speaker dependent systems with the acoustic spaces according to classes to build acoustic spaces with common features from all the speaker dependent systems; and clustering the grouped acoustic spaces with common features to form cluster systems based on acoustic characteristics of the speakers, the acoustic characteristics including class-specific characteristics. 15. The method of building class-specific cluster systems as recited in claim 9, wherein the step of clustering includes the step of clustering the grouped acoustic spaces to form cluster systems based on a common accent. | 0.84966 |
8,880,519 | 9 | 12 | 9. A computer program product comprising: a computer readable hardware storage device having a computer readable program code embodied therein, said computer readable program code containing instructions that, upon being executed by a processor of a computer system, perform a method for determining a service description that most closely matches a service name provided by a user, said method comprising: said processor determining that the service name provided by the user is not an exact match to a service name in a service registry that comprises service names and associated service descriptions; said processor generating a ranked service name list by use of a name parser, a dictionary, and a name composer, wherein the ranked service name list comprise at least one alternative service name and a respective rank of each alternative service name of the at least one alternative service name, and wherein the respective rank indicates how closely the alternative service name associated with the respective rank resembles the service name provided by the user; said processor ascertaining a service description associated with a service name in the service registry that either matches the highest ranked alternative service name in the service name list or if not, matches a second alternative service name which is the next highest ranked alternative service name in the service name list; and said processor communicating the ascertained service description to the user. | 9. A computer program product comprising: a computer readable hardware storage device having a computer readable program code embodied therein, said computer readable program code containing instructions that, upon being executed by a processor of a computer system, perform a method for determining a service description that most closely matches a service name provided by a user, said method comprising: said processor determining that the service name provided by the user is not an exact match to a service name in a service registry that comprises service names and associated service descriptions; said processor generating a ranked service name list by use of a name parser, a dictionary, and a name composer, wherein the ranked service name list comprise at least one alternative service name and a respective rank of each alternative service name of the at least one alternative service name, and wherein the respective rank indicates how closely the alternative service name associated with the respective rank resembles the service name provided by the user; said processor ascertaining a service description associated with a service name in the service registry that either matches the highest ranked alternative service name in the service name list or if not, matches a second alternative service name which is the next highest ranked alternative service name in the service name list; and said processor communicating the ascertained service description to the user. 12. The computer program product of claim 9 , said ascertaining comprising: sorting the ranked service name list by respective rank of each alternative service name; and searching the service registry for the service description with the at least one alternative service name from a top entry of the ranked alternative service name such that the service description is associated with the highest ranked alternative service name. | 0.787834 |
8,688,602 | 33 | 34 | 33. The computer readable medium of claim 32 , wherein the existing metadata comprises at least one of: user behavior data; and market data. | 33. The computer readable medium of claim 32 , wherein the existing metadata comprises at least one of: user behavior data; and market data. 34. The computer readable medium of claim 33 , wherein market data comprises information regarding at least one of: inclusion of the media object in a library catalogue; purchase of the media object as a gift; the media object's presence on a current popularity chart; sharing of the media object on social networking sites; and a metric indicating a level of discussion of the media object. | 0.69261 |
7,813,929 | 1 | 12 | 1. A method of transforming an input sequence of unstructured speech recognition text into output structured document text, the method comprising: performing transformation modeling of a source unstructured speech recognition text to create a most likely word sequence output structured document text, the transformation modeling including; providing a probabilistic word substitution model to establish association probabilities indicative of target structured document text correlating with source unstructured speech recognition text; considering a set of candidate sequences of structured document text based on the word substitution model with respect to an input sequence of unstructured speech recognition text; evaluating the likelihood of candidates corresponding to the input sequence of unstructured speech recognition text; determining as an output a most likely sequence of structured document text. | 1. A method of transforming an input sequence of unstructured speech recognition text into output structured document text, the method comprising: performing transformation modeling of a source unstructured speech recognition text to create a most likely word sequence output structured document text, the transformation modeling including; providing a probabilistic word substitution model to establish association probabilities indicative of target structured document text correlating with source unstructured speech recognition text; considering a set of candidate sequences of structured document text based on the word substitution model with respect to an input sequence of unstructured speech recognition text; evaluating the likelihood of candidates corresponding to the input sequence of unstructured speech recognition text; determining as an output a most likely sequence of structured document text. 12. A method according to claim 1 , wherein the structured document text includes legal document text. | 0.870229 |
7,835,998 | 36 | 37 | 36. The method of claim 28 , wherein at least one of the incremental input and the subsequent incremental input are entered by the corresponding user on at least one of a telephone, a PDA, and a remote control. | 36. The method of claim 28 , wherein at least one of the incremental input and the subsequent incremental input are entered by the corresponding user on at least one of a telephone, a PDA, and a remote control. 37. The method of claim 36 , wherein at least one of a telephone, a PDA, and a remote control has a plurality of overloaded keys, each of the overloaded keys representing two or more characters. | 0.954481 |
9,547,648 | 17 | 18 | 17. A graphical user interface visibly displayed on a display of a user computer comprising: a user control section visibly displayed on the display of the user computer, the user control section comprising at least one button, the at least one button being configured to initiate a browser command; and a browser display area visibly displayed on the display of the user computer, the browser display area being configured to display an electronic document, the electronic document comprising objects of interest and at least one augmented object of interest selected from the objects of interest that comprise the electronic document, said augmented object comprising code that modifies code of the electronic document associated with the determined object of interest, the at least one augmented object of interest being selected by the user computer based on instructions defined by a network content provider and based on behavioral data of a network user and predetermined instructions received from the network user that identify a type of object the network user desires to have automatically saved in a user network account associated with the network work user, wherein said selected object of interest is extracted from the electronic document, the at least one augmented object of interest comprising additional information, the additional information comprising content related to the at least one determined object of interest that also provides an indication of and a capability of additional functionality for the electronic document, said additional functionality is based on a type of the at least one object of interest and a determined identity of an Internet service having functionality for performing the additional functionality respective to the determined object of interest, and is automatically performed upon user selection. | 17. A graphical user interface visibly displayed on a display of a user computer comprising: a user control section visibly displayed on the display of the user computer, the user control section comprising at least one button, the at least one button being configured to initiate a browser command; and a browser display area visibly displayed on the display of the user computer, the browser display area being configured to display an electronic document, the electronic document comprising objects of interest and at least one augmented object of interest selected from the objects of interest that comprise the electronic document, said augmented object comprising code that modifies code of the electronic document associated with the determined object of interest, the at least one augmented object of interest being selected by the user computer based on instructions defined by a network content provider and based on behavioral data of a network user and predetermined instructions received from the network user that identify a type of object the network user desires to have automatically saved in a user network account associated with the network work user, wherein said selected object of interest is extracted from the electronic document, the at least one augmented object of interest comprising additional information, the additional information comprising content related to the at least one determined object of interest that also provides an indication of and a capability of additional functionality for the electronic document, said additional functionality is based on a type of the at least one object of interest and a determined identity of an Internet service having functionality for performing the additional functionality respective to the determined object of interest, and is automatically performed upon user selection. 18. The graphical user interface of claim 17 , wherein the at least one object of interest is augmented by changing the at least one object of interest into a hyperlink. | 0.847748 |
9,384,189 | 1 | 2 | 1. An apparatus for predicting a pleasantness-unpleasantness index of a word using a computer, the apparatus comprising: a computing unit configured to compute an emotion correlation between the word and one or more comparison word, compute emotion correlations between a plurality of reference words included in a reference word set and the one or more comparison word, compute a plurality of first absolute emotion similarity values between the word and the plurality of reference words, and compute at least one second absolute emotion similarity value between a reference word and another reference word for all of the plurality of reference words included in the reference word set; and a prediction unit configured to predict the pleasantness-unpleasantness index of the word by using the plurality of first absolute emotion similarity values, the at least one second absolute emotion similarity value, and a preset pleasantness-unpleasantness index of the plurality of reference words, wherein antonyms of the word are not included in the reference word set, and the computing unit and the prediction unit are embodied on the computer. | 1. An apparatus for predicting a pleasantness-unpleasantness index of a word using a computer, the apparatus comprising: a computing unit configured to compute an emotion correlation between the word and one or more comparison word, compute emotion correlations between a plurality of reference words included in a reference word set and the one or more comparison word, compute a plurality of first absolute emotion similarity values between the word and the plurality of reference words, and compute at least one second absolute emotion similarity value between a reference word and another reference word for all of the plurality of reference words included in the reference word set; and a prediction unit configured to predict the pleasantness-unpleasantness index of the word by using the plurality of first absolute emotion similarity values, the at least one second absolute emotion similarity value, and a preset pleasantness-unpleasantness index of the plurality of reference words, wherein antonyms of the word are not included in the reference word set, and the computing unit and the prediction unit are embodied on the computer. 2. The apparatus of claim 1 , wherein the computing unit computes the emotion correlation between the word or the reference word and the comparison word by using a ratio between a probability of the word or the reference word and the comparison word appearing independently in a paragraph and a probability of the word or the reference word and the comparison word appearing together in a paragraph. | 0.744231 |
9,715,542 | 1 | 18 | 1. A computerized method of determining relevancies of multiple objects to a search query, comprising: associating one or more of the multiple objects with user-entered tags as a result of user input, thereby defining one or more corresponding tag-object pairs, wherein each tag comprises one or more tag terms, each tag term comprising text, and wherein each association of an object with a tag comprises a tag object pair; associating an object with each tag term from the one or more tag terms, thereby defining one or more corresponding tag term object pairs, wherein at least one of the one or more tags comprises a string of multiple terms entered by a user; determining for each tag term object pair a tag term score indicating a degree of relevance between the tag term and the object, wherein a tag term score for an object X and a term A is a function of a combination comprising a total number of different terms in a tag database storing the tags, a total number of tags present in the tag database, a frequency with which the term A is present in the tag database, a number of different terms with which the object X has been tagged, a total number of tags associated with the object X, and a number of different objects that have been tagged with the term A; determining for one or more objects a term relevance score comprising combining the tag term scores from the tag term object pairs for each tag associated with each object; and determining a relevance score for each of the multiple objects for the search query, wherein the relevance score is influenced by tags associated with objects as a result of user input. | 1. A computerized method of determining relevancies of multiple objects to a search query, comprising: associating one or more of the multiple objects with user-entered tags as a result of user input, thereby defining one or more corresponding tag-object pairs, wherein each tag comprises one or more tag terms, each tag term comprising text, and wherein each association of an object with a tag comprises a tag object pair; associating an object with each tag term from the one or more tag terms, thereby defining one or more corresponding tag term object pairs, wherein at least one of the one or more tags comprises a string of multiple terms entered by a user; determining for each tag term object pair a tag term score indicating a degree of relevance between the tag term and the object, wherein a tag term score for an object X and a term A is a function of a combination comprising a total number of different terms in a tag database storing the tags, a total number of tags present in the tag database, a frequency with which the term A is present in the tag database, a number of different terms with which the object X has been tagged, a total number of tags associated with the object X, and a number of different objects that have been tagged with the term A; determining for one or more objects a term relevance score comprising combining the tag term scores from the tag term object pairs for each tag associated with each object; and determining a relevance score for each of the multiple objects for the search query, wherein the relevance score is influenced by tags associated with objects as a result of user input. 18. The method of claim 1 , wherein a tag crawler associates at least one of the multiple tags with at least one of the multiple objects. | 0.908667 |
9,021,553 | 28 | 29 | 28. The method of claim 18 , wherein said challenging step further comprises the step of challenging said user with a set of C=ƒ(Q, A, I(Q), S) challenge questions, where ƒ is a function applied on an initial set of questions Q, their corresponding answers A, the encoded information I(Q) and additional state information S. | 28. The method of claim 18 , wherein said challenging step further comprises the step of challenging said user with a set of C=ƒ(Q, A, I(Q), S) challenge questions, where ƒ is a function applied on an initial set of questions Q, their corresponding answers A, the encoded information I(Q) and additional state information S. 29. The method of claim 28 , wherein said function ƒ generates a random subset C of Q. | 0.963528 |
8,429,161 | 16 | 17 | 16. The system of claim 15 , wherein the instructions cause the data processing apparatus to perform operations further comprising: instantiating a device session for the user device; classifying the device session as an approved device session in response to receiving access approval from the verification service; and automatically providing the unfiltered content items to the user device for the duration of the device session. | 16. The system of claim 15 , wherein the instructions cause the data processing apparatus to perform operations further comprising: instantiating a device session for the user device; classifying the device session as an approved device session in response to receiving access approval from the verification service; and automatically providing the unfiltered content items to the user device for the duration of the device session. 17. The system of claim 16 , wherein instantiating a device session for the user device comprises verifying a user login to a user account from the user device. | 0.957128 |
10,121,216 | 4 | 5 | 4. The method of claim 1 , wherein the analytic result includes a table and a chart that summarize the segment of the legal data selected by the user for analysis. | 4. The method of claim 1 , wherein the analytic result includes a table and a chart that summarize the segment of the legal data selected by the user for analysis. 5. The method of claim 4 , wherein the chart is a line graph, a bar chart, a pie chart, a doughnut chart, or a histogram. | 0.971094 |
9,953,055 | 1 | 10 | 1. A method of optimizing content selection infrastructure, comprising: retrieving, by an entity engine executing on one or more processors of a data processing system, a search query report that includes 1) a plurality of queries corresponding to selected content items of a content campaign, and 2) a performance metric for each of the plurality of queries determined based on a performance of the selected content items of the content campaign; determining, by the entity engine using a database, an entity for each query of the plurality of queries, the entity having a unique identifier indicating a classification based on a domain, a type and a property that establishes a relationship to at least one other entity stored in the database; generating, by a cluster engine executing on the data processing system, using a clustering technique applied to the unique identifier indicating the classification of the entity for each query of the plurality of queries, a first subset of the plurality of queries and a second subset of the plurality of queries, wherein the plurality of queries are separated into the first subset and the second subset based on the classification indicated by the unique identifier of the entity for each query of the plurality of queries; generating, by the cluster engine based on the performance metric for each of the plurality of queries, a first performance metric for the first subset and a second performance metric for the second subset, the first performance metric different from the second performance metric; providing, for display via an interface, the first performance metric and the second performance metric; receiving, by the data processing system, based on the first performance metric, a selection of a semantic criterion associated with the first subset generated based on the classification indicated by the unique identifier of the entity for each query of the plurality of queries; and updating, by the data processing system, the content campaign to include the semantic criterion. | 1. A method of optimizing content selection infrastructure, comprising: retrieving, by an entity engine executing on one or more processors of a data processing system, a search query report that includes 1) a plurality of queries corresponding to selected content items of a content campaign, and 2) a performance metric for each of the plurality of queries determined based on a performance of the selected content items of the content campaign; determining, by the entity engine using a database, an entity for each query of the plurality of queries, the entity having a unique identifier indicating a classification based on a domain, a type and a property that establishes a relationship to at least one other entity stored in the database; generating, by a cluster engine executing on the data processing system, using a clustering technique applied to the unique identifier indicating the classification of the entity for each query of the plurality of queries, a first subset of the plurality of queries and a second subset of the plurality of queries, wherein the plurality of queries are separated into the first subset and the second subset based on the classification indicated by the unique identifier of the entity for each query of the plurality of queries; generating, by the cluster engine based on the performance metric for each of the plurality of queries, a first performance metric for the first subset and a second performance metric for the second subset, the first performance metric different from the second performance metric; providing, for display via an interface, the first performance metric and the second performance metric; receiving, by the data processing system, based on the first performance metric, a selection of a semantic criterion associated with the first subset generated based on the classification indicated by the unique identifier of the entity for each query of the plurality of queries; and updating, by the data processing system, the content campaign to include the semantic criterion. 10. The method of claim 1 , wherein the performance metric includes at least one of click through rate, conversion rate, cost per click, cost per conversion, or return on investment. | 0.808824 |
7,770,104 | 1 | 2 | 1. A method for telephone-based electronic communication, said method comprising: receiving an incoming telephone call from a user; allowing said user to enter login and password information using predetermined codes; verifying login and password information for said user to provide access to a menu of communication options; presenting a menu of communication options to said user including: interacting with an e-mail account; and browsing the internet; and allowing said user to select one of said communication options using a predetermined code, wherein said communication option of browsing the internet includes: accepting a document location from said user specified by at least one of a favorites menu and a user input; retrieving a text document including HTML tags specified by the document location; building a new text body based on the text document, wherein the new text body includes HTML document table text in accordance with a subscript tag and a superscript tag; and further comprising adding comma length pauses in accordance with at least one of: a list item tag, a hyperlink tag, a paragraph tag, a horizontal line tag, and a table element end tag in the HTML document; converting the new text body to speech; listing at least one link in the text document; accepting input from said user to designate one of said links as a selected link; and retrieving a second document specified by the selected link, wherein said communication option of interacting with an e-mail account includes: retrieving an e-mail from a mail account; listing the subject line and send name of said e-mail for said user; presenting the user with the option of sending one of several preselected replies by entering a code; and sending an e-mail reply selected by said user. | 1. A method for telephone-based electronic communication, said method comprising: receiving an incoming telephone call from a user; allowing said user to enter login and password information using predetermined codes; verifying login and password information for said user to provide access to a menu of communication options; presenting a menu of communication options to said user including: interacting with an e-mail account; and browsing the internet; and allowing said user to select one of said communication options using a predetermined code, wherein said communication option of browsing the internet includes: accepting a document location from said user specified by at least one of a favorites menu and a user input; retrieving a text document including HTML tags specified by the document location; building a new text body based on the text document, wherein the new text body includes HTML document table text in accordance with a subscript tag and a superscript tag; and further comprising adding comma length pauses in accordance with at least one of: a list item tag, a hyperlink tag, a paragraph tag, a horizontal line tag, and a table element end tag in the HTML document; converting the new text body to speech; listing at least one link in the text document; accepting input from said user to designate one of said links as a selected link; and retrieving a second document specified by the selected link, wherein said communication option of interacting with an e-mail account includes: retrieving an e-mail from a mail account; listing the subject line and send name of said e-mail for said user; presenting the user with the option of sending one of several preselected replies by entering a code; and sending an e-mail reply selected by said user. 2. A method according to claim 1 , wherein the text document is a Hypertext Markup Language (HTML) document. | 0.914286 |
7,496,834 | 34 | 37 | 34. A method implemented by an apparatus for replying to a request for updating a previously supplied electronic document related to a schedule of broadcasting a plurality of television broadcast programs in a program broadcast system, wherein said previously supplied electronic document is stored in a client of the program broadcasting system and has a hierarchical structure based on a prescribed syntax, the hierarchical structure including an upper fragment and a plurality of lower fragments located below the upper fragment in the hierarchical structure to describe, for each of the scheduled television broadcast programs, a program identifier, a title, broadcast information and corresponding program content information, the method comprising: supplying said client with an update document from a provider of the program broadcasting system, the update document having a structure based on the prescribed syntax and including the upper fragment and an invalid element to delete a first lower fragment of said previously supplied electronic document at the client, wherein said invalid element indicates that said first lower fragment is invalid and should be deleted from the previously supplied electronic document, wherein the invalid first lower fragment is related to one of the scheduled television broadcast programs. | 34. A method implemented by an apparatus for replying to a request for updating a previously supplied electronic document related to a schedule of broadcasting a plurality of television broadcast programs in a program broadcast system, wherein said previously supplied electronic document is stored in a client of the program broadcasting system and has a hierarchical structure based on a prescribed syntax, the hierarchical structure including an upper fragment and a plurality of lower fragments located below the upper fragment in the hierarchical structure to describe, for each of the scheduled television broadcast programs, a program identifier, a title, broadcast information and corresponding program content information, the method comprising: supplying said client with an update document from a provider of the program broadcasting system, the update document having a structure based on the prescribed syntax and including the upper fragment and an invalid element to delete a first lower fragment of said previously supplied electronic document at the client, wherein said invalid element indicates that said first lower fragment is invalid and should be deleted from the previously supplied electronic document, wherein the invalid first lower fragment is related to one of the scheduled television broadcast programs. 37. The method of claim 34 , wherein said invalid first lower fragment is indicated to be invalid by an invalid attribute. | 0.883142 |
8,156,508 | 1 | 9 | 1. A method for runtime execution of one or more tasks defined in a workflow process language, the method comprising: at runtime: obtaining a description of the one or more tasks from a process ontology (PO), the process ontology (PO) defining a hierarchical taxonomy of executable tasks, each task referring to at least one frame of a hierarchical frame taxonomy of the process ontology (PO); identifying at least one task parameter as described in the frame description to which the task refers; resolving the value of the at least one task parameter, wherein said resolving comprises determining the value of the at least one task parameter; selecting a most specific applicable version of the task from a plurality of versions of the task contained in the task taxonomy of the process ontology (PO) based on the resolved value of the at least one task parameter; executing the most specific applicable version of the task; and storing results of said executing in a memory, wherein the results are usable for managing a process. | 1. A method for runtime execution of one or more tasks defined in a workflow process language, the method comprising: at runtime: obtaining a description of the one or more tasks from a process ontology (PO), the process ontology (PO) defining a hierarchical taxonomy of executable tasks, each task referring to at least one frame of a hierarchical frame taxonomy of the process ontology (PO); identifying at least one task parameter as described in the frame description to which the task refers; resolving the value of the at least one task parameter, wherein said resolving comprises determining the value of the at least one task parameter; selecting a most specific applicable version of the task from a plurality of versions of the task contained in the task taxonomy of the process ontology (PO) based on the resolved value of the at least one task parameter; executing the most specific applicable version of the task; and storing results of said executing in a memory, wherein the results are usable for managing a process. 9. The method of claim 1 , wherein the description of each task comprises attributes defining the frame it refers to, one or more input parameters, one or more output parameters and a reference to an implementation of the task. | 0.608621 |
8,463,795 | 12 | 19 | 12. A computer program product comprising a non-transitory computer-readable storage medium containing computer program code for generating an aggregated social feed, the code for: receiving a feed from each of a plurality of social networking systems, each feed comprising a plurality of content items personalized for a user based on the user's social connections in the social networking system; determining a grouping criteria based on content in the plurality of content items; forming a group including a plurality of content items satisfying the grouping criteria; scoring the content items from the plurality of feeds based on one or more relevance factors, wherein each content item is scored by: assigning one or more of the relevance factors to the content item, weighting the assigned relevance factors based on a target velocity of the aggregated social feed, the target velocity representing a predetermined number of content items received from the plurality of social networking system feeds to be included in the aggregated social feed, wherein the weighting is applied to achieve the target velocity for the aggregated social feed, and calculating a composite score based on the weighted relevance factors for the content item; selecting one or more of the scored content items having a composite score that meets a relevance threshold; and sending the selected items in the aggregated social feed for display in a content region of a page. | 12. A computer program product comprising a non-transitory computer-readable storage medium containing computer program code for generating an aggregated social feed, the code for: receiving a feed from each of a plurality of social networking systems, each feed comprising a plurality of content items personalized for a user based on the user's social connections in the social networking system; determining a grouping criteria based on content in the plurality of content items; forming a group including a plurality of content items satisfying the grouping criteria; scoring the content items from the plurality of feeds based on one or more relevance factors, wherein each content item is scored by: assigning one or more of the relevance factors to the content item, weighting the assigned relevance factors based on a target velocity of the aggregated social feed, the target velocity representing a predetermined number of content items received from the plurality of social networking system feeds to be included in the aggregated social feed, wherein the weighting is applied to achieve the target velocity for the aggregated social feed, and calculating a composite score based on the weighted relevance factors for the content item; selecting one or more of the scored content items having a composite score that meets a relevance threshold; and sending the selected items in the aggregated social feed for display in a content region of a page. 19. The computer program product of claim 12 , wherein a relevance factor is based on an indication of popularity associated with the content item. | 0.773148 |
9,953,027 | 15 | 18 | 15. A computer program product for generating paraphrases, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to: receive a plurality of bidirectional disjunctive logical forms, wherein the plurality of bidirectional disjunctive logical forms includes two directional disjunctions of differences between a first logical form of a first sentence and a second logical form of a second sentence; realize the plurality of bidirectional disjunctive logical forms to generate a first plurality of paraphrases of the first and second sentences; determine a first score for a third paraphrase of the first paraphrases; determine a second score for a fourth paraphrase of the first paraphrases, wherein the first score is higher than the second score based in part on a first syntactic variation between the third paraphrase and the first sentence and the second sentence being greater than a second syntactic variation between the fourth paraphrase and the first sentence and the second sentence; and prune the first paraphrases to generate second paraphrases, wherein the first paraphrases are pruned based on the first score and the second score such that the third paraphrase is included in the second paraphrases and the fourth paraphrase is not included in the second paraphrases based on the first score being higher than the second score. | 15. A computer program product for generating paraphrases, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to: receive a plurality of bidirectional disjunctive logical forms, wherein the plurality of bidirectional disjunctive logical forms includes two directional disjunctions of differences between a first logical form of a first sentence and a second logical form of a second sentence; realize the plurality of bidirectional disjunctive logical forms to generate a first plurality of paraphrases of the first and second sentences; determine a first score for a third paraphrase of the first paraphrases; determine a second score for a fourth paraphrase of the first paraphrases, wherein the first score is higher than the second score based in part on a first syntactic variation between the third paraphrase and the first sentence and the second sentence being greater than a second syntactic variation between the fourth paraphrase and the first sentence and the second sentence; and prune the first paraphrases to generate second paraphrases, wherein the first paraphrases are pruned based on the first score and the second score such that the third paraphrase is included in the second paraphrases and the fourth paraphrase is not included in the second paraphrases based on the first score being higher than the second score. 18. The computer program product of claim 15 , wherein the program instructions are further executable by the computer to cause the computer to: convert the first sentence into the first logical form by dependency parsing the first sentence to identify parts of speech of the first sentence thereby generating a first parsed representation of the first sentence; and convert the second sentence into the second logical form by dependency parsing the second sentence to identify parts of speech of the second sentence thereby generating a second parsed representation of the second sentence. | 0.500846 |
8,635,593 | 9 | 10 | 9. A computing system, comprising: a processor; a system memory coupled to said processor; wherein the system memory stores an integrated development environment (IDE) and a dynamic autocompletion tool, when executed by the processor, the IDE provides a script editor, when executed by the processor, the dynamic autocompletion tool analyzes real-time content of a user application being executed to populate an autocompletion list for use with the script editor. | 9. A computing system, comprising: a processor; a system memory coupled to said processor; wherein the system memory stores an integrated development environment (IDE) and a dynamic autocompletion tool, when executed by the processor, the IDE provides a script editor, when executed by the processor, the dynamic autocompletion tool analyzes real-time content of a user application being executed to populate an autocompletion list for use with the script editor. 10. The computing system of claim 9 wherein the IDE comprises an automated functional testing tool (AFTT). | 0.794574 |
9,594,828 | 1 | 3 | 1. A computer-implemented method performed by one or more computing devices, comprising: transmitting a pilot query to an unstructured data store that stores records in JSON-based format; responsive to transmitting the pilot query, receiving a plurality of records generated by execution of the pilot query against the unstructured data store, each record including one or more pairs of field names and values in JSON-based format; automatically identifying field names and data types from the pairs in the plurality of records generated by execution of the pilot query against the unstructured data store that stores records in JSON-based format and defining a first set of fields that corresponds to the identified field names and data types; receiving, at a query converter, a structured query whose portions all correspond to a structured query language; converting, by the query converter, the structured query into an unstructured query in an unstructured query language associated with searching the records in the unstructured data store, the unstructured query referencing at least one field in the first set of fields; and transmitting an instruction to the unstructured data store requesting that the unstructured data store execute the unstructured query against the records. | 1. A computer-implemented method performed by one or more computing devices, comprising: transmitting a pilot query to an unstructured data store that stores records in JSON-based format; responsive to transmitting the pilot query, receiving a plurality of records generated by execution of the pilot query against the unstructured data store, each record including one or more pairs of field names and values in JSON-based format; automatically identifying field names and data types from the pairs in the plurality of records generated by execution of the pilot query against the unstructured data store that stores records in JSON-based format and defining a first set of fields that corresponds to the identified field names and data types; receiving, at a query converter, a structured query whose portions all correspond to a structured query language; converting, by the query converter, the structured query into an unstructured query in an unstructured query language associated with searching the records in the unstructured data store, the unstructured query referencing at least one field in the first set of fields; and transmitting an instruction to the unstructured data store requesting that the unstructured data store execute the unstructured query against the records. 3. The computer-implemented method of claim 1 , wherein the pilot query is transmitted upon receiving the structured query. | 0.894148 |
7,516,397 | 5 | 6 | 5. The method according to claim 4 , wherein said location-specific context for each hyperlink comprises text extracted from set a of sibling nodes and ancestor nodes of at least one of a respective anchor text within said DOM tree. | 5. The method according to claim 4 , wherein said location-specific context for each hyperlink comprises text extracted from set a of sibling nodes and ancestor nodes of at least one of a respective anchor text within said DOM tree. 6. The method according to claim 5 , wherein said location-specific context comprises text extracted from previous sibling nodes of each anchor text and text extracted from said ancestor nodes of said anchor text and from previous siblings of said ancestor nodes within said DOM tree. | 0.911582 |
6,122,628 | 47 | 48 | 47. The program storage device of claim 26, wherein the data is stored in a database, further comprising the steps of: reducing a dimensionality of the database and generating dimensionality reduction information associated with the database; and storing the dimensionality reduction information associated with the database; wherein said partitioning step is responsive to said reducing step. | 47. The program storage device of claim 26, wherein the data is stored in a database, further comprising the steps of: reducing a dimensionality of the database and generating dimensionality reduction information associated with the database; and storing the dimensionality reduction information associated with the database; wherein said partitioning step is responsive to said reducing step. 48. The program storage device of claim 47, for performing an exact search, comprising the steps of: reducing the dimensionality of specified data, based on the dimensionality reduction information for the database; associating reduced dimensionality specified data to one of the clusters, based on the clustering information, in response to said reducing; reducing a dimensionality of the specified data to that of a reduced dimensionality cluster defined by an associated cluster, based on dimensionality reduction information for the associated cluster; and searching for a matching reduced dimensionality cluster, based on a reduced dimensionality version the specified data. | 0.86349 |
8,666,931 | 11 | 12 | 11. A method for encoding identifiers for source states in a state transition table, comprising: constructing a space reduction graph from the deterministic finite automaton, where vertices of the graph represent a distinct state of the automaton and weight assigned to each edge of the graph is a number of common transitions between two connected states; trimming away edges in the graph having a weight below a predefined threshold; computing a deferment forest by finding a maximum weight spanning forest for the space reduction graph; assigning identifiers for source states and destination states for states of the deferment forest by constructing an assignment tree by adding a virtual root node whose children are root nodes of all deferment trees comprising the deferment forest; assigning nonzero binary identifiers to each node in the assignment tree such that all siblings have the same identifier; setting source state identifiers for each node in the assignment tree such that a source state identifier of a given node is set to a concatenation of the binary identifiers assigned to the given node and its parent nodes; sizing source state identifiers for each node in the assignment tree to equate in size to longest source state identifier from amongst the nodes; and setting destination state identifiers for each node in the assignment tree such that a destination state identifier of a given node is set to corresponding source state identifier for the given node. | 11. A method for encoding identifiers for source states in a state transition table, comprising: constructing a space reduction graph from the deterministic finite automaton, where vertices of the graph represent a distinct state of the automaton and weight assigned to each edge of the graph is a number of common transitions between two connected states; trimming away edges in the graph having a weight below a predefined threshold; computing a deferment forest by finding a maximum weight spanning forest for the space reduction graph; assigning identifiers for source states and destination states for states of the deferment forest by constructing an assignment tree by adding a virtual root node whose children are root nodes of all deferment trees comprising the deferment forest; assigning nonzero binary identifiers to each node in the assignment tree such that all siblings have the same identifier; setting source state identifiers for each node in the assignment tree such that a source state identifier of a given node is set to a concatenation of the binary identifiers assigned to the given node and its parent nodes; sizing source state identifiers for each node in the assignment tree to equate in size to longest source state identifier from amongst the nodes; and setting destination state identifiers for each node in the assignment tree such that a destination state identifier of a given node is set to corresponding source state identifier for the given node. 12. The method of claim 11 further comprises receiving a set of regular expressions that specify data elements to be extracted from data packets; and constructing the deterministic finite automaton from the set of regular expressions. | 0.887066 |
9,514,746 | 8 | 9 | 8. The system of claim 1 , wherein said controller generates at least one speech command based on an interpretation of at least a portion of the audio input. | 8. The system of claim 1 , wherein said controller generates at least one speech command based on an interpretation of at least a portion of the audio input. 9. The system of claim 8 , wherein the controller sends the at least one speech command to a device operable by the at least one speech command. | 0.954774 |
8,209,241 | 11 | 20 | 11. A system residing on a client computing device comprising computer code that, when executed by the client computing device, causes the client computing device to perform a method for illustrating locations of available tickets in an event venue, the method comprising: presenting, by a web browser, a filter module for allowing a user to perform a search of tickets listed for sale by a ticket service hosted by a web site; accepting, at the filter module, event criteria for at least one ticket and at least one event; accepting, at the filter module, price criteria for the at least one ticket and the at least one event; sending the request for filtering tickets by criteria to the ticket service; receiving, from the ticket service, data representing a filtered ticket set meeting the event criteria and the price criteria from the ticket service; displaying a ticket listing corresponding to tickets of the filtered ticket set located in a plurality of sections of an event venue; displaying, by the web browser, an interactive graphics-based event venue map for the event venue illustrating locations of sections having tickets of the filtered ticket set; accepting, at the interactive graphics-based event venue map, a particular section of interest in response to the user selecting the particular section from the interactive graphics-based event venue map; accepting, at the interactive graphics-based event venue map, a particular section of interest; and displaying ticket information in a web browsing language corresponding to the tickets of the filtered ticket set located in the particular section of interest as an overlay on the particular section of interest on the interactive graphics-based event venue map. | 11. A system residing on a client computing device comprising computer code that, when executed by the client computing device, causes the client computing device to perform a method for illustrating locations of available tickets in an event venue, the method comprising: presenting, by a web browser, a filter module for allowing a user to perform a search of tickets listed for sale by a ticket service hosted by a web site; accepting, at the filter module, event criteria for at least one ticket and at least one event; accepting, at the filter module, price criteria for the at least one ticket and the at least one event; sending the request for filtering tickets by criteria to the ticket service; receiving, from the ticket service, data representing a filtered ticket set meeting the event criteria and the price criteria from the ticket service; displaying a ticket listing corresponding to tickets of the filtered ticket set located in a plurality of sections of an event venue; displaying, by the web browser, an interactive graphics-based event venue map for the event venue illustrating locations of sections having tickets of the filtered ticket set; accepting, at the interactive graphics-based event venue map, a particular section of interest in response to the user selecting the particular section from the interactive graphics-based event venue map; accepting, at the interactive graphics-based event venue map, a particular section of interest; and displaying ticket information in a web browsing language corresponding to the tickets of the filtered ticket set located in the particular section of interest as an overlay on the particular section of interest on the interactive graphics-based event venue map. 20. The system of claim 11 , wherein: the interactive graphics-based event venue map is a FLASH-based event venue map; and the web browsing language is HTML. | 0.781337 |
8,688,721 | 1 | 2 | 1. A method of determining a flush point, comprising: receiving, with a computer including a processor, a query, wherein the query is formed by one or more paths, and wherein each path includes one or more steps, wherein a query structure represents the query, wherein the query structure includes query nodes, and wherein each of the query nodes is flagged with a FOR binding or a LET binding; receiving a hierarchical document including one or more document nodes; determining whether there is a parent axis in the query; in response to determining that there is no parent axis in the query, identifying a first query node in the query structure by traversing the query structure up from one or more extraction nodes and stopping at a first one of the query node flagged with the FOR binding from among the query nodes or a root node of the query structure; flagging the first query node as a flush candidate; identifying a second query node by traversing the query structure from the root node of the query structure downwards until finding the query node that is flagged with a FlushCandidate identifier or the query node that has more than one child from among the query nodes; and flagging the second query node as the flush point. | 1. A method of determining a flush point, comprising: receiving, with a computer including a processor, a query, wherein the query is formed by one or more paths, and wherein each path includes one or more steps, wherein a query structure represents the query, wherein the query structure includes query nodes, and wherein each of the query nodes is flagged with a FOR binding or a LET binding; receiving a hierarchical document including one or more document nodes; determining whether there is a parent axis in the query; in response to determining that there is no parent axis in the query, identifying a first query node in the query structure by traversing the query structure up from one or more extraction nodes and stopping at a first one of the query node flagged with the FOR binding from among the query nodes or a root node of the query structure; flagging the first query node as a flush candidate; identifying a second query node by traversing the query structure from the root node of the query structure downwards until finding the query node that is flagged with a FlushCandidate identifier or the query node that has more than one child from among the query nodes; and flagging the second query node as the flush point. 2. The method of claim 1 , further comprising: determining whether there is at least one recursive node in the hierarchical document detected during traversal of the hierarchical document that is described by the query node in the query structure flagged with the FOR binding from among the query nodes while using a descendant axis; and in response to determining that there is at least one recursive node, setting an outermost recursive node to be a new flush point. | 0.663309 |
6,134,532 | 1 | 7 | 1. A computerized system for associating an observed behavior with items, comprising: a converter capable of converting the observed behavior to a behavior vector; a profile adapter capable of modifying a profile vector with the behavior vector; and a comparater capable of comparing the modified profile vector to a plurality of entity vectors, the entity vectors indicative of the items, so as to identify at least one entity vector closely associated with the observed behavior. | 1. A computerized system for associating an observed behavior with items, comprising: a converter capable of converting the observed behavior to a behavior vector; a profile adapter capable of modifying a profile vector with the behavior vector; and a comparater capable of comparing the modified profile vector to a plurality of entity vectors, the entity vectors indicative of the items, so as to identify at least one entity vector closely associated with the observed behavior. 7. The computerized system as defined in claim 1, wherein the profile adapter modifies the profile vector based upon at least one parameter selected from the group consisting of: a threshold by which a behavior vector will be used instead of the entity vector, a learning rate for a profile update, a leaning rate for an entity update, an update rate for a query universe estimate of a mean, an update for a profile universe update of a mean, a forgetting factor for a set of profile vectors, a forgetting factor for a set of entity vectors, a mean of a set of entity vectors, a mean of a set profile vectors, and a mean of a set of behavior vectors. | 0.678854 |
8,365,072 | 13 | 14 | 13. The computer readable medium of claim 11 , wherein the particular set of constraints comprises a requirement that bounds for each particular primitive element in the sub-group intersect collective bounds for all primitive elements in the sub-group previous to the particular primitive element in the drawing order. | 13. The computer readable medium of claim 11 , wherein the particular set of constraints comprises a requirement that bounds for each particular primitive element in the sub-group intersect collective bounds for all primitive elements in the sub-group previous to the particular primitive element in the drawing order. 14. The computer readable medium of claim 13 , wherein the bounds for each primitive element is a smallest upright bounding box that includes the primitive element. | 0.944293 |
10,049,380 | 1 | 2 | 1. A system comprising: a hardware processor; and a storage device storing instructions that, when executed by the hardware processor, cause the hardware processor to: receive, for each of a plurality of publications, a set of comments provided for the publication; receive training data that specifies controversial terms; for each comment included in each set of comments, identify i) at least one controversial term included in the comment, or ii) at least one non-controversial term included in the comment, the identification being based on the training data; generate a controversy classifier that i) accepts, as input, a particular set of comments for a particular publication and ii) produces, as output and for each comment in the particular set of comments, data indicating a measure of controversy for the particular comment; identify a second set of comments for a second publication, the second set of comments selected from a plurality of comments associated with the second publication based upon time of entry of each comment in the second set of comments after publication of the second publication; provide each comment in the second set of comments to the controversy classifier as input; determine, using output from the controversy classifier, that each comment in the second set of comments is controversial or non-controversial; and determine, based on the determinations made for each comment in the second set of comments, that the second publication is controversial or non-controversial. | 1. A system comprising: a hardware processor; and a storage device storing instructions that, when executed by the hardware processor, cause the hardware processor to: receive, for each of a plurality of publications, a set of comments provided for the publication; receive training data that specifies controversial terms; for each comment included in each set of comments, identify i) at least one controversial term included in the comment, or ii) at least one non-controversial term included in the comment, the identification being based on the training data; generate a controversy classifier that i) accepts, as input, a particular set of comments for a particular publication and ii) produces, as output and for each comment in the particular set of comments, data indicating a measure of controversy for the particular comment; identify a second set of comments for a second publication, the second set of comments selected from a plurality of comments associated with the second publication based upon time of entry of each comment in the second set of comments after publication of the second publication; provide each comment in the second set of comments to the controversy classifier as input; determine, using output from the controversy classifier, that each comment in the second set of comments is controversial or non-controversial; and determine, based on the determinations made for each comment in the second set of comments, that the second publication is controversial or non-controversial. 2. The system of claim 1 , wherein the instructions further cause the hardware processor to: extract content-based features from the set of comments. | 0.863051 |
9,781,392 | 1 | 5 | 1. An apparatus comprising: detection/reception logic to receive one or more media items relating to an event; event extraction engine to capture a theme from the one or more media items, wherein the theme is captured based on at least one of activities, textual content, and scenes associated with the event; story and scene segmentation engine to form a plurality of story elements to generate a story relating to the event, wherein the plurality of story elements are formed based on at least one of one or more characters, the theme associated with the event, and one or more emotions associated with the one or more characters, wherein the story is presented, via one or more display devices, to one or more users having access to the one or more display devices; character resolution engine to extract the one or more characters from the one or more media items, wherein the one or more characters having assigned one or more roles representing one or more individuals associated with the event; emotion understanding engine to determine the one or more emotions from the one or more media items, wherein the one or more emotions are determined based on one or more expressions associated with the one or more characters; feedback and generation/presentation logic to generate the story based on the plurality of story elements, wherein the feedback and generation/presentation logic is further to facilitate posting of the story at one or more websites; named entity resolution logic to extract, from the one or more media items, one or more identities or the one or more roles associated with the one or more characters wherein the one or more identities are extracted based on at least one of comments or descriptions associated with the one or more characters such that an identity associated with a character is detected based on at least one of a role, a comment, and a description associated with the character, wherein the identity refers to one or more of a parent, a child, a relative, a friend, a neighbor, a teammate, a coach, a boss, an employee, and a stranger; co-reference resolution logic to resolve one or more references relating to the one or more characters, wherein the one or more references include one or more pronouns associated with the one or more characters; contextual discovery logic to discover one or more locations of the event, wherein the one or more locations are discovered based on global positioning system (GPS) coordinates relating to one or more computing devices accessible to the one or more characters; and role assignment logic to determine the one or more roles associated with the one or more characters, wherein the role assignment logic is further to assign a role to a character of the one or more characters based on a comment regarding the character, wherein the one or more roles further refer to one or more relationships between two or more characters, wherein the one or more relationships include one or more of parent-child, brother-sister, aunt-nephew, grandfather-grandson, teammate-teammate, coach-player, neighbor-neighbor, boss-subordinate, owner-employee, partner-partner, and stranger-stranger. | 1. An apparatus comprising: detection/reception logic to receive one or more media items relating to an event; event extraction engine to capture a theme from the one or more media items, wherein the theme is captured based on at least one of activities, textual content, and scenes associated with the event; story and scene segmentation engine to form a plurality of story elements to generate a story relating to the event, wherein the plurality of story elements are formed based on at least one of one or more characters, the theme associated with the event, and one or more emotions associated with the one or more characters, wherein the story is presented, via one or more display devices, to one or more users having access to the one or more display devices; character resolution engine to extract the one or more characters from the one or more media items, wherein the one or more characters having assigned one or more roles representing one or more individuals associated with the event; emotion understanding engine to determine the one or more emotions from the one or more media items, wherein the one or more emotions are determined based on one or more expressions associated with the one or more characters; feedback and generation/presentation logic to generate the story based on the plurality of story elements, wherein the feedback and generation/presentation logic is further to facilitate posting of the story at one or more websites; named entity resolution logic to extract, from the one or more media items, one or more identities or the one or more roles associated with the one or more characters wherein the one or more identities are extracted based on at least one of comments or descriptions associated with the one or more characters such that an identity associated with a character is detected based on at least one of a role, a comment, and a description associated with the character, wherein the identity refers to one or more of a parent, a child, a relative, a friend, a neighbor, a teammate, a coach, a boss, an employee, and a stranger; co-reference resolution logic to resolve one or more references relating to the one or more characters, wherein the one or more references include one or more pronouns associated with the one or more characters; contextual discovery logic to discover one or more locations of the event, wherein the one or more locations are discovered based on global positioning system (GPS) coordinates relating to one or more computing devices accessible to the one or more characters; and role assignment logic to determine the one or more roles associated with the one or more characters, wherein the role assignment logic is further to assign a role to a character of the one or more characters based on a comment regarding the character, wherein the one or more roles further refer to one or more relationships between two or more characters, wherein the one or more relationships include one or more of parent-child, brother-sister, aunt-nephew, grandfather-grandson, teammate-teammate, coach-player, neighbor-neighbor, boss-subordinate, owner-employee, partner-partner, and stranger-stranger. 5. The apparatus of claim 1 , wherein the event extraction engine further comprises: location resolution logic to extract location-related information relating to the one or more locations discovered based on the GPS coordinates, wherein the location-related information includes at least one of a local scene, a local culture, a local climate, a local language, a local time, and a local history, wherein the location-related information includes indigenous events or global events being performed locally such that the local scene includes a farmer's market, a garage sale, a beer festival, a new year's day celebration, a soccer world cup, and a royal coronation, wherein the theme is formed based on the location-related information; temporal resolution logic to extract time-related information relating to the one or more locations; topic modeling logic to statistically analyze words obtained from each of the one or more media items, wherein the theme is confirmed based on the statistically analyzed words; and scene understanding logic to analyze visible items in the one or more media items, wherein the visible items include at least one of objects, clothing, other individuals, animals, vegetation, weather, foregrounds, and backgrounds in each of the media items, wherein the backgrounds include one or more of color schemes, weather patterns, wall shades, and moods in imagery based on general scenery or photographic techniques, wherein the visible items are analyzed to determine a scene from the theme, wherein the scene understanding logic is further to analyze metadata associated with the visible items or the one or more characters in the one or more media items, the metadata being captured in real-time indicates relevant information about each of the visible items, the one or more characters, and the one or more roles or the one or more identities associated with the one or more characters. | 0.615014 |
7,856,375 | 1 | 13 | 1. A method for automatically preparing customized communication documents for a plurality of consumer entities, the method comprising the steps of: using data from a first electronic data file containing financial product and/or financial service data for the customized communications, which financial product and/or financial service data includes a plurality of separate descriptions, characteristics and/or identifications for at least a first financial product and/or financial service; using data from a second electronic data file containing customer information for at least certain of the plurality of consumer entities, said customer information including customer related data in addition to, but not excluding, any one or more of customer name, customer address and customer account information obtained for said certain of the plurality of consumer entities; performing an automated composition process using a computing system configured to access said first data file and second data file to compose an electronic document file representing a customized communication document for at least one of said certain of the plurality of the consumer entities, said customized communication document comprising information relating to an offering for one or more financial products or services; wherein at least some content included in said customized communication document is customized content generated by said computing system for said electronic document file which includes variable data specifically for a consumer entity automatically derived and/or calculated from said first electronic data file and/or said second electronic data file during said automated composition process for said electronic document file and said consumer entity; delivering said customized communication documents based on said electronic document file to at least one of said certain of the plurality of consumer entities. | 1. A method for automatically preparing customized communication documents for a plurality of consumer entities, the method comprising the steps of: using data from a first electronic data file containing financial product and/or financial service data for the customized communications, which financial product and/or financial service data includes a plurality of separate descriptions, characteristics and/or identifications for at least a first financial product and/or financial service; using data from a second electronic data file containing customer information for at least certain of the plurality of consumer entities, said customer information including customer related data in addition to, but not excluding, any one or more of customer name, customer address and customer account information obtained for said certain of the plurality of consumer entities; performing an automated composition process using a computing system configured to access said first data file and second data file to compose an electronic document file representing a customized communication document for at least one of said certain of the plurality of the consumer entities, said customized communication document comprising information relating to an offering for one or more financial products or services; wherein at least some content included in said customized communication document is customized content generated by said computing system for said electronic document file which includes variable data specifically for a consumer entity automatically derived and/or calculated from said first electronic data file and/or said second electronic data file during said automated composition process for said electronic document file and said consumer entity; delivering said customized communication documents based on said electronic document file to at least one of said certain of the plurality of consumer entities. 13. The method of claim 1 , wherein said variable data included in said customized content comprises at least one of textual components, alphanumeric components, and graphical components is varied between consumer entities. | 0.79428 |
9,374,225 | 18 | 21 | 18. A system comprising: at least one processor device; at least one memory element; and a registration module comprising code executable by the at least one processor device to: monitor security of a plurality of registered digital documents in a system, the monitoring including determining whether signatures associated with the registered digital documents are included in data propagating in network traffic of the system; detect a particular signature of a particular document in the plurality of registered digital documents from the data propagating in the network; determine, based at least in part on the detecting, that detection of the particular signature exceeds a threshold detection rate for registered digital documents in the system, wherein the threshold detection rate comprises a threshold percentage of digital documents detected in the network traffic over a time period; remove the particular signature from a signature database based on determining that detection of the particular signature exceeds the threshold detection rate, wherein the signature database includes the signatures of the plurality of registered digital documents; and perform a security action to protect access to the registered digital documents, wherein the security action is not performed on the particular document based on removal of the particular signature from the signature database. | 18. A system comprising: at least one processor device; at least one memory element; and a registration module comprising code executable by the at least one processor device to: monitor security of a plurality of registered digital documents in a system, the monitoring including determining whether signatures associated with the registered digital documents are included in data propagating in network traffic of the system; detect a particular signature of a particular document in the plurality of registered digital documents from the data propagating in the network; determine, based at least in part on the detecting, that detection of the particular signature exceeds a threshold detection rate for registered digital documents in the system, wherein the threshold detection rate comprises a threshold percentage of digital documents detected in the network traffic over a time period; remove the particular signature from a signature database based on determining that detection of the particular signature exceeds the threshold detection rate, wherein the signature database includes the signatures of the plurality of registered digital documents; and perform a security action to protect access to the registered digital documents, wherein the security action is not performed on the particular document based on removal of the particular signature from the signature database. 21. The system of claim 18 , wherein the registration module is further to de-register documents in the plurality of registered digital document based on determining that a time interval associated with initial registration of the registered documents has expired. | 0.674074 |
9,489,451 | 18 | 19 | 18. A computer-implemented method for defining a structure for items to be identified in loosely-structured data, comprising: assigning a name to a composite data definition using a visual editor, where the visual editor is implemented by computer-executable instructions executed by a computer processor; selecting, via the visual editor, a first data item from a listing of data items, where the first data item has a common meaning for applications that use the first data item and includes one or more properties associated therewith; arranging, via the visual editor, the first data item in a layout for the composite data definition; creating an identification order list for the composite data definition, where the identification order list includes the first data item and specifies an order in which data items comprising the composite data definition are to be identified within the loosely-structured data; selecting, via the visual editor, a second data item from the listing of data items; arranging, via the visual editor, the second data item in relation to the first data item within the layout; adding the second data item to the identification order list, where the order of the data items in the identification order list is in accordance with the arrangement of the first data time in relation to the second data item in the layout; receiving input data; and parsing the input data to identify items therein using the layout and the identification order list of the composite data definition, where the data items in the layout are searched for in the order specified by the identification order list and the order specified in the identification order list differs from the arrangement of the data items in the layout of the composite data definition. | 18. A computer-implemented method for defining a structure for items to be identified in loosely-structured data, comprising: assigning a name to a composite data definition using a visual editor, where the visual editor is implemented by computer-executable instructions executed by a computer processor; selecting, via the visual editor, a first data item from a listing of data items, where the first data item has a common meaning for applications that use the first data item and includes one or more properties associated therewith; arranging, via the visual editor, the first data item in a layout for the composite data definition; creating an identification order list for the composite data definition, where the identification order list includes the first data item and specifies an order in which data items comprising the composite data definition are to be identified within the loosely-structured data; selecting, via the visual editor, a second data item from the listing of data items; arranging, via the visual editor, the second data item in relation to the first data item within the layout; adding the second data item to the identification order list, where the order of the data items in the identification order list is in accordance with the arrangement of the first data time in relation to the second data item in the layout; receiving input data; and parsing the input data to identify items therein using the layout and the identification order list of the composite data definition, where the data items in the layout are searched for in the order specified by the identification order list and the order specified in the identification order list differs from the arrangement of the data items in the layout of the composite data definition. 19. The method of claim 18 further comprises assigning a search direction for the first data item in a search domain, where the search direction is assigned in accordance with placement of the first data item in the layout. | 0.858142 |
8,898,701 | 1 | 2 | 1. A method comprising: categorizing, by a processor, a first set of attributes associated with a first list of objects, wherein each of the objects represents a video asset that is associated with one or more of the attributes of the first set; ranking, by the processor, the first set of attributes according to a criterion associated with one or more characteristics of the attributes, wherein the criterion specifies a frequency of occurrence of an attribute of the first set of attributes; presenting the first list of objects and associated attributes; receiving a first input indicating selection of at least one of the attributes of the first set; collapsing the first list of objects into a second list of objects consisting of a subset of the first list of objects, wherein the subset consists of the objects associated with the selected attributes; generating, by the processor, a second set of attributes based on the second list of objects, the second set of attributes comprising a non-selected attribute of the first set of attributes, wherein each of the attributes of the second set of attributes is associated with at least one object of the second list of objects; ranking, by the processor, the second set of attributes according to the criterion, wherein the criterion specifies a frequency of occurrence of an attribute of the second set of attributes; presenting the second list of objects and associated attributes in response to the first input; receiving a second input indicating selection of one of the objects in the second list; and retrieving the video asset corresponding to the one selected object, wherein the selection of the at least one of the attributes of the first set of attributes specifies a maximum and/or minimum value. | 1. A method comprising: categorizing, by a processor, a first set of attributes associated with a first list of objects, wherein each of the objects represents a video asset that is associated with one or more of the attributes of the first set; ranking, by the processor, the first set of attributes according to a criterion associated with one or more characteristics of the attributes, wherein the criterion specifies a frequency of occurrence of an attribute of the first set of attributes; presenting the first list of objects and associated attributes; receiving a first input indicating selection of at least one of the attributes of the first set; collapsing the first list of objects into a second list of objects consisting of a subset of the first list of objects, wherein the subset consists of the objects associated with the selected attributes; generating, by the processor, a second set of attributes based on the second list of objects, the second set of attributes comprising a non-selected attribute of the first set of attributes, wherein each of the attributes of the second set of attributes is associated with at least one object of the second list of objects; ranking, by the processor, the second set of attributes according to the criterion, wherein the criterion specifies a frequency of occurrence of an attribute of the second set of attributes; presenting the second list of objects and associated attributes in response to the first input; receiving a second input indicating selection of one of the objects in the second list; and retrieving the video asset corresponding to the one selected object, wherein the selection of the at least one of the attributes of the first set of attributes specifies a maximum and/or minimum value. 2. A method according to claim 1 , further comprising: receiving a metadata file including the first set of attributes, wherein the categorizing of the first set of attributes includes parsing the metadata. | 0.818021 |
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