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7,831,597 | 6 | 7 | 6. The method of claim 1 , wherein the second unit of text data is a query. | 6. The method of claim 1 , wherein the second unit of text data is a query. 7. The method of claim 6 , further comprising selecting as the first unit of text data a relevant document from the document collection based at least in part on the query. | 0.966115 |
7,873,642 | 1 | 8 | 1. A method, in a data processing system, for classifying media data, comprising: responsive to receiving input media data, classifying the input media data for later access based on classification; applying a plurality of classifiers in a hierarchical classification structure to the input media data; generating confidence scores for the plurality of classifiers in the hierarchical classification structure; modifying a confidence score automatically for a classifier in the hierarchical classification structure based on a relationship between the classifier and other classifiers in the hierarchical classification structure and the confidence scores of the other classifiers in the hierarchical classification structure by applying a confusion factor to the confidence score based on a correspondence between the confidence score and confidence scores of mutually exclusive classifiers in the hierarchical classification structure; generating a representation of the input media data based on the modified confidence score being higher than a predetermined threshold confidence score; and storing the generated representation of the input media data. | 1. A method, in a data processing system, for classifying media data, comprising: responsive to receiving input media data, classifying the input media data for later access based on classification; applying a plurality of classifiers in a hierarchical classification structure to the input media data; generating confidence scores for the plurality of classifiers in the hierarchical classification structure; modifying a confidence score automatically for a classifier in the hierarchical classification structure based on a relationship between the classifier and other classifiers in the hierarchical classification structure and the confidence scores of the other classifiers in the hierarchical classification structure by applying a confusion factor to the confidence score based on a correspondence between the confidence score and confidence scores of mutually exclusive classifiers in the hierarchical classification structure; generating a representation of the input media data based on the modified confidence score being higher than a predetermined threshold confidence score; and storing the generated representation of the input media data. 8. The method of claim 1 , wherein the confusion factor is a probability of misclassifying the input media data into a classifier in the plurality of classifiers. | 0.853791 |
8,406,384 | 11 | 17 | 11. A system for developing query tags for classification of user queries to a call routing application, the system comprising: a plurality of user query corpuses containing user queries from a plurality of call routing applications in a plurality of different vertical domains; a query tag selection module for accessing the user query corpuses to select a set of frequent user queries that appear in a plurality of different query corpuses in a plurality of different vertical domains to develop frequent query tags for semantic classification of the frequent user queries; and a query tag database for storing the frequent query tags; wherein the user queries and the query tags are in a first language, and the system further automatically translates the user queries into a second language and stores the translated user queries with the frequent query tags in a call routing database for a call routing application in the second language. | 11. A system for developing query tags for classification of user queries to a call routing application, the system comprising: a plurality of user query corpuses containing user queries from a plurality of call routing applications in a plurality of different vertical domains; a query tag selection module for accessing the user query corpuses to select a set of frequent user queries that appear in a plurality of different query corpuses in a plurality of different vertical domains to develop frequent query tags for semantic classification of the frequent user queries; and a query tag database for storing the frequent query tags; wherein the user queries and the query tags are in a first language, and the system further automatically translates the user queries into a second language and stores the translated user queries with the frequent query tags in a call routing database for a call routing application in the second language. 17. A system according to claim 11 , further comprising: a clustering algorithm module of a call steering application that uses the stored query tags. | 0.816626 |
4,007,548 | 1 | 9 | 1. In a method of teaching reading, the steps of 1. presenting the student with material to be read in an orthography consisting of: a. the words to be read in standard type; b. symbols representing the sounds of vowel phonemes and consonant digraphs appearing in the material proximately located to the phonemes and digraphs to assist in pronouncing the sounds, c. markings to designate combined letters forming a single sound, and d. numerical designations in directional sequence of each sound in each word, and 2. | 1. In a method of teaching reading, the steps of 1. presenting the student with material to be read in an orthography consisting of: a. the words to be read in standard type; b. symbols representing the sounds of vowel phonemes and consonant digraphs appearing in the material proximately located to the phonemes and digraphs to assist in pronouncing the sounds, c. markings to designate combined letters forming a single sound, and d. numerical designations in directional sequence of each sound in each word, and 2. 9. A method as in claim 1 wherein the orthography also includes symbols associated with consonant sounds. | 0.87069 |
10,007,674 | 5 | 7 | 5. One or more non-transitory computer-readable media storing a set of instructions for execution by one or more processors, the set of instructions configured for performing operations comprising: storing a first version of a first dataset that is derived from a first version of a second dataset based on a first execution of a first version of a driver program; storing a first build catalog entry comprising an identifier of the first version of the first dataset, an identifier of the first version of the second dataset, a first branch name, and an identifier of the first version of the driver program; storing a second version of the first dataset that is derived from a second version of the second dataset based on a second execution of the first version of the driver program; storing a second build catalog entry comprising an identifier of the second version of the first dataset, an identifier of the second version of the second dataset, a second branch name that is different from the first branch name, and an identifier of the first version of the driver program; storing a first transaction entry in a database, the first transaction entry comprising a first transaction commit identifier of the first version of the first dataset; wherein the first build catalog entry comprises the first transaction commit identifier; storing a second transaction entry in the database, the second transaction entry comprising a second transaction commit identifier of the first version of the second dataset; wherein the identifier of the first version of the second dataset in the first build catalog entry is the second transaction commit identifier; storing a third transaction entry in the database, the third transaction entry comprising a third transaction commit identifier of the second version of the second dataset; wherein the identifier of the second version of the second dataset in the second build catalog entry is the third transaction commit identifier; and causing display of a provenance graph in a graphical user interface based on the second build catalog entry, the provenance graph display including display of: a first node representing the second version of the first dataset, a second node representing the second version of the second dataset, and a first directed edge from the first node to the second node. | 5. One or more non-transitory computer-readable media storing a set of instructions for execution by one or more processors, the set of instructions configured for performing operations comprising: storing a first version of a first dataset that is derived from a first version of a second dataset based on a first execution of a first version of a driver program; storing a first build catalog entry comprising an identifier of the first version of the first dataset, an identifier of the first version of the second dataset, a first branch name, and an identifier of the first version of the driver program; storing a second version of the first dataset that is derived from a second version of the second dataset based on a second execution of the first version of the driver program; storing a second build catalog entry comprising an identifier of the second version of the first dataset, an identifier of the second version of the second dataset, a second branch name that is different from the first branch name, and an identifier of the first version of the driver program; storing a first transaction entry in a database, the first transaction entry comprising a first transaction commit identifier of the first version of the first dataset; wherein the first build catalog entry comprises the first transaction commit identifier; storing a second transaction entry in the database, the second transaction entry comprising a second transaction commit identifier of the first version of the second dataset; wherein the identifier of the first version of the second dataset in the first build catalog entry is the second transaction commit identifier; storing a third transaction entry in the database, the third transaction entry comprising a third transaction commit identifier of the second version of the second dataset; wherein the identifier of the second version of the second dataset in the second build catalog entry is the third transaction commit identifier; and causing display of a provenance graph in a graphical user interface based on the second build catalog entry, the provenance graph display including display of: a first node representing the second version of the first dataset, a second node representing the second version of the second dataset, and a first directed edge from the first node to the second node. 7. The one or more non-transitory computer-readable media of claim 5 , wherein the identifier of the first version of the first dataset is an identifier assigned to a commit of a transaction in context of which the first version of the first dataset is stored. | 0.604863 |
9,390,079 | 1 | 2 | 1. A computing system comprising: an electronic display configured to display items of textual information, the items of textual information including one or more headings; a microphone configured to receive audio input from a user of the computing system; one or more computer processors in communication with the electronic display and the microphone and configured to execute software instructions; and one or more storage devices in communication with the one or more computer processors and storing a rule set and software instructions, wherein the rule set includes selected text action rules, and wherein the software instructions are configured for execution by the one or more computer processors in order to cause the system to: display, on the electronic display, the items of textual information to the user; receive, from the user via the microphone, an audio input including at least a command and a heading identifier; in response to receiving the command and the heading identifier, determine, based on the rule set, a first item of textual information following a heading associated with the heading identifier, wherein the first item of textual information includes one or more subheadings; select, based on the rule set, the first item of textual information; and in response to determining, based on the selected text action rules, that the first item of textual information is to be deleted or replaced: determine the one or more subheadings and textual information associated with each of the one or more subheadings; and delete or replace the textual information associated with each of the one or more subheadings but not the one or more subheadings. | 1. A computing system comprising: an electronic display configured to display items of textual information, the items of textual information including one or more headings; a microphone configured to receive audio input from a user of the computing system; one or more computer processors in communication with the electronic display and the microphone and configured to execute software instructions; and one or more storage devices in communication with the one or more computer processors and storing a rule set and software instructions, wherein the rule set includes selected text action rules, and wherein the software instructions are configured for execution by the one or more computer processors in order to cause the system to: display, on the electronic display, the items of textual information to the user; receive, from the user via the microphone, an audio input including at least a command and a heading identifier; in response to receiving the command and the heading identifier, determine, based on the rule set, a first item of textual information following a heading associated with the heading identifier, wherein the first item of textual information includes one or more subheadings; select, based on the rule set, the first item of textual information; and in response to determining, based on the selected text action rules, that the first item of textual information is to be deleted or replaced: determine the one or more subheadings and textual information associated with each of the one or more subheadings; and delete or replace the textual information associated with each of the one or more subheadings but not the one or more subheadings. 2. The computing system of claim 1 , wherein the rule set further includes heading identification rules, and wherein the heading associated with the heading identifier is determined based on the heading identification rules. | 0.714286 |
7,673,230 | 2 | 4 | 2. The method of claim 1 , wherein visually identifying the single hyperlink in the document comprises drawing a focus shape around the visual representation of the hyperlink. | 2. The method of claim 1 , wherein visually identifying the single hyperlink in the document comprises drawing a focus shape around the visual representation of the hyperlink. 4. The method of claim 2 , wherein the focus shape is a circle. | 0.970994 |
7,818,713 | 23 | 24 | 23. The process according to claim 22 , wherein said determining step further comprises the steps of: mapping said one or more specifications to said each attribute of said defined set of attributes inputted to form relationship mappings; and storing said relationship mappings formed in said repository. | 23. The process according to claim 22 , wherein said determining step further comprises the steps of: mapping said one or more specifications to said each attribute of said defined set of attributes inputted to form relationship mappings; and storing said relationship mappings formed in said repository. 24. The process according to claim 23 , wherein said defining affinities step further comprises the steps of: establishing affinity values for said affinities defined based on said domain context defined and said relationship requirement patterns determined; and storing said affinity values established in said repository. | 0.910278 |
9,940,365 | 6 | 9 | 6. The computer system of claim 1 , further comprising for each candidate table the hardware processor executing the instructions stored in the system memory to: access a set of static features for the candidate table; and derive a set of ranking features for the candidate table from the set of static features and the one or more dynamic features; and wherein the hardware processor executing the instructions stored in the system memory to generate a ranking score for the candidate table comprises the hardware processor executing the instructions stored in the system memory to generate a ranking score for the candidate table from the set of ranking features for the candidate table. | 6. The computer system of claim 1 , further comprising for each candidate table the hardware processor executing the instructions stored in the system memory to: access a set of static features for the candidate table; and derive a set of ranking features for the candidate table from the set of static features and the one or more dynamic features; and wherein the hardware processor executing the instructions stored in the system memory to generate a ranking score for the candidate table comprises the hardware processor executing the instructions stored in the system memory to generate a ranking score for the candidate table from the set of ranking features for the candidate table. 9. The computer system of claim 6 , wherein the hardware processor executing the instructions stored in the system memory to access a set of static features comprises the hardware processor executing the instructions stored in the system memory to access one or more of: a static rank of a web page containing the candidate table, a domain rank of the web page containing the candidate table, a click count of the web page containing the candidate table, a subject column index, number of rows in the candidate table, or a data type for each column of the candidate table. | 0.82864 |
9,514,750 | 2 | 3 | 2. The method of claim 1 , further comprising presenting the first portion and the second portion of the audio data to the originating station or a terminal station other than the station that generated the content containing the particular phrase or topic that is disallowed for the conversation. | 2. The method of claim 1 , further comprising presenting the first portion and the second portion of the audio data to the originating station or a terminal station other than the station that generated the content containing the particular phrase or topic that is disallowed for the conversation. 3. The method of claim 2 , wherein the method further comprises: determining, from stored configuration information, whether or not one of the originating station or the terminal station is designated as a station for which conversation auditing has been directed; and responsive to determining that the originating station or the terminal station is designated as a station for which conversation auditing has been directed, performing the processing of the audio data content. | 0.877624 |
8,239,593 | 4 | 5 | 4. The method of claim 3 , further comprising outputting a number of interpretations of the ambiguous input, at least some of the interpretations each comprising at least an initial number of the characters of a language object of the number of language objects, at least one of the interpretations comprising the particular character and being an artificial variant that does not correspond with a language object. | 4. The method of claim 3 , further comprising outputting a number of interpretations of the ambiguous input, at least some of the interpretations each comprising at least an initial number of the characters of a language object of the number of language objects, at least one of the interpretations comprising the particular character and being an artificial variant that does not correspond with a language object. 5. The method of claim 4 , further comprising outputting the artificial variant at a location of relatively lower priority than the at least some of the interpretations. | 0.914387 |
10,102,201 | 18 | 19 | 18. A method for selecting a natural language module from a natural language module store comprising: inputting a natural language query to the natural language module store, the natural language module store offering use of natural language modules in a domain for compensation in accordance with corresponding defined pricing models; responsive to the natural language query, receiving from the natural language module store a list of natural language modules capable of interpreting at least a part of the natural language query to produce a meaning representation in the domain; and selecting a natural language module, from among the plurality of natural language modules, for inclusion in a natural language interpreter to interpret natural language queries in the domain. | 18. A method for selecting a natural language module from a natural language module store comprising: inputting a natural language query to the natural language module store, the natural language module store offering use of natural language modules in a domain for compensation in accordance with corresponding defined pricing models; responsive to the natural language query, receiving from the natural language module store a list of natural language modules capable of interpreting at least a part of the natural language query to produce a meaning representation in the domain; and selecting a natural language module, from among the plurality of natural language modules, for inclusion in a natural language interpreter to interpret natural language queries in the domain. 19. The method of claim 18 , wherein selecting a natural language module from a natural language module store comprises: browsing through the plurality of natural language modules presented by the natural language module store; and selecting the natural language module from among the plurality of natural language modules. | 0.678926 |
4,229,113 | 10 | 12 | 10. In a printing system of the type including means for advancing a receipt tape through a receipt tape zone and a printing mechanism for effecting printing along a printing path extending across the receipt tape zone and thereby printing on the receipt tape, the improvement comprising: means for positioning an alternative document in a zone overlying the receipt tape zone and including the printing path so that the printing mechanism prints on the alternative document instead of the receipt tape; and means responsive to the positioning of an alternative document to receive printing for advancing the alternative document with respect to the printing path; the means responsive to the positioning of an alternative document to receive printing comprising first and second document detecting means positioned on opposite sides of the printing path. | 10. In a printing system of the type including means for advancing a receipt tape through a receipt tape zone and a printing mechanism for effecting printing along a printing path extending across the receipt tape zone and thereby printing on the receipt tape, the improvement comprising: means for positioning an alternative document in a zone overlying the receipt tape zone and including the printing path so that the printing mechanism prints on the alternative document instead of the receipt tape; and means responsive to the positioning of an alternative document to receive printing for advancing the alternative document with respect to the printing path; the means responsive to the positioning of an alternative document to receive printing comprising first and second document detecting means positioned on opposite sides of the printing path. 12. The improvement according to claim 10 wherein one of the document detecting means includes means for directing a light beam across the path of an alternative document inserted to receive printing. | 0.886878 |
9,734,151 | 1 | 4 | 1. A method comprising: sending voice input data received by a media device to a speech-to-text service; receiving, by the media device, a textual representation of the voice input from the speech-to-text service; generating a signature based on the entire textual representation of the voice input, wherein the signature is a hash value; searching a set of data entries stored by the media device for a data entry matching the signature generated based on the entire textual representation of the voice input, each data entry of the set of stored data entries specifying a mapping between a signature and one or more media device actions; updating the set of stored data entries by storing the mapping between the signature and the entire textual representation; in response to locating a particular data entry among the set of stored data entries based on the generated signature, performing one or more particular media device actions associated with the particular stored data entry, the one or more particular media device actions including sending a media content query to a media search service; receiving, by the media device, one or more content item listings based on the media content query; causing display of at least a portion of the one or more content item listings; wherein the method is performed on one or more computing devices. | 1. A method comprising: sending voice input data received by a media device to a speech-to-text service; receiving, by the media device, a textual representation of the voice input from the speech-to-text service; generating a signature based on the entire textual representation of the voice input, wherein the signature is a hash value; searching a set of data entries stored by the media device for a data entry matching the signature generated based on the entire textual representation of the voice input, each data entry of the set of stored data entries specifying a mapping between a signature and one or more media device actions; updating the set of stored data entries by storing the mapping between the signature and the entire textual representation; in response to locating a particular data entry among the set of stored data entries based on the generated signature, performing one or more particular media device actions associated with the particular stored data entry, the one or more particular media device actions including sending a media content query to a media search service; receiving, by the media device, one or more content item listings based on the media content query; causing display of at least a portion of the one or more content item listings; wherein the method is performed on one or more computing devices. 4. The method of claim 1 , further comprising: receiving input from a user indicating a selection of one or more of the one or more content item listings; in response to selection of one or more of the one or more content item listings, storing information representing the selection. | 0.862669 |
9,779,131 | 33 | 34 | 33. The method of claim 27 , wherein a recognizer remains dormant prior to a match between spatiotemporal data and activation criteria of the recognizer. | 33. The method of claim 27 , wherein a recognizer remains dormant prior to a match between spatiotemporal data and activation criteria of the recognizer. 34. The method of claim 33 , wherein a recognizer becomes active when parameters of the spatiotemporal data match the activation criteria. | 0.91958 |
8,260,785 | 16 | 17 | 16. A system, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: 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 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 that invokes performance of a search 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 automatically 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 automatically constructing and storing search links in the fact repository. | 16. A system, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: 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 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 that invokes performance of a search 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 automatically 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 automatically constructing and storing search links in the fact repository. 17. The system of claim 16 , wherein the one or more predefined criteria are met when a predetermined time period has elapsed since the fact repository was last modified. | 0.866771 |
7,904,478 | 20 | 21 | 20. The apparatus of claim 19 , wherein a displaying mechanism is configured to display path expressions which are associated with the determined paths, wherein a path expression is an alternating sequence of entity names and relationship names. | 20. The apparatus of claim 19 , wherein a displaying mechanism is configured to display path expressions which are associated with the determined paths, wherein a path expression is an alternating sequence of entity names and relationship names. 21. The apparatus of claim 20 , wherein the processing mechanism is configured to use the displayed path expressions to determine how to access an instance of the second entity by using an instance of the first entity. | 0.945825 |
8,521,764 | 18 | 19 | 18. The computer-readable memory device of claim 15 , where storing the same variation of the entity name in the first memory or the second memory includes: storing the same variation of the entity name in the first memory or the second memory further based on information that includes at least one of an amount of time a user spent accessing the plurality of documents or whether a conversion occurred based on accessing the plurality of documents. | 18. The computer-readable memory device of claim 15 , where storing the same variation of the entity name in the first memory or the second memory includes: storing the same variation of the entity name in the first memory or the second memory further based on information that includes at least one of an amount of time a user spent accessing the plurality of documents or whether a conversion occurred based on accessing the plurality of documents. 19. The computer-readable memory device of claim 18 , where storing the same variation of the entity name in the first memory or the second memory includes: assigning a first weight to the determined total quantity of selections of the document associated with the particular entity identifier; assigning a second weight, different than the first weight, to the at least one of the amount of time the user spent accessing the plurality of documents or whether the conversion occurred based on accessing the plurality of documents; and storing the same variation of the entity name in the first memory or the second memory based on the first weight and the second weight. | 0.842353 |
9,710,548 | 7 | 9 | 7. A computer program product for using user preferences to customize answer output comprising: a computer readable, tangible storage device; and program instructions stored by the computer readable, tangible storage device, which, when executed by a processor, cause a computing platform to: extract from a first question one or more user preferences for a first user and one or more sentiment levels for a first user; perform a first semantic search on the first question; receive a plurality of candidate answers from the first semantic search; responsive to determining, by a computer that the first question contains multiple-parts or multiple-steps, retrieve, by a computer, supplemental information regarding at least one of the candidate answers; select one or more of the received candidate answers according to the one or more sentiment levels, or according to the one or more user preferences, or both, and adjust for the retrieved supplemental information; and produce a computer output including the selected one or more candidate answers. | 7. A computer program product for using user preferences to customize answer output comprising: a computer readable, tangible storage device; and program instructions stored by the computer readable, tangible storage device, which, when executed by a processor, cause a computing platform to: extract from a first question one or more user preferences for a first user and one or more sentiment levels for a first user; perform a first semantic search on the first question; receive a plurality of candidate answers from the first semantic search; responsive to determining, by a computer that the first question contains multiple-parts or multiple-steps, retrieve, by a computer, supplemental information regarding at least one of the candidate answers; select one or more of the received candidate answers according to the one or more sentiment levels, or according to the one or more user preferences, or both, and adjust for the retrieved supplemental information; and produce a computer output including the selected one or more candidate answers. 9. The computer program product as set forth in claim 7 wherein the program instructions further comprise program instructions which, when executed by a processor, cause a computing platform to: extract from a second question one or more additional user preferences for a second user and one or more additional sentiment levels for the second user; perform a second semantic search on the second question; receive a plurality of candidate answers from the second semantic search; select one or more of the received candidate answers from the second semantic search according to a combination of the one or more sentiment levels and according to the one or more user preferences associated with the first and second users and with the first and second questions; and wherein the producing, by a computer, an output includes the selected one or more candidate answers from the second semantic search. | 0.519272 |
7,546,546 | 19 | 20 | 19. A computer implemented contextual desktop system for providing a plurality of concurrent computer desktops or desktop metaphors, the system comprising: a network; and a computer system in communication with the network the computer system comprising a processor, a storage media having software programming code, a display and an operating system, said software programming code when executed on the computer system performs a method comprising: the operating system presenting a graphical user interface (GUI) desktop representation of the plurality of desktops at the display wherein each desktop comprises a file directory and an associated GUI, the desktop representation comprising a representation of a first desktop and a representation of a second desktop; responsive to the operating system enabling the first desktop as a default enabled desktop, the operating system directing user GUI access to a first file directory of the enabled first desktop, wherein the first file directory is based on a first desktop folder associated with the first desktop; responsive to the first desktop being the default enabled desktop, the operating system presenting the first desktop graphical user interface (GUI) as a displayed desktop; responsive to a first user GUI action, creating a user defined second file directory based on a first sub- folder of the first desktop folder; making the first sub-folder a second desktop folder of the second desktop; responsive to a user GUI second desktop enabling action enabling the second desktop as the default enabled desktop, the operating system directing user GUI access to the second file directory defined by the second desktop folder of the enabled second desktop, wherein the user GUI access comprises default file open and file save dialogs of application programs; responsive to the second desktop being the default enabled desktop, the operating system presenting the second desktop GUI as the displayed desktop; and responsive to the second desktop being the default enabled desktop, the operating system denying user GUI access to files other than files of the second file directory. | 19. A computer implemented contextual desktop system for providing a plurality of concurrent computer desktops or desktop metaphors, the system comprising: a network; and a computer system in communication with the network the computer system comprising a processor, a storage media having software programming code, a display and an operating system, said software programming code when executed on the computer system performs a method comprising: the operating system presenting a graphical user interface (GUI) desktop representation of the plurality of desktops at the display wherein each desktop comprises a file directory and an associated GUI, the desktop representation comprising a representation of a first desktop and a representation of a second desktop; responsive to the operating system enabling the first desktop as a default enabled desktop, the operating system directing user GUI access to a first file directory of the enabled first desktop, wherein the first file directory is based on a first desktop folder associated with the first desktop; responsive to the first desktop being the default enabled desktop, the operating system presenting the first desktop graphical user interface (GUI) as a displayed desktop; responsive to a first user GUI action, creating a user defined second file directory based on a first sub- folder of the first desktop folder; making the first sub-folder a second desktop folder of the second desktop; responsive to a user GUI second desktop enabling action enabling the second desktop as the default enabled desktop, the operating system directing user GUI access to the second file directory defined by the second desktop folder of the enabled second desktop, wherein the user GUI access comprises default file open and file save dialogs of application programs; responsive to the second desktop being the default enabled desktop, the operating system presenting the second desktop GUI as the displayed desktop; and responsive to the second desktop being the default enabled desktop, the operating system denying user GUI access to files other than files of the second file directory. 20. The system according to claim 19 , wherein the first desktop comprises a corresponding first desktop GUI for displaying representations of any one of widgets, files or folders of the first desktop, wherein the second desktop comprises a corresponding second desktop graphical user interface GUI for displaying representations of any one of widgets, files or folders of the second desktop, wherein only one of the plurality of desktops is enabled at a time as a default enabled desktop for directing user GUI access to a file directory of the default enabled desktop. | 0.648148 |
10,003,671 | 1 | 5 | 1. A computer program product for replaying an application session, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code executable by a computer to cause the computer to: monitor an application session; capture client events for the application session; capture image identifiers for images displayed during the application session, wherein the image identifiers are configured to identify image code from an application resource file associated with the images; and send the client events and image identifiers to a replay system that generates an image generation file including the image code from the application resource file to generate one or more images from the application session. | 1. A computer program product for replaying an application session, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code executable by a computer to cause the computer to: monitor an application session; capture client events for the application session; capture image identifiers for images displayed during the application session, wherein the image identifiers are configured to identify image code from an application resource file associated with the images; and send the client events and image identifiers to a replay system that generates an image generation file including the image code from the application resource file to generate one or more images from the application session. 5. The computer program product of claim 1 , wherein the computer comprises at least one of a portable smart phone and/or a portable tablet computer. | 0.853635 |
9,734,454 | 13 | 14 | 13. The method of claim 1 further comprising parsing the target information into the segments and prioritizing the segments, so that the highest priority segment is fact checked first, wherein priority is based on the relatedness of the segment to a current topic being discussed and when the segment was presented, wherein if the segment is not fact checked before a timeout threshold, then the segment is removed from a fact check queue. | 13. The method of claim 1 further comprising parsing the target information into the segments and prioritizing the segments, so that the highest priority segment is fact checked first, wherein priority is based on the relatedness of the segment to a current topic being discussed and when the segment was presented, wherein if the segment is not fact checked before a timeout threshold, then the segment is removed from a fact check queue. 14. The method of claim 13 wherein a plurality of fact check queues are implemented, wherein a first fact check queue contains the segments to be fact checked in real-time, and the second fact check queue contains the segments to be fact checked in non-real-time. | 0.928103 |
8,307,073 | 2 | 3 | 2. The method of claim 1 , wherein the non-URL escape sequence comprises XML encoded escape sequences. | 2. The method of claim 1 , wherein the non-URL escape sequence comprises XML encoded escape sequences. 3. The method of claim 2 , wherein the XML encoded escape sequences comprises “&” and the corresponding escaped character comprises “&”. | 0.95687 |
8,204,896 | 9 | 13 | 9. An image processing method, comprising: scanning image information regarding an original document, the original document including character addition information added manually to at least one character string in the original document; extracting layout information regarding character regions and the character addition information added to the at least one character string within the character regions from the image information; converting the character regions included in the layout information into character information; extracting one or more keywords comprising the at least one character string from the character information in response to determining that the character addition information added to the at least one character string has a predefined image characteristic; searching by use of the one or more keywords and generating meta-information based on information retrieved by the searching; and generating an electronic document according to a description of a predetermined format by adding the meta-information to the character information. | 9. An image processing method, comprising: scanning image information regarding an original document, the original document including character addition information added manually to at least one character string in the original document; extracting layout information regarding character regions and the character addition information added to the at least one character string within the character regions from the image information; converting the character regions included in the layout information into character information; extracting one or more keywords comprising the at least one character string from the character information in response to determining that the character addition information added to the at least one character string has a predefined image characteristic; searching by use of the one or more keywords and generating meta-information based on information retrieved by the searching; and generating an electronic document according to a description of a predetermined format by adding the meta-information to the character information. 13. The method according to claim 9 , further comprising storing a word dictionary database, wherein the extracting the one or more keywords includes extracting the one or more keywords by use of a weight coefficient of words registered on the word dictionary database. | 0.771259 |
8,832,584 | 1 | 11 | 1. A computer-implemented method, comprising: collecting highlights of a digital work entered by a plurality of different users via digital work presentation devices, individual digital work presentation devices having a display, wherein the plurality of different users includes a first user and a second user, and wherein the highlights of the digital work include (i) a first highlight entered by the first user to highlight a first passage, and (ii) a second highlight entered by the second user to highlight a second passage; serving the highlights to an individual digital work presentation device for presentation on the display; providing a user interface to enable the first user to craft questions, wherein the questions include (i) a first question pertaining to the first highlight entered by the first user to highlight the first passage, and (ii) a second question pertaining to the second highlight entered by the second user to highlight the second passage; storing the questions in association with the highlights to which the questions pertain; serving the questions in association with the highlights for presentation on the display; comparing the first question to a plurality of questions that pertain to highlights of the first passage, wherein comparing the first question to the plurality of questions further comprises comparing one or more words of the first question to the plurality of questions that pertain to the highlights of the first passage; grouping the first question and the plurality of questions in one or more groups based at least in part on the comparing the first question to the plurality of questions; and facilitating discovery of answers to the questions. | 1. A computer-implemented method, comprising: collecting highlights of a digital work entered by a plurality of different users via digital work presentation devices, individual digital work presentation devices having a display, wherein the plurality of different users includes a first user and a second user, and wherein the highlights of the digital work include (i) a first highlight entered by the first user to highlight a first passage, and (ii) a second highlight entered by the second user to highlight a second passage; serving the highlights to an individual digital work presentation device for presentation on the display; providing a user interface to enable the first user to craft questions, wherein the questions include (i) a first question pertaining to the first highlight entered by the first user to highlight the first passage, and (ii) a second question pertaining to the second highlight entered by the second user to highlight the second passage; storing the questions in association with the highlights to which the questions pertain; serving the questions in association with the highlights for presentation on the display; comparing the first question to a plurality of questions that pertain to highlights of the first passage, wherein comparing the first question to the plurality of questions further comprises comparing one or more words of the first question to the plurality of questions that pertain to the highlights of the first passage; grouping the first question and the plurality of questions in one or more groups based at least in part on the comparing the first question to the plurality of questions; and facilitating discovery of answers to the questions. 11. The computer-implemented method of claim 1 , wherein the facilitating discovery of answers comprises conducting an electronic search for the answers. | 0.878764 |
9,552,615 | 6 | 7 | 6. The computer system of claim 5 , wherein the at least one money laundering indicator requires that the first entity accessed the financial account from at least three distinct locations in the plurality of distinct locations in a specific order or pattern. | 6. The computer system of claim 5 , wherein the at least one money laundering indicator requires that the first entity accessed the financial account from at least three distinct locations in the plurality of distinct locations in a specific order or pattern. 7. The computer system of claim 6 , wherein the specific order or pattern comprises a timing requirement for the first entity accessing the financial account from the at least three distinct locations in the plurality of distinct locations. | 0.976517 |
8,522,255 | 13 | 15 | 13. An apparatus comprising: at least one processor; and at least one memory, wherein the at least one processor and the at least one memory are configured to provide operations comprising: receiving, at a service consumer implemented on a client computing system from a service provider implemented on a server computing system, a message comprising data values associated with a business object; transforming, at the service consumer, a portion of the message into first data values of a first data type, the first data values corresponding to a first business object instance, the first data type comprising character strings representing data elements of at least one business object node instance, the first data type being different than a second data type; storing the first data values in a table, the table being of a type associated with the business object, wherein each business object node instance corresponds to a row of the table and each column corresponds to the data elements; determining, at the service consumer, by type checking the first data values in response to a request for the first data values presented in the second data type, whether the first data values have already been transformed from the first data type to the second data type; transforming, at the service consumer, the first data values into the second data type based upon the determination that the first data values have not been previously transformed from the first data type to the second data type and based upon a plurality of rules; and replacing the first data values stored in the table in the first data type with the first data values transformed from the first data type to the second data type, wherein the computing resources utilized by the service consumer are reduced by transforming fewer than all of the data values from the first data type to the second data type. | 13. An apparatus comprising: at least one processor; and at least one memory, wherein the at least one processor and the at least one memory are configured to provide operations comprising: receiving, at a service consumer implemented on a client computing system from a service provider implemented on a server computing system, a message comprising data values associated with a business object; transforming, at the service consumer, a portion of the message into first data values of a first data type, the first data values corresponding to a first business object instance, the first data type comprising character strings representing data elements of at least one business object node instance, the first data type being different than a second data type; storing the first data values in a table, the table being of a type associated with the business object, wherein each business object node instance corresponds to a row of the table and each column corresponds to the data elements; determining, at the service consumer, by type checking the first data values in response to a request for the first data values presented in the second data type, whether the first data values have already been transformed from the first data type to the second data type; transforming, at the service consumer, the first data values into the second data type based upon the determination that the first data values have not been previously transformed from the first data type to the second data type and based upon a plurality of rules; and replacing the first data values stored in the table in the first data type with the first data values transformed from the first data type to the second data type, wherein the computing resources utilized by the service consumer are reduced by transforming fewer than all of the data values from the first data type to the second data type. 15. An apparatus in accordance with claim 13 , further comprising: buffering the first data values in the table associated with the business object; receiving request for the first data values; and returning an instance of the first data values from the table. | 0.560811 |
9,842,300 | 14 | 15 | 14. The apparatus of claim 13 , wherein the state transition probability is further calculated using a transition histogram comprising information from the sequence of previous states. | 14. The apparatus of claim 13 , wherein the state transition probability is further calculated using a transition histogram comprising information from the sequence of previous states. 15. The apparatus of claim 14 , wherein the state transition probability is further calculated as a parametric approximation of each state transition probability. | 0.960851 |
9,098,719 | 1 | 2 | 1. A machine-readable non-transitory storage medium having instructions therein, which when executed by a machine, causes the machine to perform a method, the method comprising: in response to receiving a first request associated with a document, updating the document in a first domain, the updated document associated with a mechanism for secure activation of active content referred to by a hyperlink; storing the active content in a second domain without filtering the active content; in response to receiving a subsequent request from a client to retrieve the updated document in the first domain, generating, at a device, a one time token uniquely for the subsequent request, the one time token to authorize an access to the active content of the second domain via a hyperlink having the one time token; sending the updated document modified with the hyperlink having the one time token to the client, the active content accessible via the hyperlink having the one time token when the client presents the updated document; in response to receiving a second request addressing the active content of the second domain, extracting a token from the second request, the token dynamically generated for a request to retrieve the updated document in the first domain; verifying, at the device, whether the second request is valid using the token extracted from the second request, the second request being valid when the token matches the one time token; and sending the active content for the second request if validity of the second request is verified based on the token to allow the secure activation of the active content in the updated document. | 1. A machine-readable non-transitory storage medium having instructions therein, which when executed by a machine, causes the machine to perform a method, the method comprising: in response to receiving a first request associated with a document, updating the document in a first domain, the updated document associated with a mechanism for secure activation of active content referred to by a hyperlink; storing the active content in a second domain without filtering the active content; in response to receiving a subsequent request from a client to retrieve the updated document in the first domain, generating, at a device, a one time token uniquely for the subsequent request, the one time token to authorize an access to the active content of the second domain via a hyperlink having the one time token; sending the updated document modified with the hyperlink having the one time token to the client, the active content accessible via the hyperlink having the one time token when the client presents the updated document; in response to receiving a second request addressing the active content of the second domain, extracting a token from the second request, the token dynamically generated for a request to retrieve the updated document in the first domain; verifying, at the device, whether the second request is valid using the token extracted from the second request, the second request being valid when the token matches the one time token; and sending the active content for the second request if validity of the second request is verified based on the token to allow the secure activation of the active content in the updated document. 2. The medium of claim 1 , wherein the verification comprises: sending a verification request to a server, the verification request including the token; and receiving a verification response from the server, the verification response indicating whether the token is valid, wherein the first request was received by the server and wherein the token is valid if the server generated the token for the second request. | 0.501205 |
8,976,179 | 1 | 3 | 1. A method, comprising: receiving, at a server, a search query, wherein the search query comprises a request for information about an object; determining a 3D model for the object based on the search query, wherein the 3D model comprises three-dimensional shape information about the object; determining, based on a plurality of stored images of the object, at least one applicable light field and at least one applicable viewing perspective, wherein the plurality of stored images of the object include images of the object captured under different lighting conditions and from different viewing perspectives; determining at least one applicable shader based on evaluation after receiving the search query; and transmitting, from the server, a search query result, wherein the search query result comprises the 3D model, the at least one applicable light field, the at least one applicable viewing perspective, and the at least one applicable shader. | 1. A method, comprising: receiving, at a server, a search query, wherein the search query comprises a request for information about an object; determining a 3D model for the object based on the search query, wherein the 3D model comprises three-dimensional shape information about the object; determining, based on a plurality of stored images of the object, at least one applicable light field and at least one applicable viewing perspective, wherein the plurality of stored images of the object include images of the object captured under different lighting conditions and from different viewing perspectives; determining at least one applicable shader based on evaluation after receiving the search query; and transmitting, from the server, a search query result, wherein the search query result comprises the 3D model, the at least one applicable light field, the at least one applicable viewing perspective, and the at least one applicable shader. 3. The method of claim 1 , wherein the at least one applicable viewing perspective is determined so as to substantially match at least one viewing perspective of at least one of the stored images of the object. | 0.863281 |
9,092,422 | 1 | 12 | 1. A method comprising: receiving a plurality of documents of text, wherein each document is associated with one or more category labels and includes one or more sequences of one or more words; determining a plurality of topics from the plurality of documents, wherein each topic represents a subdivision of a respective category label; performing a plurality of sampling iterations to generate a category-topic model that represents co-occurrence relationships between sequences and topics and co-occurrence relationships between topics and categories, wherein performing each of the plurality of sampling iterations comprises, for each sequence in each of the plurality of documents: sampling a category label for the sequence from the category labels associated with the document that includes the sequence; sampling a topic for the sequence; and updating current values of representations of the co-occurrence relationships based on the category label and the topic sampled for the sequence. | 1. A method comprising: receiving a plurality of documents of text, wherein each document is associated with one or more category labels and includes one or more sequences of one or more words; determining a plurality of topics from the plurality of documents, wherein each topic represents a subdivision of a respective category label; performing a plurality of sampling iterations to generate a category-topic model that represents co-occurrence relationships between sequences and topics and co-occurrence relationships between topics and categories, wherein performing each of the plurality of sampling iterations comprises, for each sequence in each of the plurality of documents: sampling a category label for the sequence from the category labels associated with the document that includes the sequence; sampling a topic for the sequence; and updating current values of representations of the co-occurrence relationships based on the category label and the topic sampled for the sequence. 12. The method of claim 1 , further comprising: determining that a first document of the plurality of documents is not associated with any category labels; and assigning a unique label to the first document. | 0.902726 |
9,081,767 | 1 | 8 | 1. A method for browsing a datastore of data objects, the method comprising: providing a first sentence for display in a first region of a user interface, the first sentence having a subject, verb and object, the object of the first sentence representing a first data object from the datastore of data objects, the datastore associating the first data object with a plurality of attributes describing characteristics of the first data object; providing a second sentence for display in the first region of a user interface, the second sentence having a subject, verb and object, the subject of the second sentence representing the first data object from the datastore of data objects and the object of the second sentence representing at least a second data object from the datastore of data objects that is related to the first data object, the datastore associating the second data object with a plurality of attributes describing characteristics of the second data object, the first sentence and the second sentence organized in the user interface as a hierarchy that includes a plurality of levels and the first sentence is in a superior level of the hierarchy and the second sentence is in a subordinate level of the hierarchy; receiving, by a computer, a user input selecting the second sentence displayed in the subordinate level of the hierarchy in the first region of the user interface; and responsive to receiving the user input selecting the second sentence displayed in the subordinate level of the hierarchy in the first region of the user interface: providing, for display in a second region of the user interface, one or more of the attributes of the first data object represented by the subject of the second sentence; and providing, for display in a third region of the user interface, one or more of the attributes of the second data object represented by the object of the second sentence. | 1. A method for browsing a datastore of data objects, the method comprising: providing a first sentence for display in a first region of a user interface, the first sentence having a subject, verb and object, the object of the first sentence representing a first data object from the datastore of data objects, the datastore associating the first data object with a plurality of attributes describing characteristics of the first data object; providing a second sentence for display in the first region of a user interface, the second sentence having a subject, verb and object, the subject of the second sentence representing the first data object from the datastore of data objects and the object of the second sentence representing at least a second data object from the datastore of data objects that is related to the first data object, the datastore associating the second data object with a plurality of attributes describing characteristics of the second data object, the first sentence and the second sentence organized in the user interface as a hierarchy that includes a plurality of levels and the first sentence is in a superior level of the hierarchy and the second sentence is in a subordinate level of the hierarchy; receiving, by a computer, a user input selecting the second sentence displayed in the subordinate level of the hierarchy in the first region of the user interface; and responsive to receiving the user input selecting the second sentence displayed in the subordinate level of the hierarchy in the first region of the user interface: providing, for display in a second region of the user interface, one or more of the attributes of the first data object represented by the subject of the second sentence; and providing, for display in a third region of the user interface, one or more of the attributes of the second data object represented by the object of the second sentence. 8. The method of claim 1 , wherein providing, for display in a second region of the interface, one or more attributes of the first data object comprises providing, for display in the second region of the interface, one or more attributes of the first data object that are fewer than all the attributes of the first data object. | 0.645336 |
9,361,363 | 4 | 7 | 4. The method of claim 1 , further comprising: determining a score for each query modification; and transmitting one or more of the query modifications having a score greater than a threshold score to the first user. | 4. The method of claim 1 , further comprising: determining a score for each query modification; and transmitting one or more of the query modifications having a score greater than a threshold score to the first user. 7. The method of claim 4 , wherein determining the score for each query modification is based on a number of possible search results corresponding to the query modification. | 0.956291 |
9,465,795 | 8 | 12 | 8. Logic encoded in one or more tangible non-transitory media that includes code for execution and when executed by a processor is operable to perform operations comprising: receiving enterprise network traffic associated with a particular user; identifying irrelevant documents in the received network traffic using a document filter; developing a personal vocabulary for the particular user based on the enterprise network traffic, wherein the irrelevant documents are not evaluated to develop the personal vocabulary, wherein the personal vocabulary is developed independent of additional users; determining an expertise associated with the particular user based, at least in part, on the personal vocabulary and activity of the additional users; determining a category associated with the particular user, wherein the category is at least partially based on applications used by the particular user; determining areas of interest for the particular user based on the personal vocabulary, the category, and inter-category terms, wherein the inter-category terms are used to link similar categories; determining associations for the particular user in relation to the additional users; and generating a feed based on a portion of the enterprise network traffic and areas of interest for the particular user, wherein the feed is automatically delivered to a subset of the additional users. | 8. Logic encoded in one or more tangible non-transitory media that includes code for execution and when executed by a processor is operable to perform operations comprising: receiving enterprise network traffic associated with a particular user; identifying irrelevant documents in the received network traffic using a document filter; developing a personal vocabulary for the particular user based on the enterprise network traffic, wherein the irrelevant documents are not evaluated to develop the personal vocabulary, wherein the personal vocabulary is developed independent of additional users; determining an expertise associated with the particular user based, at least in part, on the personal vocabulary and activity of the additional users; determining a category associated with the particular user, wherein the category is at least partially based on applications used by the particular user; determining areas of interest for the particular user based on the personal vocabulary, the category, and inter-category terms, wherein the inter-category terms are used to link similar categories; determining associations for the particular user in relation to the additional users; and generating a feed based on a portion of the enterprise network traffic and areas of interest for the particular user, wherein the feed is automatically delivered to a subset of the additional users. 12. The logic of claim 8 , wherein weights are used to filter the network traffic in order to develop the feed for the subset of the additional users. | 0.740484 |
8,341,167 | 17 | 21 | 17. A computer readable medium comprising computer readable program code embodied therein for causing a computer system to: receive a first search phrase for a search within a domain of a product; evaluate the first search phrase based on the domain of the product, wherein evaluating the first search phrase comprises: obtaining a plurality of user-submitted keywords from the first search phrase, querying a keyword repository with at least two user-submitted keywords of the plurality of user-submitted keywords to obtain a derivative keyword of a plurality of derivative keywords, wherein the keyword repository relates each of the plurality of user-submitted keywords to at least one of the plurality of derivative keywords, identifying a facet from a facet repository using the derivative keyword, wherein the facet is a term that is contextually related to the plurality of user-submitted keywords based on historical usage by multiple users of the user-submitted keywords when searching in the domain of the product, and wherein the facet, the derivative keyword, and the plurality of user-submitted keywords are used to obtain a plurality of search terms, applying a backward filter to revise the plurality of search terms into a second search phrase, and identifying a previously submitted question based on the facet, the derivative keyword, and the plurality of user-submitted keywords; and display the second search phrase and the previously submitted question. | 17. A computer readable medium comprising computer readable program code embodied therein for causing a computer system to: receive a first search phrase for a search within a domain of a product; evaluate the first search phrase based on the domain of the product, wherein evaluating the first search phrase comprises: obtaining a plurality of user-submitted keywords from the first search phrase, querying a keyword repository with at least two user-submitted keywords of the plurality of user-submitted keywords to obtain a derivative keyword of a plurality of derivative keywords, wherein the keyword repository relates each of the plurality of user-submitted keywords to at least one of the plurality of derivative keywords, identifying a facet from a facet repository using the derivative keyword, wherein the facet is a term that is contextually related to the plurality of user-submitted keywords based on historical usage by multiple users of the user-submitted keywords when searching in the domain of the product, and wherein the facet, the derivative keyword, and the plurality of user-submitted keywords are used to obtain a plurality of search terms, applying a backward filter to revise the plurality of search terms into a second search phrase, and identifying a previously submitted question based on the facet, the derivative keyword, and the plurality of user-submitted keywords; and display the second search phrase and the previously submitted question. 21. The computer readable medium of claim 17 , wherein the facet is the term that is contextually related to the plurality of user-submitted keywords when historical search phrases include the facet and a keyword of the plurality of user-submitted keywords. | 0.822268 |
5,526,268 | 13 | 16 | 13. An apparatus for monitoring a process, comprising: a digital processor coupled to an industrial process via means for encoding values of process parameters and process configuration information, the processor being programmed to control a display device and to present on the display device a diagrammatic display including text and graphics for simulating a condition of the process; a memory coupled to the processor, containing programmed definitions of the text and graphics included in the diagrammatic display during predetermined process conditions, the processor normally formatting the diagrammatic display at least partly as a function of said definitions, the memory further containing alternative definitions of at least a portion of at least a subset of one of the text and the graphics, the alternative definitions being different than the programmed definitions but representing the same said condition of the process; a user operated control input coupled to the processor and operable with the processor to select at least a subset of the information on the diagrammatic display, the processor switching between the alternative definitions and thereby converting the subset of the diagrammatic display from one format to another format during operation of the apparatus for monitoring the process. | 13. An apparatus for monitoring a process, comprising: a digital processor coupled to an industrial process via means for encoding values of process parameters and process configuration information, the processor being programmed to control a display device and to present on the display device a diagrammatic display including text and graphics for simulating a condition of the process; a memory coupled to the processor, containing programmed definitions of the text and graphics included in the diagrammatic display during predetermined process conditions, the processor normally formatting the diagrammatic display at least partly as a function of said definitions, the memory further containing alternative definitions of at least a portion of at least a subset of one of the text and the graphics, the alternative definitions being different than the programmed definitions but representing the same said condition of the process; a user operated control input coupled to the processor and operable with the processor to select at least a subset of the information on the diagrammatic display, the processor switching between the alternative definitions and thereby converting the subset of the diagrammatic display from one format to another format during operation of the apparatus for monitoring the process. 16. The apparatus of claim 13, wherein the definitions and the alternative definitions correspond one for one, and are addressably stored in the memory, and wherein the processor is operable to switch from said one format to said another format by altering selections from the memory. | 0.865147 |
9,843,555 | 9 | 14 | 9. The method of claim 1 , further comprising sending by the server system a text message to the second communication device advising of the receipt of the redirected call. | 9. The method of claim 1 , further comprising sending by the server system a text message to the second communication device advising of the receipt of the redirected call. 14. The method of claim 9 , further comprising receiving a call by the server system from the second communication device directed to the common identifier and recording by the server system a voice message therefrom. | 0.891174 |
8,990,241 | 1 | 2 | 1. A system having at least one processor, storage, and a communication platform connected to a network for identifying candidate queries related to a trending topic, the system comprising: a trending topic identification module that is configured to identify topics trending in one or more real-time content sources, wherein the trending topic identification module comprises: a content segmenting module that is configured to segment received documents from the one or more real-time content sources into words and named entities, a volume calculation module that is configured to calculate a volume for each of a predetermined number of topics by organizing the received documents into two or more portions of documents each defined by a time interval within a historical time period and, for each portion: calculating a probability for every word and named entity within the portion that the respective word or named entity is related to one of the predetermined number of topics, calculating a probability for every document within the portion that the respective document is related to one of the predetermined number of topics, and determining a volume for each of the predetermined number of topics by summing the calculated probabilities that each document is related to the respective topic, and a topic list generation module that is configured to generate a list of trending topics based on the calculated volumes for the predetermined number of topics; and a query recommendation module that is configured to suggest at least one candidate query in response to receiving a user query, wherein the at least one candidate query is obtained by comparing words and named entities of the user query with words and named entities associated with the identified topics. | 1. A system having at least one processor, storage, and a communication platform connected to a network for identifying candidate queries related to a trending topic, the system comprising: a trending topic identification module that is configured to identify topics trending in one or more real-time content sources, wherein the trending topic identification module comprises: a content segmenting module that is configured to segment received documents from the one or more real-time content sources into words and named entities, a volume calculation module that is configured to calculate a volume for each of a predetermined number of topics by organizing the received documents into two or more portions of documents each defined by a time interval within a historical time period and, for each portion: calculating a probability for every word and named entity within the portion that the respective word or named entity is related to one of the predetermined number of topics, calculating a probability for every document within the portion that the respective document is related to one of the predetermined number of topics, and determining a volume for each of the predetermined number of topics by summing the calculated probabilities that each document is related to the respective topic, and a topic list generation module that is configured to generate a list of trending topics based on the calculated volumes for the predetermined number of topics; and a query recommendation module that is configured to suggest at least one candidate query in response to receiving a user query, wherein the at least one candidate query is obtained by comparing words and named entities of the user query with words and named entities associated with the identified topics. 2. The system of claim 1 , wherein: the topic list generation module is configured to generate the list of trending topics by, for every one of the predetermined number of topics: calculating a mean volume by taking an average of the determined volumes for every portion within the historical time period; and calculating a deviation between a determined volume associated with a portion defined by a most recent time interval of the historical time period to the mean volume; and identifying one of the predetermined number of topics as a trending topic when the topic is associated with a determined volume that has a calculated deviation from the mean volume that exceeds a threshold value. | 0.575368 |
8,762,152 | 9 | 10 | 9. The method of claim 8 , wherein the method further comprises determining the resources available at the client. | 9. The method of claim 8 , wherein the method further comprises determining the resources available at the client. 10. The method of claim 9 , wherein the method further comprises allocating speech recognition tasks between the client and the server based on the resources available at one or both of the client and at the server. | 0.932517 |
8,788,262 | 16 | 17 | 16. The computer program product of claim 15 : wherein combining the text phrase of the abstract phrase and the text value comprises: creating a delimited phrase, comprising: inserting the text value into the abstract phrase at the particular position indicated by the variable; and inserting a delimiter before and/or after the inserted text value; wherein applying the integration rule comprises: determining whether the delimited phrase satisfies a condition of the rule, the determining based at least in part on the location of a delimiter within the delimited phrase; responsive to the determination, performing an action of the rule, the action comprising modifying the delimited phrase; and wherein the computer program code is further configured for: creating an integrated phrase, comprising removing delimiters from the delimited phrase. | 16. The computer program product of claim 15 : wherein combining the text phrase of the abstract phrase and the text value comprises: creating a delimited phrase, comprising: inserting the text value into the abstract phrase at the particular position indicated by the variable; and inserting a delimiter before and/or after the inserted text value; wherein applying the integration rule comprises: determining whether the delimited phrase satisfies a condition of the rule, the determining based at least in part on the location of a delimiter within the delimited phrase; responsive to the determination, performing an action of the rule, the action comprising modifying the delimited phrase; and wherein the computer program code is further configured for: creating an integrated phrase, comprising removing delimiters from the delimited phrase. 17. The computer program product of claim 16 , wherein determining whether the text of the delimited phrase satisfies a condition of the rule comprises determining whether a particular pattern of characters is present in the delimited phrase, the particular pattern including a delimiter character, and wherein modifying the delimited phrase comprises modifying the particular pattern of characters. | 0.753094 |
9,323,720 | 1 | 6 | 1. A method for unifying a fragmented document comprising: identifying structural information elements of a root document, wherein the structural information elements comprise at least one reference to a discrete document other than the root document; presenting to a user, the identified structural information elements within a rapid selection interface for selective acquisition of content from the discrete document; receiving at the rapid selection interface, a user initiated unification command including a user selection of one or more of the presented structural information elements; responsive to said unification command, acquiring content represented by the at least one reference from the discrete document without presenting the discrete document within a user interface window; and adding the acquired content to the root document. | 1. A method for unifying a fragmented document comprising: identifying structural information elements of a root document, wherein the structural information elements comprise at least one reference to a discrete document other than the root document; presenting to a user, the identified structural information elements within a rapid selection interface for selective acquisition of content from the discrete document; receiving at the rapid selection interface, a user initiated unification command including a user selection of one or more of the presented structural information elements; responsive to said unification command, acquiring content represented by the at least one reference from the discrete document without presenting the discrete document within a user interface window; and adding the acquired content to the root document. 6. The method of claim 1 , wherein each of the discrete documents is associated with a unique uniform resource locator (URL). | 0.939202 |
9,082,408 | 30 | 35 | 30. A method, for use with a system, the method performed by at least one processor executing computer program instructions stored on a non-transitory computer-readable medium: wherein the system comprises: a first device including an audio capture component; a speech recognition processing component; and a second device including a result processing component; wherein the method comprises: (A) using the audio capture component to capture an audio signal representing speech of a user to produce a captured audio signal; (B) using the speech recognition processing component to perform automatic speech recognition on the captured audio signal to produce speech recognition results; (C) determining that the result processing component is associated with a current context of the user, comprising: a. identifying a list of at least one result processing component currently authorized for use on behalf of the user; and b. determining that the at least one result processing component in the list is associated with the current context of the user; (D) in response to the determination that the result processing component is associated with the current context of the user, providing the speech recognition results to the result processing component; and (E) using the result processing component to process the speech recognition results to produce result output. | 30. A method, for use with a system, the method performed by at least one processor executing computer program instructions stored on a non-transitory computer-readable medium: wherein the system comprises: a first device including an audio capture component; a speech recognition processing component; and a second device including a result processing component; wherein the method comprises: (A) using the audio capture component to capture an audio signal representing speech of a user to produce a captured audio signal; (B) using the speech recognition processing component to perform automatic speech recognition on the captured audio signal to produce speech recognition results; (C) determining that the result processing component is associated with a current context of the user, comprising: a. identifying a list of at least one result processing component currently authorized for use on behalf of the user; and b. determining that the at least one result processing component in the list is associated with the current context of the user; (D) in response to the determination that the result processing component is associated with the current context of the user, providing the speech recognition results to the result processing component; and (E) using the result processing component to process the speech recognition results to produce result output. 35. The method of claim 30 , wherein (D) comprises providing the speech recognition results to the result processing component in real-time. | 0.862475 |
8,024,703 | 7 | 12 | 7. A system for developing view templates, comprising: a processor; storage, coupled to the processor, for storing example code artifacts; logic, stored on the storage for execution on the processor, for categorizing each of said example code artifacts according to purpose and function; logic, stored on the storage for execution on the processor, for grouping said example code artifacts based on the categorization to produce corresponding artifact roles; logic, stored on the storage for execution on the processor, for generating a view template, based upon the artifact roles, having static content portions and zero, one or more dynamic content portions; and logic, stored on the storage for execution on the processor, for storing view templates for reuse. | 7. A system for developing view templates, comprising: a processor; storage, coupled to the processor, for storing example code artifacts; logic, stored on the storage for execution on the processor, for categorizing each of said example code artifacts according to purpose and function; logic, stored on the storage for execution on the processor, for grouping said example code artifacts based on the categorization to produce corresponding artifact roles; logic, stored on the storage for execution on the processor, for generating a view template, based upon the artifact roles, having static content portions and zero, one or more dynamic content portions; and logic, stored on the storage for execution on the processor, for storing view templates for reuse. 12. The system of claims 7 , wherein said example code artifacts are web application files including, HTML source files, XML source files, portlet code and JSP source code. | 0.773087 |
10,158,596 | 1 | 5 | 1. A method comprising: durably storing a plurality of domain correction records, wherein each domain correction record of the plurality of domain correction records comprises a misspelled domain name and one or more candidate domain name corrections; detecting that an unprocessed email address of an attempt to log in to an online user account is not contained in a plurality of known email addresses, wherein the unprocessed email address comprises a misspelled domain name, wherein each known email address of the plurality of known email addresses comprises a domain name; retrieving, based on the misspelled domain name of the unprocessed email address, from the plurality of domain correction records, a matching domain correction record having a same misspelled domain name as the unprocessed email address; causing the one or more candidate domain name corrections of the matching domain correction record to be displayed on a client device; wherein each of the one or more candidate domain name corrections of the matching domain correction record occurs within the plurality of known email addresses at a frequency that exceeds a threshold; wherein the method is performed by one or more computers. | 1. A method comprising: durably storing a plurality of domain correction records, wherein each domain correction record of the plurality of domain correction records comprises a misspelled domain name and one or more candidate domain name corrections; detecting that an unprocessed email address of an attempt to log in to an online user account is not contained in a plurality of known email addresses, wherein the unprocessed email address comprises a misspelled domain name, wherein each known email address of the plurality of known email addresses comprises a domain name; retrieving, based on the misspelled domain name of the unprocessed email address, from the plurality of domain correction records, a matching domain correction record having a same misspelled domain name as the unprocessed email address; causing the one or more candidate domain name corrections of the matching domain correction record to be displayed on a client device; wherein each of the one or more candidate domain name corrections of the matching domain correction record occurs within the plurality of known email addresses at a frequency that exceeds a threshold; wherein the method is performed by one or more computers. 5. The method of claim 1 wherein the causing to be displayed comprises causing the one or more candidate domain name corrections of the matching domain correction record to be displayed in descending order of frequency that each of the one or more candidate domain name corrections occurs within the plurality of known email addresses. | 0.716582 |
9,013,485 | 13 | 14 | 13. The system of claim 10 , wherein to said create the sequence of synthesized poses, the computer device is further configured to: identify a collection of nearest neighbor feature vectors for each of the plurality of samples of the query stroke, wherein the collection of nearest neighbor feature vectors for each sample of the query stroke comprises two or more feature vectors for respective samples of one or more reference strokes that are most similar to the feature vector constructed for the sample of the query stroke; and wherein to said identify a best neighbor feature vector for each of the plurality of samples of the query stroke, one of the nearest neighbor feature vectors are selected from each of the collections of nearest neighbor feature vectors. | 13. The system of claim 10 , wherein to said create the sequence of synthesized poses, the computer device is further configured to: identify a collection of nearest neighbor feature vectors for each of the plurality of samples of the query stroke, wherein the collection of nearest neighbor feature vectors for each sample of the query stroke comprises two or more feature vectors for respective samples of one or more reference strokes that are most similar to the feature vector constructed for the sample of the query stroke; and wherein to said identify a best neighbor feature vector for each of the plurality of samples of the query stroke, one of the nearest neighbor feature vectors are selected from each of the collections of nearest neighbor feature vectors. 14. The system of claim 13 , wherein to said select one of the nearest neighbor feature vectors from each of the collections of nearest neighbor feature vectors, the computer device is configured to: apply a weighting to the collections of nearest neighbor feature vectors that encourages the selection, for adjacent samples of the query stroke, of nearest neighbor feature vectors for adjacent samples of a same reference stroke; and apply dynamic programming to the collections of weighted nearest neighbor feature vectors to determine the lowest cost sequence of nearest neighbor feature vectors. | 0.810443 |
8,762,161 | 20 | 22 | 20. The apparatus of claim 18 further comprising a visualization component for visualizing the network of category connections. | 20. The apparatus of claim 18 further comprising a visualization component for visualizing the network of category connections. 22. The apparatus of claim 20 wherein the visualization component represents the network according to time domain correlations between categories. | 0.932843 |
7,778,469 | 1 | 21 | 1. A computer implemented method for discriminatively selecting keyframes representative of segments of a source digital media, comprising the steps of: obtaining said source digital media for which keyframes are to be selected, wherein said source digital media comprises a plurality of segments, wherein said plurality of segments comprises a plurality of frames, said plurality of frames comprising candidate keyframes; pre-processing said source digital media to obtain a plurality of feature vectors, said feature vectors being representative of the candidate keyframes; determining in-class similarity values for said candidate keyframes, wherein the in-class similarity values are determined by comparing the feature vectors for the candidate keyframes to other feature vectors found solely within the same segment the candidate keyframes come from; determining out-of-class similarity values for said candidate keyframes, wherein the out-of-class similarity values are determined by comparing the feature vectors for the candidate keyframes to other feature vectors found solely outside of the segment the candidate keyframes come from; discriminatively selecting a keyframe for each segment based on both the in-class similarity values and the out-of-class similarity values of the candidate keyframes, wherein each selected keyframe is both representative of the segment the selected keyframe originates from and distinguishable from other selected keyframes which are representative of the remaining plurality of segments; wherein the chronological order of the selected keyframes as they appear within the source digital media is maintained during the step of discriminatively selecting a keyframe for each segment; and wherein the method steps are done by at least one processor. | 1. A computer implemented method for discriminatively selecting keyframes representative of segments of a source digital media, comprising the steps of: obtaining said source digital media for which keyframes are to be selected, wherein said source digital media comprises a plurality of segments, wherein said plurality of segments comprises a plurality of frames, said plurality of frames comprising candidate keyframes; pre-processing said source digital media to obtain a plurality of feature vectors, said feature vectors being representative of the candidate keyframes; determining in-class similarity values for said candidate keyframes, wherein the in-class similarity values are determined by comparing the feature vectors for the candidate keyframes to other feature vectors found solely within the same segment the candidate keyframes come from; determining out-of-class similarity values for said candidate keyframes, wherein the out-of-class similarity values are determined by comparing the feature vectors for the candidate keyframes to other feature vectors found solely outside of the segment the candidate keyframes come from; discriminatively selecting a keyframe for each segment based on both the in-class similarity values and the out-of-class similarity values of the candidate keyframes, wherein each selected keyframe is both representative of the segment the selected keyframe originates from and distinguishable from other selected keyframes which are representative of the remaining plurality of segments; wherein the chronological order of the selected keyframes as they appear within the source digital media is maintained during the step of discriminatively selecting a keyframe for each segment; and wherein the method steps are done by at least one processor. 21. The method of claim 1 , wherein the in-class similarity values and out-of-class similarity values are determined utilizing linear discriminant analysis. | 0.771261 |
8,108,218 | 20 | 23 | 20. An apparatus for analyzing voice information received from a person over a communications line, comprising: a storage device for storing one or more voice representations, where each voice representation corresponds to a word or phrase and is associated with a value, and for storing one or more actions; an interface for receiving a one of: a user-specified word and a user-specified phrase; and a processor for receiving voice information from a person over a communications line, analyzing the voice information to determine if one or more of the stored voice representations corresponding to the received user-specified word or phrase occur in the voice information received from the person and to generate a final criteria measurement value associated with the voice information, and performing one or more of the stored actions based on the final criteria measurement value if the voice information is found to include one or more of the stored voice representations, the final criteria measurement value based on the value associated with each determined stored voice representation occurring in the voice information. | 20. An apparatus for analyzing voice information received from a person over a communications line, comprising: a storage device for storing one or more voice representations, where each voice representation corresponds to a word or phrase and is associated with a value, and for storing one or more actions; an interface for receiving a one of: a user-specified word and a user-specified phrase; and a processor for receiving voice information from a person over a communications line, analyzing the voice information to determine if one or more of the stored voice representations corresponding to the received user-specified word or phrase occur in the voice information received from the person and to generate a final criteria measurement value associated with the voice information, and performing one or more of the stored actions based on the final criteria measurement value if the voice information is found to include one or more of the stored voice representations, the final criteria measurement value based on the value associated with each determined stored voice representation occurring in the voice information. 23. The apparatus of claim 20 , further comprising: a user interface for receiving information regarding user specified actions, wherein the actions are to be performed in the event one or more of the voice representations are found in the voice information; and wherein the storage device is further for storing the user specified actions. | 0.633621 |
8,489,400 | 1 | 2 | 1. A method comprising: presenting text on a touch-sensitive display of a computing device; receiving, via the touch-sensitive display, a user touch; identifying a portion of the text based at least in part on the user touch; and audibly presenting the portion of the text. | 1. A method comprising: presenting text on a touch-sensitive display of a computing device; receiving, via the touch-sensitive display, a user touch; identifying a portion of the text based at least in part on the user touch; and audibly presenting the portion of the text. 2. The method of claim 1 , wherein receiving the user touch further comprises receiving non-contiguous separate inputs, wherein the non-contiguous separate inputs indicate a number of paragraphs of the text to be audibly presented as the portion of the text. | 0.702765 |
9,171,072 | 2 | 3 | 2. The system of claim 1 , wherein the system is configured to allow a user to monitor the best case estimate of the overall classification quality and terminate the document review process and change parameters and/or instruction for the document classification process based on the best case estimate of the overall classification quality being equal to or lower than the predetermined quality threshold of the documents in the random selected document set. | 2. The system of claim 1 , wherein the system is configured to allow a user to monitor the best case estimate of the overall classification quality and terminate the document review process and change parameters and/or instruction for the document classification process based on the best case estimate of the overall classification quality being equal to or lower than the predetermined quality threshold of the documents in the random selected document set. 3. The system of claim 2 , wherein the system is configured to allow the user to accept an original classification of all the documents in the entire document set based on the best case estimate being equal to or higher than the predetermined quality threshold of the documents in the random selected document set. | 0.885569 |
9,008,429 | 1 | 2 | 1. A method for comparing a text image and a character string comprising: embedding a character string into a vectorial space, comprising extracting a set of features from the character string and generating a character string representation based on the extracted character string features; embedding a text image into a vectorial space, comprising extracting a set of features from the text image and generating a text image representation based on the extracted text image features; and computing a compatibility between the text image representation and character string representation comprising computing a function of the text image representation and character string representation, the function including an embedding parameter w which is a DE-dimensional vector or a D×E matrix W which embeds the text image representation and character string representation into a new space, where D is the dimensionality of the text image representation and E is the dimensionality of the character string representation, wherein at least one of the embedding and the computing of the compatibility is performed with a processor. | 1. A method for comparing a text image and a character string comprising: embedding a character string into a vectorial space, comprising extracting a set of features from the character string and generating a character string representation based on the extracted character string features; embedding a text image into a vectorial space, comprising extracting a set of features from the text image and generating a text image representation based on the extracted text image features; and computing a compatibility between the text image representation and character string representation comprising computing a function of the text image representation and character string representation, the function including an embedding parameter w which is a DE-dimensional vector or a D×E matrix W which embeds the text image representation and character string representation into a new space, where D is the dimensionality of the text image representation and E is the dimensionality of the character string representation, wherein at least one of the embedding and the computing of the compatibility is performed with a processor. 2. The method of claim 1 , wherein the function of the text image representation and character string representation is in a bilinear form. | 0.777955 |
9,280,749 | 9 | 10 | 9. A computer system comprising: a processor; and a memory storing computer-executable instructions that, when executed by the processor, cause the processor to: identify a first set of model data including a first set of device data from a plurality of model computing devices, the first set of device data including location data and access data for the plurality of model computing devices; identify a plurality of categories for an attribute of a population segment, each category defining a segment of the attribute, the population segment including the candidate computing device; train a classification model using the first set of model data and the plurality of categories; receive a device identifier from the candidate computing device, the device identifier including device data of the candidate computing device; apply the device data to the classification model to generate an offline prediction of a category of the plurality of categories for the candidate computing device; determine a location of the candidate computing device using an IP address of the candidate computing device; generate an online prediction of a category of the plurality of categories for the candidate computing device using the location; and generate a composite prediction of a category of the plurality of categories for the candidate computing device by combining the offline prediction and the online prediction. | 9. A computer system comprising: a processor; and a memory storing computer-executable instructions that, when executed by the processor, cause the processor to: identify a first set of model data including a first set of device data from a plurality of model computing devices, the first set of device data including location data and access data for the plurality of model computing devices; identify a plurality of categories for an attribute of a population segment, each category defining a segment of the attribute, the population segment including the candidate computing device; train a classification model using the first set of model data and the plurality of categories; receive a device identifier from the candidate computing device, the device identifier including device data of the candidate computing device; apply the device data to the classification model to generate an offline prediction of a category of the plurality of categories for the candidate computing device; determine a location of the candidate computing device using an IP address of the candidate computing device; generate an online prediction of a category of the plurality of categories for the candidate computing device using the location; and generate a composite prediction of a category of the plurality of categories for the candidate computing device by combining the offline prediction and the online prediction. 10. The computer system of claim 9 , the computer-executable instructions further causing the processor to: receive, from the candidate computing device, a request for content; select a content item based on the composite prediction; and serve the content item to the candidate computing device in response to the request. | 0.718039 |
8,718,672 | 10 | 14 | 10. A mobile device comprising: a memory; a processor coupled to the memory; a plurality of modules stored in the memory and executable on the processor, the plurality of modules comprising: a status application module configured to: collect sensor data on the mobile device, monitor an activity of a user of the mobile device, detect a modification of the monitored activity, and provide a recommendation to the user of the mobile device based at least in part on a difference between the modified activity and the monitored activity; an accelerometer module or a barometer module to identify transportation modes of the user of the mobile device; a Wi-Fi module, a Global System for Mobile Communications (GSM) module, a Personal Area Network (PAN) module, and/or a Global Positioning System (GPS) module to track locations of the user of the mobile device; a microphone module to record environmental conditions surrounding the user of the mobile device, and to record speech being spoken in proximity to the user of the mobile device. | 10. A mobile device comprising: a memory; a processor coupled to the memory; a plurality of modules stored in the memory and executable on the processor, the plurality of modules comprising: a status application module configured to: collect sensor data on the mobile device, monitor an activity of a user of the mobile device, detect a modification of the monitored activity, and provide a recommendation to the user of the mobile device based at least in part on a difference between the modified activity and the monitored activity; an accelerometer module or a barometer module to identify transportation modes of the user of the mobile device; a Wi-Fi module, a Global System for Mobile Communications (GSM) module, a Personal Area Network (PAN) module, and/or a Global Positioning System (GPS) module to track locations of the user of the mobile device; a microphone module to record environmental conditions surrounding the user of the mobile device, and to record speech being spoken in proximity to the user of the mobile device. 14. The mobile device of claim 10 , further comprising a compass module, a camera module, or an ambient light module to collect sensor data to augment the transportation modes of the user or to augment tracking locations of the user. | 0.659357 |
8,132,098 | 14 | 15 | 14. A system, comprising: a processor; and a computer-readable storage device coupled to the processor, the computer-readable storage device storing instructions that, when executed by the processor, perform operations including: identifying a hyphenation window comprising text in one or more paragraphs; determining a layout of text within the hyphenation window, the layout comprising a plurality of consecutive text lines; identifying each text line, in the plurality of consecutive text lines, that ends in a hyphen; determining proximity of at least two non-consecutive text lines, in the plurality of consecutive lines, that end in hyphens; and calculating a hyphenation penalty value based on the determined proximity of the at least two non-consecutive lines that end in hyphens. | 14. A system, comprising: a processor; and a computer-readable storage device coupled to the processor, the computer-readable storage device storing instructions that, when executed by the processor, perform operations including: identifying a hyphenation window comprising text in one or more paragraphs; determining a layout of text within the hyphenation window, the layout comprising a plurality of consecutive text lines; identifying each text line, in the plurality of consecutive text lines, that ends in a hyphen; determining proximity of at least two non-consecutive text lines, in the plurality of consecutive lines, that end in hyphens; and calculating a hyphenation penalty value based on the determined proximity of the at least two non-consecutive lines that end in hyphens. 15. The system of claim 14 , wherein identifying a hyphenation window comprises receiving input from a user and identifying the hyphenation window based on the received input. | 0.876934 |
9,760,624 | 15 | 20 | 15. The computer-implemented method of claim 4 , further comprising, when the contents of the web page do not exceed at least one text threshold: identifying a resource identifier for the web page; identifying a language corresponding to the resource identifier in a mapping table that maps a plurality of resource identifiers to the plurality of languages; and setting the identified language as the input language. | 15. The computer-implemented method of claim 4 , further comprising, when the contents of the web page do not exceed at least one text threshold: identifying a resource identifier for the web page; identifying a language corresponding to the resource identifier in a mapping table that maps a plurality of resource identifiers to the plurality of languages; and setting the identified language as the input language. 20. The computer-implemented method of claim 15 , wherein the mapping table is stored on a remote server, and wherein the method further comprises: submitting, to the remote server, a request for a language based on the resource identifier; and receiving, from the remote server, the language in response to the request. | 0.910011 |
8,646,029 | 27 | 28 | 27. A computer-implemented method comprising: enabling, using a computing device, secure information transfer between a web browser's scripting engine and layout engine, said enabling comprising: enabling restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; enabling at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object, said enabling the at least one object to be returned cross-domain enabling return of a proxy object associated with the at least one object, the proxy object created in a type system associated with the calling system; and enabling at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine. | 27. A computer-implemented method comprising: enabling, using a computing device, secure information transfer between a web browser's scripting engine and layout engine, said enabling comprising: enabling restricted access to at least one Application Programming Interface (API) associated with a scripting language of the scripting engine; enabling at least one object to be returned cross-domain to a calling system, via the scripting engine and the layout engine, without divulging type system information associated with the at least one object, said enabling the at least one object to be returned cross-domain enabling return of a proxy object associated with the at least one object, the proxy object created in a type system associated with the calling system; and enabling at least one sub-window proxy object to assert security policies associated with a primary window object associated with the layout engine. 28. The computer-implemented method of claim 27 , further comprising: enabling the scripting engine to access to at least one property descriptor. | 0.892962 |
9,830,318 | 6 | 9 | 6. The computer-implemented method of claim 1 , wherein the end-of-sentence cue is a prosodic cue. | 6. The computer-implemented method of claim 1 , wherein the end-of-sentence cue is a prosodic cue. 9. The computer-implemented method of claim 6 , wherein prosodic cue is based on duration. | 0.969799 |
7,899,812 | 1 | 4 | 1. A system for interactive browsing, wherein the system is coupled to a knowledge base and a document database, the knowledge base stores a plurality of terms and information relating to each term, and the document database stores a plurality of documents, the system comprises: term acquiring means, for acquiring one or more terms in which a user has interest; first extracting means, for extracting information relating to the one or more terms in which the user has interest from the knowledge base; second extracting means, for extracting documents containing the one or more terms in which the user has interest from the document database; a first display part in a user interface, for displaying information extracted by the first extracting means; and a second display part in the user interface, for displaying a list of the documents extracted by the second extracting means; wherein the information extracted by the first extracting means and the list of the documents extracted by the second extracting means are concurrently displayed in the same user interface such that: (i) selection by the user of a portion of the information displayed in the first display part effectuates a change in the list of documents displayed in the second display part; and (ii) selection by the user of a term in the list of documents displayed in the second display part effectuates a change in the information displayed in the first display part. | 1. A system for interactive browsing, wherein the system is coupled to a knowledge base and a document database, the knowledge base stores a plurality of terms and information relating to each term, and the document database stores a plurality of documents, the system comprises: term acquiring means, for acquiring one or more terms in which a user has interest; first extracting means, for extracting information relating to the one or more terms in which the user has interest from the knowledge base; second extracting means, for extracting documents containing the one or more terms in which the user has interest from the document database; a first display part in a user interface, for displaying information extracted by the first extracting means; and a second display part in the user interface, for displaying a list of the documents extracted by the second extracting means; wherein the information extracted by the first extracting means and the list of the documents extracted by the second extracting means are concurrently displayed in the same user interface such that: (i) selection by the user of a portion of the information displayed in the first display part effectuates a change in the list of documents displayed in the second display part; and (ii) selection by the user of a term in the list of documents displayed in the second display part effectuates a change in the information displayed in the first display part. 4. The system according to claim 1 , wherein the first display part displays the one or more terms in which the user has interest and at least one of their relations and properties by a term graph or a text description. | 0.733577 |
8,108,890 | 11 | 17 | 11. A non-transitory machine readable medium on which is stored a computer program for an automated method of authoring a number of interactive menu audiovisual assets in respective languages, the computer program comprising instructions which when executed by a computer system performs the method comprising: establishing or creating a menu component representing a plurality of interactive menu audiovisual assets, the menu component comprising references to an instance of menu background data, a number of sets of menu text in a plurality of different languages, each text having an associated length, and a menu text template defining a number of text positions of dynamic adjustability to automatically accommodate varying lengths of the sets of menu text; and the computer, as instructed by the computer program, iteratively compositing for each of the plurality of languages the menu background data, the menu text and the menu text template, the menu text template dimensioning an associated graphical highlight element to each item of menu text to author the plurality of interactive menu audiovisual assets for each of the plurality of languages, the interactive menu audiovisual assets structured and arranged as executable code upon a non-transitory storage medium for a playback device. | 11. A non-transitory machine readable medium on which is stored a computer program for an automated method of authoring a number of interactive menu audiovisual assets in respective languages, the computer program comprising instructions which when executed by a computer system performs the method comprising: establishing or creating a menu component representing a plurality of interactive menu audiovisual assets, the menu component comprising references to an instance of menu background data, a number of sets of menu text in a plurality of different languages, each text having an associated length, and a menu text template defining a number of text positions of dynamic adjustability to automatically accommodate varying lengths of the sets of menu text; and the computer, as instructed by the computer program, iteratively compositing for each of the plurality of languages the menu background data, the menu text and the menu text template, the menu text template dimensioning an associated graphical highlight element to each item of menu text to author the plurality of interactive menu audiovisual assets for each of the plurality of languages, the interactive menu audiovisual assets structured and arranged as executable code upon a non-transitory storage medium for a playback device. 17. The non-transitory machine readable medium as claimed in claim 11 , further including a manual override to allow a menu items to be generated manually. | 0.719203 |
10,061,867 | 4 | 5 | 4. The method of claim 1 , wherein the plurality of interactions correspond to a first time period comprising the particular time period, and wherein the method further comprises: extracting, by a processor, a second plurality of fragments from a second plurality of interactions, the second plurality of interactions corresponding to a second time period, the second time period being different from the first time period; initializing, by the processor, a second collection of tracked topics to the empty collection; computing, by the processor, a similarity between each fragment of the second fragments and each of the known topics; and adding, by the processor, a known topic of the known topics to the second tracked topics in response to the similarity between a fragment and the known topic exceeding the threshold value. | 4. The method of claim 1 , wherein the plurality of interactions correspond to a first time period comprising the particular time period, and wherein the method further comprises: extracting, by a processor, a second plurality of fragments from a second plurality of interactions, the second plurality of interactions corresponding to a second time period, the second time period being different from the first time period; initializing, by the processor, a second collection of tracked topics to the empty collection; computing, by the processor, a similarity between each fragment of the second fragments and each of the known topics; and adding, by the processor, a known topic of the known topics to the second tracked topics in response to the similarity between a fragment and the known topic exceeding the threshold value. 5. The method of claim 4 , wherein the first time period has a length different from a length of the second time period. | 0.95509 |
8,281,284 | 1 | 4 | 1. A method that uses a processor to edit text using a web-based text editor, comprising: opening a document using a web-based text editor; receiving a first user input for selecting a block of text in the document; in reply to the first user input, inserting, using the processor, into a source code of the document, a first temporary node before the selected block and a second temporary node after the selected block; receiving a second user input for applying an attribute to the selected block; and in reply to the second user input, adding, using the processor, an attribute node between the first and second temporary nodes of the source code so as to apply the attribute to at least part of the block of the document. | 1. A method that uses a processor to edit text using a web-based text editor, comprising: opening a document using a web-based text editor; receiving a first user input for selecting a block of text in the document; in reply to the first user input, inserting, using the processor, into a source code of the document, a first temporary node before the selected block and a second temporary node after the selected block; receiving a second user input for applying an attribute to the selected block; and in reply to the second user input, adding, using the processor, an attribute node between the first and second temporary nodes of the source code so as to apply the attribute to at least part of the block of the document. 4. The method of claim 1 , further comprising identifying a plurality of children nodes between the first and second temporary nodes. | 0.868317 |
8,793,265 | 29 | 31 | 29. The system of claim 27 , further comprising an application module configured for receiving the query, wherein the selector is further configured for causing execution of the query on the selected personalized search engine. | 29. The system of claim 27 , further comprising an application module configured for receiving the query, wherein the selector is further configured for causing execution of the query on the selected personalized search engine. 31. The system of claim 29 , wherein the selector further includes an analyzer configured for analyzing quality of the search results based on one or more of the query and characteristic information for the selected personalized search engine; and a scoring module configured for scoring the selected personalized search engine based on the quality of the search results. | 0.916479 |
9,317,555 | 1 | 7 | 1. A method for querying a distributed database system, the method comprising: parsing, by one or more processors, a query request; generating, by one or more processors, an access plan for the query request, wherein the access plan specifies therein a database table related to the query request, and wherein a copy of the database table is stored in multiple database devices; selecting, by one or more processors and based on status information of each copy of the database table, one copy of the database table from a plurality of copies of the database table as a target database table, wherein the status information of each of the plurality of copies of the database table comprises: consistent status information indicating whether a particular copy of the database table is consistent with other copies of the database table; availability status information indicating an availability of a particular copy of the database table; and load status information indicating workload of a database device in which a particular copy of the database table is stored; executing, by one or more processors, a query operation on the target database table according to the access plan; checking, by one or more processors, a consistent requirement of the query request; selecting, by one or more processors and based on the consistent status information of each of the plurality of copies, at least one copy of the database table whose consistent status information indicates that said at least one copy is consistent with other copies of the database table to form a first candidate copy set, wherein the first candidate copy set is selected in response to the consistent requirement of the query request being determined as having a consistency level that exceeds a first predefined level; selecting, by one or more processors, the plurality of copies to form a first candidate copy set without considering the consistent status information if the consistent requirement of the query request has a consistency level that is below a second predefined level; selecting from the first candidate copy set, by one or more processors and based on the availability status information of each copy of the database table in the first candidate copy set, at least one copy of the database table whose availability status information indicates that said at least one copy of the database table is available to form a second candidate copy set; and selecting from the second candidate copy set, by one or more processors and based on the load status information of each copy in the second candidate copy set, a copy of the database table, whose load status information indicates that the database device that stores the copy has a lowest workload compared to other database devices that are soring the copy of the database table, as the target database table. | 1. A method for querying a distributed database system, the method comprising: parsing, by one or more processors, a query request; generating, by one or more processors, an access plan for the query request, wherein the access plan specifies therein a database table related to the query request, and wherein a copy of the database table is stored in multiple database devices; selecting, by one or more processors and based on status information of each copy of the database table, one copy of the database table from a plurality of copies of the database table as a target database table, wherein the status information of each of the plurality of copies of the database table comprises: consistent status information indicating whether a particular copy of the database table is consistent with other copies of the database table; availability status information indicating an availability of a particular copy of the database table; and load status information indicating workload of a database device in which a particular copy of the database table is stored; executing, by one or more processors, a query operation on the target database table according to the access plan; checking, by one or more processors, a consistent requirement of the query request; selecting, by one or more processors and based on the consistent status information of each of the plurality of copies, at least one copy of the database table whose consistent status information indicates that said at least one copy is consistent with other copies of the database table to form a first candidate copy set, wherein the first candidate copy set is selected in response to the consistent requirement of the query request being determined as having a consistency level that exceeds a first predefined level; selecting, by one or more processors, the plurality of copies to form a first candidate copy set without considering the consistent status information if the consistent requirement of the query request has a consistency level that is below a second predefined level; selecting from the first candidate copy set, by one or more processors and based on the availability status information of each copy of the database table in the first candidate copy set, at least one copy of the database table whose availability status information indicates that said at least one copy of the database table is available to form a second candidate copy set; and selecting from the second candidate copy set, by one or more processors and based on the load status information of each copy in the second candidate copy set, a copy of the database table, whose load status information indicates that the database device that stores the copy has a lowest workload compared to other database devices that are soring the copy of the database table, as the target database table. 7. The method of claim 1 , wherein the distributed database system is a federation database system. | 0.958921 |
7,739,277 | 1 | 7 | 1. A computer-implemented method for presenting a ranking of search results, comprising: providing an index to a plurality of documents including: a main index associating with each of the documents a frequency of one or more terms being included in each of the documents; an anchor text index associating with each of the documents an anchor text frequency of the one or more terms being included in anchor text in a source document referencing each of the documents; receiving a query including at least one query term; applying the query to the index to yield results of the query identifying one or more of the documents that include the at least one query term; applying a scoring function to generate a score for each of the one or more documents included in the results of the query, wherein the scoring function (score) includes one of: score = ∑ ( wtf B + wtf Anchor B Anchor ) ( k 1 + 1 ) k 1 ( ( 1 - b ) + b w ⅆ l avw ⅆ l ) + ( wtf + wtf Anchor ) × log ( N n ) ; and score = ∑ ( wtf B + wtf Anchor B Anchor ) ( k 1 + 1 ) k 1 + ( wtf B + wtf Anchor B Anchor ) × log ( N n ) , where: wtf is a weighted term frequency applying a weight to a frequency with which a given query term is included in the document; wtf Anchor is a weighted term frequency applying a weight to a frequency with which the given query term is included in anchor text referencing the document; k 1 is a constant; b is a constant; wdl is a weighted document length applying a weight to a length of the document being scored; avwdl is an average weighted document length of all documents being scored; N is the number of documents on the network; and n is the number of documents including at least one appearance of a given query term; and generating an output of the ranked results of the query to be displayed to a user. | 1. A computer-implemented method for presenting a ranking of search results, comprising: providing an index to a plurality of documents including: a main index associating with each of the documents a frequency of one or more terms being included in each of the documents; an anchor text index associating with each of the documents an anchor text frequency of the one or more terms being included in anchor text in a source document referencing each of the documents; receiving a query including at least one query term; applying the query to the index to yield results of the query identifying one or more of the documents that include the at least one query term; applying a scoring function to generate a score for each of the one or more documents included in the results of the query, wherein the scoring function (score) includes one of: score = ∑ ( wtf B + wtf Anchor B Anchor ) ( k 1 + 1 ) k 1 ( ( 1 - b ) + b w ⅆ l avw ⅆ l ) + ( wtf + wtf Anchor ) × log ( N n ) ; and score = ∑ ( wtf B + wtf Anchor B Anchor ) ( k 1 + 1 ) k 1 + ( wtf B + wtf Anchor B Anchor ) × log ( N n ) , where: wtf is a weighted term frequency applying a weight to a frequency with which a given query term is included in the document; wtf Anchor is a weighted term frequency applying a weight to a frequency with which the given query term is included in anchor text referencing the document; k 1 is a constant; b is a constant; wdl is a weighted document length applying a weight to a length of the document being scored; avwdl is an average weighted document length of all documents being scored; N is the number of documents on the network; and n is the number of documents including at least one appearance of a given query term; and generating an output of the ranked results of the query to be displayed to a user. 7. The computer-implemented method of claim 1 , wherein when the document is not associated with anchor text data, the scoring function (score) includes: score = ∑ wtf ( k 1 + 1 ) k 1 ( ( 1 - b ) + b wdl avwdl ) + wtf × log ( N n ) . | 0.840397 |
9,171,530 | 18 | 19 | 18. An encryption apparatus comprising: at least one input device; at least one output device; at least one processor; and at least one memory device which stores a plurality of instructions, which when executed by the at least one processor, cause the at least one processor to (a) receive an input of characters through the at least one input device, the characters corresponding to a message, (b) receive a selection of a recipe through the at least one input device, (c) determine whether each character is a valid character, wherein a valid character includes a number or a letter of an alphabet; (d) remove each invalid character; (e) transform the remaining characters into a string of musical notes b executing an algorithm corresponding to the recipe, and (f) transmit the string of musical notes and a recipe type via the at least one output device to a communicatively coupled destination computing device. | 18. An encryption apparatus comprising: at least one input device; at least one output device; at least one processor; and at least one memory device which stores a plurality of instructions, which when executed by the at least one processor, cause the at least one processor to (a) receive an input of characters through the at least one input device, the characters corresponding to a message, (b) receive a selection of a recipe through the at least one input device, (c) determine whether each character is a valid character, wherein a valid character includes a number or a letter of an alphabet; (d) remove each invalid character; (e) transform the remaining characters into a string of musical notes b executing an algorithm corresponding to the recipe, and (f) transmit the string of musical notes and a recipe type via the at least one output device to a communicatively coupled destination computing device. 19. The encryption apparatus of claim 18 , wherein the destination computing device: receives the string of musical notes and the recipe type; executes a second algorithm corresponding to the recipe to transform the string of musical notes into characters; and displays the characters. | 0.601955 |
8,200,670 | 11 | 27 | 11. A non-transitory computer readable medium having stored thereon instructions which, when executed by one or more processors, causes the processors to perform operations comprising: identifying a plurality of documents, from a set of documents, wherein each of the plurality of documents include a top N terms, wherein the top N terms are the same for each of the plurality of documents, wherein the top N terms are based on respective term frequency scores, and wherein N is an integer; identifying at least a subset of the identified documents that satisfy a pattern string; and forming a document cluster from at least the subset of the identified documents. | 11. A non-transitory computer readable medium having stored thereon instructions which, when executed by one or more processors, causes the processors to perform operations comprising: identifying a plurality of documents, from a set of documents, wherein each of the plurality of documents include a top N terms, wherein the top N terms are the same for each of the plurality of documents, wherein the top N terms are based on respective term frequency scores, and wherein N is an integer; identifying at least a subset of the identified documents that satisfy a pattern string; and forming a document cluster from at least the subset of the identified documents. 27. The non-transitory computer readable medium of claim 11 , wherein N is greater than or equal to 1. | 0.911917 |
7,577,639 | 1 | 2 | 1. A computer-readable storage medium in a content management system, comprising computer instructions for: retrieving at least one of a first plurality of records, each comprising content; receiving a user input of contextual information; storing the contextual information; determining a rhetorical purpose for the content of each record by comparing the content with the contextual information; associating at least one rhetorical topic library with the content of each record according to the content's determined rhetorical purpose; parsing the content of each record into a combination of one or more rhetorical and structural elements by utilizing the at least one rhetorical topic library associated with said content; and storing the rhetorical elements each with an identifiable functional attribute for association with a portion of the at least one rhetorical topic library. | 1. A computer-readable storage medium in a content management system, comprising computer instructions for: retrieving at least one of a first plurality of records, each comprising content; receiving a user input of contextual information; storing the contextual information; determining a rhetorical purpose for the content of each record by comparing the content with the contextual information; associating at least one rhetorical topic library with the content of each record according to the content's determined rhetorical purpose; parsing the content of each record into a combination of one or more rhetorical and structural elements by utilizing the at least one rhetorical topic library associated with said content; and storing the rhetorical elements each with an identifiable functional attribute for association with a portion of the at least one rhetorical topic library. 2. The storage medium of claim 1 , wherein the content comprises at least one among visual rhetoric, audible rhetoric, and tactile rhetoric, and wherein the at least one rhetorical library is a database independent of the first plurality of records. | 0.824153 |
7,720,657 | 1 | 6 | 1. A computer-implemented method for modeling a target system, the method comprising: identifying a first block that represents multiple component models in a block diagram model of a target system; displaying a user interface in response to a first user action, the first user action indicating a selection of the first block, the user interface including a mechanism that provides the user with the multiple component models; receiving a user selection that selects a first component model from the multiple component models; incorporating the first component model into the model of the target system using the first block; saving the model of the target system that includes the first component model in a memory; and switching the first block to represent a second component model in response to a second user action indicating a selection of second component model in the user interface, without replacing the first block with a second block representing the second component model. | 1. A computer-implemented method for modeling a target system, the method comprising: identifying a first block that represents multiple component models in a block diagram model of a target system; displaying a user interface in response to a first user action, the first user action indicating a selection of the first block, the user interface including a mechanism that provides the user with the multiple component models; receiving a user selection that selects a first component model from the multiple component models; incorporating the first component model into the model of the target system using the first block; saving the model of the target system that includes the first component model in a memory; and switching the first block to represent a second component model in response to a second user action indicating a selection of second component model in the user interface, without replacing the first block with a second block representing the second component model. 6. The method of claim 1 wherein after the second component model is selected in the user interface, the second component model is incorporated into the model of the target system through the first block. | 0.726542 |
8,370,162 | 1 | 2 | 1. A method of processing user input, the method comprising: receiving a first input having a first modality; determining, with at least one processor, a first temporal window for the first input based, at least in part, on first data stored on at least one storage device, wherein the first data indicates a duration of the first temporal window associated with inputs received via the first modality; receiving a second input from the user having a second modality that is different than the first modality; determining whether the second input is received during the first temporal window; aggregating based, at least in part on whether the second input is received during the first temporal window, the first input and the second input to obtain an aggregated input; determining whether any portion of the second input is received after the first temporal window has expired; and wherein aggregating the first input and the second input comprises aggregating the first input and only a portion of the second input received during the first temporal window. | 1. A method of processing user input, the method comprising: receiving a first input having a first modality; determining, with at least one processor, a first temporal window for the first input based, at least in part, on first data stored on at least one storage device, wherein the first data indicates a duration of the first temporal window associated with inputs received via the first modality; receiving a second input from the user having a second modality that is different than the first modality; determining whether the second input is received during the first temporal window; aggregating based, at least in part on whether the second input is received during the first temporal window, the first input and the second input to obtain an aggregated input; determining whether any portion of the second input is received after the first temporal window has expired; and wherein aggregating the first input and the second input comprises aggregating the first input and only a portion of the second input received during the first temporal window. 2. The method of claim 1 , wherein aggregating the first input and only a portion of the second input comprises aggregating the first input and the entire second input, in response to determining that no portion of the second input is received after the first temporal window has expired. | 0.674944 |
9,384,267 | 1 | 7 | 1. A method, comprising: at a computing system with one or more processors and memory storing one or more programs for execution by the one or more processors, obtaining a partial search query; mapping the partial search query to an entry in a chunk table, the entry in the chunk table having at least one pointer to a complete query in a first language in a token table, wherein an entry in the token table matches a complete query in the first language to a translation of the complete query in a second language; and formatting both a set of complete queries in the first language and the matching translations for display, wherein the set is determined from the pointers for the entry in the chunk table. | 1. A method, comprising: at a computing system with one or more processors and memory storing one or more programs for execution by the one or more processors, obtaining a partial search query; mapping the partial search query to an entry in a chunk table, the entry in the chunk table having at least one pointer to a complete query in a first language in a token table, wherein an entry in the token table matches a complete query in the first language to a translation of the complete query in a second language; and formatting both a set of complete queries in the first language and the matching translations for display, wherein the set is determined from the pointers for the entry in the chunk table. 7. The method of claim 1 , the token table further including entries matching complete queries in the first language to expansions in the first language and the method further comprising: formatting an expansion of a first complete query in the set of complete queries for display concurrently with a translation of the first complete query. | 0.678908 |
7,865,491 | 8 | 12 | 8. A system, comprising, an underlying database; and a runtime component executing on a processor, configured to: receive a user request to perform a model entity operation, wherein the user request includes a user selection of a first instance of a model entity selected from a plurality of instances of the model entity included in a first query result and a selected query operation, wherein the model entity is defined by a database abstraction model logically describing an underlying database and wherein the model entity defines a focus for the selected query operation, and wherein instances of the model entity are distinguished by an identifier in the underlying database; retrieve, in response to the user request, a linking function configured to identify instances of the model entity that are related to the first instance of the model entity, according to a predefined relationship; and perform the model entity operation by: invoking the linking function to retrieve any instances of the model entity that are related to the first instance of the model entity; executing the selected query operation against the retrieved instances of the model entity; and returning, as a second query result, at least a second instance of the model entity that satisfies any conditions specified by the selected query operation. | 8. A system, comprising, an underlying database; and a runtime component executing on a processor, configured to: receive a user request to perform a model entity operation, wherein the user request includes a user selection of a first instance of a model entity selected from a plurality of instances of the model entity included in a first query result and a selected query operation, wherein the model entity is defined by a database abstraction model logically describing an underlying database and wherein the model entity defines a focus for the selected query operation, and wherein instances of the model entity are distinguished by an identifier in the underlying database; retrieve, in response to the user request, a linking function configured to identify instances of the model entity that are related to the first instance of the model entity, according to a predefined relationship; and perform the model entity operation by: invoking the linking function to retrieve any instances of the model entity that are related to the first instance of the model entity; executing the selected query operation against the retrieved instances of the model entity; and returning, as a second query result, at least a second instance of the model entity that satisfies any conditions specified by the selected query operation. 12. The system of claim 8 , wherein the model entity represents an individual, and wherein the linking function identifies additional instances of the model entity that represent individuals related to one another by geographic locations. | 0.76938 |
9,195,646 | 13 | 15 | 13. The training data generation method according to claim 12 , wherein in Step (b), the training data candidates assigned a specified label in the cluster containing the specified label at or above a predetermined percentage are used as the training data having the specified label. | 13. The training data generation method according to claim 12 , wherein in Step (b), the training data candidates assigned a specified label in the cluster containing the specified label at or above a predetermined percentage are used as the training data having the specified label. 15. The training data generation method according to claim 13 , wherein in Step (b), the degree of cluster membership is obtained for training data candidates that are not assigned the specified label in the cluster containing the specified label at or above a predetermined percentage, and the training data candidates for which the obtained degree is not lower than a threshold value are used as training data, while the training data candidates for which the obtained degree is less than the threshold value are deleted from the entire set of training data candidates. | 0.81873 |
9,588,960 | 14 | 19 | 14. A non-transitory computer readable medium having executable instructions stored thereon, the instructions causing a processor to: identify a set of training texts; extract a respective set of features for each of the training texts; train a classification model using the training texts and the extracted features; extract a token from a natural language text; identify a set of token attributes associated with the token based on a semantic-syntactic analysis of the natural language text, wherein the set of token attributes comprises at least one of a lexical attribute, a syntactic attribute, or a semantic attribute, and wherein to perform the semantic-syntactic analysis of the natural language text, the processor is to: generate a lexical-morphological structure of a sentence of the natural language text; identify a syntactic tree using the lexical-morphological structure; generate a language-independent semantic structure based on the syntactic tree; and identify a set of token attributes using the language-independent semantic structure; determine a category for the token based on the set of token attributes and the trained classification model; and generate a tagged representation of the natural language text, the tagged representation referencing the category for the token. | 14. A non-transitory computer readable medium having executable instructions stored thereon, the instructions causing a processor to: identify a set of training texts; extract a respective set of features for each of the training texts; train a classification model using the training texts and the extracted features; extract a token from a natural language text; identify a set of token attributes associated with the token based on a semantic-syntactic analysis of the natural language text, wherein the set of token attributes comprises at least one of a lexical attribute, a syntactic attribute, or a semantic attribute, and wherein to perform the semantic-syntactic analysis of the natural language text, the processor is to: generate a lexical-morphological structure of a sentence of the natural language text; identify a syntactic tree using the lexical-morphological structure; generate a language-independent semantic structure based on the syntactic tree; and identify a set of token attributes using the language-independent semantic structure; determine a category for the token based on the set of token attributes and the trained classification model; and generate a tagged representation of the natural language text, the tagged representation referencing the category for the token. 19. The non-transitory computer-readable medium of claim 14 , further comprising executable instructions causing the processor to: rank the set of token attributes; and identify a first subset of the set of token attributes based on the ranking. | 0.814955 |
8,487,942 | 45 | 46 | 45. A system for processing an action script for a graphical image for visual display, the system comprising: a network input and output interface to receive data; a first memory circuit to store data; a frame buffer to store pixel data; and a plurality of processor circuits to separate the action script from other data, to parse the action script into a plurality of descriptions and a corresponding plurality of variable length operand data sets, the plurality of descriptions specifying the graphical image in a non-pixel-by-pixel form; to directly convert each description of the plurality of descriptions of the action script into a plurality of operational codes, each corresponding operational code comprising at least one graphical primitive instruction for native execution by at least one processor circuit of the plurality of processor circuits or comprising a memory pointer to an address in the first memory having a sequence of graphical primitive instructions for native execution by the at least one processor circuit of the plurality of processor circuits; to directly convert each variable length operand data set of the corresponding plurality of variable length operand data sets into one or more control words and store the one or more control words in the first memory, each control word comprising operand data and one or more control bits in predetermined fields for the native execution of the one or more graphical primitive instructions by the at least one processor circuit of the plurality of processor circuits; at least one processor circuit of the plurality of processor circuits to directly execute the one or more graphical primitive instructions using the one or more control words to generate pixel data for the graphical image. | 45. A system for processing an action script for a graphical image for visual display, the system comprising: a network input and output interface to receive data; a first memory circuit to store data; a frame buffer to store pixel data; and a plurality of processor circuits to separate the action script from other data, to parse the action script into a plurality of descriptions and a corresponding plurality of variable length operand data sets, the plurality of descriptions specifying the graphical image in a non-pixel-by-pixel form; to directly convert each description of the plurality of descriptions of the action script into a plurality of operational codes, each corresponding operational code comprising at least one graphical primitive instruction for native execution by at least one processor circuit of the plurality of processor circuits or comprising a memory pointer to an address in the first memory having a sequence of graphical primitive instructions for native execution by the at least one processor circuit of the plurality of processor circuits; to directly convert each variable length operand data set of the corresponding plurality of variable length operand data sets into one or more control words and store the one or more control words in the first memory, each control word comprising operand data and one or more control bits in predetermined fields for the native execution of the one or more graphical primitive instructions by the at least one processor circuit of the plurality of processor circuits; at least one processor circuit of the plurality of processor circuits to directly execute the one or more graphical primitive instructions using the one or more control words to generate pixel data for the graphical image. 46. The system of claim 45 , further comprising: a display controller coupled to the frame buffer to receive the pixel data; and a display coupled to the display controller to visually display the graphical image. | 0.909362 |
8,825,698 | 1 | 8 | 1. A computer implemented method executed using one or more processors, the method comprising: receiving a search query from a searching user; determining, by the one or more processors, that the search query corresponds to a trigger query and, in response, providing data associated with a first set of authoritative users for potential display to the searching user; determining, by the one or more processors, a second set of authoritative users based on the first set of authoritative users; for each authoritative user in the second set of authoritative users, receiving a contact status between the authoritative user and the searching user within a social networking service; and transmitting instructions to display data associated with authoritative users of the second set of authoritative users with search results responsive to the search query, the data comprising the contact status for each authoritative user in the second set of authoritative users. | 1. A computer implemented method executed using one or more processors, the method comprising: receiving a search query from a searching user; determining, by the one or more processors, that the search query corresponds to a trigger query and, in response, providing data associated with a first set of authoritative users for potential display to the searching user; determining, by the one or more processors, a second set of authoritative users based on the first set of authoritative users; for each authoritative user in the second set of authoritative users, receiving a contact status between the authoritative user and the searching user within a social networking service; and transmitting instructions to display data associated with authoritative users of the second set of authoritative users with search results responsive to the search query, the data comprising the contact status for each authoritative user in the second set of authoritative users. 8. The method of claim 1 , wherein the trigger query comprises a query for which one or more authoritative users are to be displayed in response to a matching query. | 0.89777 |
9,645,912 | 9 | 10 | 9. The method of claim 1 , comprising: identifying a branch structure associated with the modifying intermediate language code; and preserving the branch structure within the modified intermediate language code. | 9. The method of claim 1 , comprising: identifying a branch structure associated with the modifying intermediate language code; and preserving the branch structure within the modified intermediate language code. 10. The method of claim 9 , the identifying comprising: parsing the modifying intermediate language code to create a directed graph; and evaluating the directed graph to identify the branch structure. | 0.926901 |
9,152,709 | 6 | 7 | 6. The method as recited in claim 1 , further comprising generating an updated topic space based on a plurality of additional microblog entries that are received via the social stream domain. | 6. The method as recited in claim 1 , further comprising generating an updated topic space based on a plurality of additional microblog entries that are received via the social stream domain. 7. The method as recited in claim 6 , further comprising: receiving a second microblog entry from the social stream domain that is associated with the topic; and determining, based on the updated topic space, that at least one different media item in the media domain is associated with the topic. | 0.901198 |
8,700,367 | 1 | 15 | 1. A method comprising: analyzing, by a computer, dependency data from a simulation model having a model identifier, wherein said computer is configured for creating a visualization of a plurality of simulation models that depend from said simulation model; determining, by said computer, first variables within a first subset of said plurality of simulation models; analyzing, by said computer, said dependency data relating to said first subset of said plurality of simulation models; determining, by said computer, second variables within a second subset of said plurality of simulation models, wherein said second subset of said plurality of simulation models is impacted by said dependency data, wherein said second subset of said plurality of simulation models is dependent upon said first subset of said plurality of simulation models, and wherein said dependency data relates to a transfer of information exchanged between at least one of said first variables or said second variables, and at least one of said first subset of said plurality of simulation models or said second subset of said plurality of simulation models, wherein said information includes at least one of accuracy of said information, an amount of said information, a transfer rate of said information, a processing rate of said information, and usage data for each of variable types; distributing, by said computer, and based on said dependency data and according to a dependency tree, a change to a select variable to at least one of said first subset of said plurality of simulation models or said second subset of said plurality of simulation models, wherein said dependency tree includes at least one of said first subset of said plurality of simulation models or said second subset of said plurality of simulation models, that depend from said simulation model; creating, by said computer, said visualization based on how said change to said select variable affects at least one of said first subset of said plurality of simulation models or said second subset of said plurality of simulation models, wherein said visualization shows dependencies of said simulation model based upon said dependency data, and wherein said visualization lists at least one of said first subset of said plurality of simulation models or said second subset of said plurality of simulation models, impacted by said select variable; determining, by said computer, a number of said plurality of simulation models affected by said select variable, wherein said plurality of simulation models simulate outcomes, effectiveness, penetration, utilization, and distribution of marketing strategies based upon at least one of historic, current or probability data of said marketing strategies. | 1. A method comprising: analyzing, by a computer, dependency data from a simulation model having a model identifier, wherein said computer is configured for creating a visualization of a plurality of simulation models that depend from said simulation model; determining, by said computer, first variables within a first subset of said plurality of simulation models; analyzing, by said computer, said dependency data relating to said first subset of said plurality of simulation models; determining, by said computer, second variables within a second subset of said plurality of simulation models, wherein said second subset of said plurality of simulation models is impacted by said dependency data, wherein said second subset of said plurality of simulation models is dependent upon said first subset of said plurality of simulation models, and wherein said dependency data relates to a transfer of information exchanged between at least one of said first variables or said second variables, and at least one of said first subset of said plurality of simulation models or said second subset of said plurality of simulation models, wherein said information includes at least one of accuracy of said information, an amount of said information, a transfer rate of said information, a processing rate of said information, and usage data for each of variable types; distributing, by said computer, and based on said dependency data and according to a dependency tree, a change to a select variable to at least one of said first subset of said plurality of simulation models or said second subset of said plurality of simulation models, wherein said dependency tree includes at least one of said first subset of said plurality of simulation models or said second subset of said plurality of simulation models, that depend from said simulation model; creating, by said computer, said visualization based on how said change to said select variable affects at least one of said first subset of said plurality of simulation models or said second subset of said plurality of simulation models, wherein said visualization shows dependencies of said simulation model based upon said dependency data, and wherein said visualization lists at least one of said first subset of said plurality of simulation models or said second subset of said plurality of simulation models, impacted by said select variable; determining, by said computer, a number of said plurality of simulation models affected by said select variable, wherein said plurality of simulation models simulate outcomes, effectiveness, penetration, utilization, and distribution of marketing strategies based upon at least one of historic, current or probability data of said marketing strategies. 15. The method of claim 1 , further including: categorizing said plurality of simulation models according to identifiers for a plurality of model developers; and determining an allocation of human resources based upon an allocation type identifier. | 0.714286 |
9,645,800 | 1 | 4 | 1. A method of enabling static analysis of indirectly modeled code by an analyzer lacking capability for direct analysis of any indirectly modeled code, the method comprising: transforming by a processor a syntax tree of a source code segment written in an indirectly modeled language that is not supported by a static analyzer, by including in each node of the syntax tree a respective location identifier identifying a location of at least one of an operator and an operand corresponding to that node in source code specified in the indirectly modeled language; identifying by the processor a set of nodes of selected types in the transformed syntax tree, each selected type being associated with taint propagation indicating propagation of an operand comprising or derived from a user input to an operator specified in a code module specified in a directly modeled language, the static analyzer supporting the directly modelled language; and for each node in the identified set, generating by the processor a statement in the directly modeled language, based on, at least in part, at least one of: (i) a type of the node, (ii) a type of an input to the node, and (iii) an object corresponding to the node. | 1. A method of enabling static analysis of indirectly modeled code by an analyzer lacking capability for direct analysis of any indirectly modeled code, the method comprising: transforming by a processor a syntax tree of a source code segment written in an indirectly modeled language that is not supported by a static analyzer, by including in each node of the syntax tree a respective location identifier identifying a location of at least one of an operator and an operand corresponding to that node in source code specified in the indirectly modeled language; identifying by the processor a set of nodes of selected types in the transformed syntax tree, each selected type being associated with taint propagation indicating propagation of an operand comprising or derived from a user input to an operator specified in a code module specified in a directly modeled language, the static analyzer supporting the directly modelled language; and for each node in the identified set, generating by the processor a statement in the directly modeled language, based on, at least in part, at least one of: (i) a type of the node, (ii) a type of an input to the node, and (iii) an object corresponding to the node. 4. The method of claim 1 , wherein the transformed syntax tree comprises a JavaScript Object Notification (JSON) tree. | 0.912979 |
7,492,888 | 4 | 17 | 4. The method according to claim 1 wherein the contact evaluation parameter is derived from information obtained from a database, the database being accessed based upon an identification of the call. | 4. The method according to claim 1 wherein the contact evaluation parameter is derived from information obtained from a database, the database being accessed based upon an identification of the call. 17. The method according to claim 4 wherein the priority value assigned to the call is increased in priority if the time of receipt of the call is within a predetermined period of time of the close-of-business time of the caller. | 0.921629 |
8,352,412 | 9 | 13 | 9. A programmable non-transitory storage medium tangibly embodying a program of machine-readable instructions executable by a digital processing apparatus to perform operations of transforming domain specific unstructured and broken language data into structured data for enabling custom data analytics, the operations comprising: acquiring structured data, semi-structured data, and associated metadata related to a domain and problem of interest; developing baseline data related to said domain and problem of interest from said structured data, semi-structured data, and associated metadata; receiving structured and unstructured content related to said domain and problem of interest; providing word equivalents to words within said structured and unstructured content according to a domain and problem of interest; providing definitions of key descriptors within said domain and problem of interest; processing said structured and unstructured content using said baseline data, said word equivalents, and said key descriptors to develop a workflow for classifying said structured and unstructured content for said domain and problem of interest; identifying data acquisition and data analysis errors relating to said receiving of said structured and unstructured content and said classifying of said structured and unstructured content; analyzing states of said data within said workflow to identify state errors; monitoring sources of said structured and unstructured content and monitoring said data within said workflow to identify source and processing errors; maintaining policies for resolving said data acquisition and data analysis errors, said state errors, and said source and processing errors; resolving said data acquisition and data analysis errors, said state errors, and said source and processing errors according to said policies; and outputting results of said workflow, said results of said workflow comprising said structured and unstructured content classified into structured data enabled to be used in data analytics. | 9. A programmable non-transitory storage medium tangibly embodying a program of machine-readable instructions executable by a digital processing apparatus to perform operations of transforming domain specific unstructured and broken language data into structured data for enabling custom data analytics, the operations comprising: acquiring structured data, semi-structured data, and associated metadata related to a domain and problem of interest; developing baseline data related to said domain and problem of interest from said structured data, semi-structured data, and associated metadata; receiving structured and unstructured content related to said domain and problem of interest; providing word equivalents to words within said structured and unstructured content according to a domain and problem of interest; providing definitions of key descriptors within said domain and problem of interest; processing said structured and unstructured content using said baseline data, said word equivalents, and said key descriptors to develop a workflow for classifying said structured and unstructured content for said domain and problem of interest; identifying data acquisition and data analysis errors relating to said receiving of said structured and unstructured content and said classifying of said structured and unstructured content; analyzing states of said data within said workflow to identify state errors; monitoring sources of said structured and unstructured content and monitoring said data within said workflow to identify source and processing errors; maintaining policies for resolving said data acquisition and data analysis errors, said state errors, and said source and processing errors; resolving said data acquisition and data analysis errors, said state errors, and said source and processing errors according to said policies; and outputting results of said workflow, said results of said workflow comprising said structured and unstructured content classified into structured data enabled to be used in data analytics. 13. The programmable non-transitory storage medium of claim 9 , wherein said analyzing states of said data further executes state assertion and associated source accessibility state assertion. | 0.909434 |
9,516,004 | 1 | 5 | 1. A system, comprising: a non-transitory memory storing a list of common credentials; a network interface component, configured to receive a credential associated with a user authentication attempt; and one or more hardware processors configured to execute instructions to cause the system to perform operations comprising: determining if the received credential is correct; comparing the received credential to the list of common credentials when the received credential is not correct; and when the received credential matches a common credential on the list of common credentials: increasing a score by a weighted factor based on the received credential matching the common credential, wherein increasing the score indicates an increased likelihood that an attacker is entering common credentials in a horizontal attack in order to gain access to a user account; storing a time associated with the score increase; and making a security determination based on the score; wherein the weighted factor is lower when a time since a previous score increase is greater than a threshold time than when the time since the previous score increase is less than or equal to the threshold time. | 1. A system, comprising: a non-transitory memory storing a list of common credentials; a network interface component, configured to receive a credential associated with a user authentication attempt; and one or more hardware processors configured to execute instructions to cause the system to perform operations comprising: determining if the received credential is correct; comparing the received credential to the list of common credentials when the received credential is not correct; and when the received credential matches a common credential on the list of common credentials: increasing a score by a weighted factor based on the received credential matching the common credential, wherein increasing the score indicates an increased likelihood that an attacker is entering common credentials in a horizontal attack in order to gain access to a user account; storing a time associated with the score increase; and making a security determination based on the score; wherein the weighted factor is lower when a time since a previous score increase is greater than a threshold time than when the time since the previous score increase is less than or equal to the threshold time. 5. The system of claim 1 , wherein the weighted factor is associated with a commonality of the common credential. | 0.687845 |
9,852,188 | 11 | 12 | 11. A non-transitory machine-readable medium comprising instructions stored therein, which when executed by a processor, causes the processor to perform operations comprising: receiving a query related to multimedia content, the query including one or more terms, being in addition to the multimedia content, and being provided by a user during consumption of the multimedia content by the user; identifying one or more terms in the query; automatically generating, for rewriting the query related to the multimedia content, one or more query rewrite candidates based on entities associated with the multimedia content and the one or more terms in the query, wherein the entities include values characterizing one or more objects represented in the multimedia content, and wherein generating the one or more query rewrite candidates comprises: scoring the one or more extracted entities based on one or more of: a time at which the extracted entities are annotated in the multimedia content or based on co-occurrences of n-grams in a query repository, the n-grams in the query repository each being a contiguous sequence of n items from a given sequence of text or speech, and the n-grams in the query repository including unigrams, bigrams, tri grams, and four-grams, ranking the extracted entities based on the scoring, and combining one or more of the terms of the query with one or more scored extracted entities to generate the one or more query rewrite candidates; providing the one or more query rewrite candidates to a search engine; scoring the one or more query rewrite candidates based on characteristics of respective result sets resulting from the providing; ranking the scored one or more query rewrite candidates based on their respective scores; rewriting the query related to the multimedia content based on a particular ranked query rewrite candidate; and providing for display, responsive to the query related to the multimedia content, a result set from the search engine based on the rewritten query. | 11. A non-transitory machine-readable medium comprising instructions stored therein, which when executed by a processor, causes the processor to perform operations comprising: receiving a query related to multimedia content, the query including one or more terms, being in addition to the multimedia content, and being provided by a user during consumption of the multimedia content by the user; identifying one or more terms in the query; automatically generating, for rewriting the query related to the multimedia content, one or more query rewrite candidates based on entities associated with the multimedia content and the one or more terms in the query, wherein the entities include values characterizing one or more objects represented in the multimedia content, and wherein generating the one or more query rewrite candidates comprises: scoring the one or more extracted entities based on one or more of: a time at which the extracted entities are annotated in the multimedia content or based on co-occurrences of n-grams in a query repository, the n-grams in the query repository each being a contiguous sequence of n items from a given sequence of text or speech, and the n-grams in the query repository including unigrams, bigrams, tri grams, and four-grams, ranking the extracted entities based on the scoring, and combining one or more of the terms of the query with one or more scored extracted entities to generate the one or more query rewrite candidates; providing the one or more query rewrite candidates to a search engine; scoring the one or more query rewrite candidates based on characteristics of respective result sets resulting from the providing; ranking the scored one or more query rewrite candidates based on their respective scores; rewriting the query related to the multimedia content based on a particular ranked query rewrite candidate; and providing for display, responsive to the query related to the multimedia content, a result set from the search engine based on the rewritten query. 12. The non-transitory machine-readable medium of claim 11 , wherein rewriting the query related to the multimedia content includes replacing the query with the particular ranked query rewrite candidate. | 0.792857 |
8,300,023 | 39 | 44 | 39. A non-transitory, computer-readable medium having stored thereon processor-executable instructions configured to cause a processor to perform operations, comprising: receiving a series of coordinates of a series of user touches on the touch sensitive surface; correlating a plurality of keys with the received series of coordinates; determining an average of received coordinates correlated with each of the plurality of keys, wherein determining the average of received coordinates correlated with each of the plurality of keys comprises: calculating a variability of key-strike locations for each of the plurality of keys; determining when the calculated variability of key-strike locations for each of the plurality of keys has plateaued; and calculating an average of coordinate key strike locations for each of the plurality of keys once the variability of key strike locations has plateaued; saving the calculated average coordinates for each of the plurality of keys in keypad layout data; and generating an image of a virtual keypad using the keypad layout data. | 39. A non-transitory, computer-readable medium having stored thereon processor-executable instructions configured to cause a processor to perform operations, comprising: receiving a series of coordinates of a series of user touches on the touch sensitive surface; correlating a plurality of keys with the received series of coordinates; determining an average of received coordinates correlated with each of the plurality of keys, wherein determining the average of received coordinates correlated with each of the plurality of keys comprises: calculating a variability of key-strike locations for each of the plurality of keys; determining when the calculated variability of key-strike locations for each of the plurality of keys has plateaued; and calculating an average of coordinate key strike locations for each of the plurality of keys once the variability of key strike locations has plateaued; saving the calculated average coordinates for each of the plurality of keys in keypad layout data; and generating an image of a virtual keypad using the keypad layout data. 44. The non-transitory computer-readable medium of claim 39 , wherein the stored processor-executable instructions are configured to cause the processor to perform operations further comprising: monitoring typing on the virtual keypad on the touch sensitive surface; identifying an adjacent key typing error; determining a correct key associated with the adjacent key typing error; updating the average coordinate for the correct key based upon received coordinates for the typed keystroke; and saving the updated average coordinates with the correct key in the keypad layout data. | 0.529173 |
6,133,904 | 20 | 21 | 20. A computer readable medium according to claim 19, wherein said reproducing step displays said image on a display, and further comprising processing steps designating one or more areas of the displayed image to be altered. | 20. A computer readable medium according to claim 19, wherein said reproducing step displays said image on a display, and further comprising processing steps designating one or more areas of the displayed image to be altered. 21. A computer readable medium according to claim 20, wherein a user moves a pointing device across an area to be changed in order to designate said one or more areas of the displayed image, and wherein said changing step determines the statistical characteristics of the hue values of the pixels traced by said pointing device, and wherein said changing step is arranged to change the hue value of all pixels in the image having a hue value similar to the determined statistical characteristics. | 0.89118 |
7,685,100 | 1 | 6 | 1. A method in a computing device for forecasting frequency of a query, the frequency of the query being a number of times the query is submitted to a search engine during an interval, the method comprising: determining whether the query is time-dependent or time-independent by analyzing frequencies of the query during past intervals; when it is determined that the query is time-dependent, generating a time-dependent query model to predict the frequency of the query at a future interval, the time-dependent model being derived from the frequency of the query during the past intervals; generating a predicted frequency for the query during a future interval using the generated time-dependent query model; and storing an indication of the predicted frequency generated using the time-dependent query model; and; when it is determined that the query is time-independent, generating a time-independent query model to predict the frequency of the query at a future interval, the time-independent model being derived from the frequency of the query and the frequency of another query during the past intervals; and generating a predicted frequency of the query during a future interval using the generated time-independent query model; and storing an indication of the predicted frequency generated using the time-independent query model. | 1. A method in a computing device for forecasting frequency of a query, the frequency of the query being a number of times the query is submitted to a search engine during an interval, the method comprising: determining whether the query is time-dependent or time-independent by analyzing frequencies of the query during past intervals; when it is determined that the query is time-dependent, generating a time-dependent query model to predict the frequency of the query at a future interval, the time-dependent model being derived from the frequency of the query during the past intervals; generating a predicted frequency for the query during a future interval using the generated time-dependent query model; and storing an indication of the predicted frequency generated using the time-dependent query model; and; when it is determined that the query is time-independent, generating a time-independent query model to predict the frequency of the query at a future interval, the time-independent model being derived from the frequency of the query and the frequency of another query during the past intervals; and generating a predicted frequency of the query during a future interval using the generated time-independent query model; and storing an indication of the predicted frequency generated using the time-independent query model. 6. The method of claim 1 wherein the generating of the time-independent query model includes identifying queries that are causally related to the query and the time-independent query model predicts frequency of the query based on the frequency of the causally related queries. | 0.629032 |
8,086,997 | 1 | 7 | 1. A computer implemented method for detecting aspectual behavior in unified modeling language artifacts, the computer method comprising: representing static and dynamic properties of the unified modeling language artifacts in a set of production rules; creating a set of bit representations of method invocations found in the set of production rules; determining whether common sub-sequences exist in the set of bit representations; identifying a set of aspects within the production rules responsive to a determination that the common sub-sequences exist; and modifying the unified modeling language artifacts. | 1. A computer implemented method for detecting aspectual behavior in unified modeling language artifacts, the computer method comprising: representing static and dynamic properties of the unified modeling language artifacts in a set of production rules; creating a set of bit representations of method invocations found in the set of production rules; determining whether common sub-sequences exist in the set of bit representations; identifying a set of aspects within the production rules responsive to a determination that the common sub-sequences exist; and modifying the unified modeling language artifacts. 7. The computer implemented method of claim 1 , wherein modifying the unified modeling language artifacts further comprises: modifying the unified modeling language artifacts in accordance with the set of aspects. | 0.879932 |
8,478,597 | 23 | 24 | 23. The non-transitory medium of claim 21 , wherein calculating the language model score comprises calculating a language model for the language of the non-native speaker and the second language. | 23. The non-transitory medium of claim 21 , wherein calculating the language model score comprises calculating a language model for the language of the non-native speaker and the second language. 24. The non-transitory medium of claim 23 , wherein calculating a language model for the language of the non-native speaker and the second language comprises phonetically transcribing the first language of the non-native speaker and the second language. | 0.941081 |
5,590,319 | 4 | 5 | 4. A query processor in accordance with claim 3, further comprising meta-data means for generating seventh signals indicative of the structures of the database engines and the data accessible by them, wherein said translator means further comprises semantic analyzer means for comparing said sixth signals and said seventh signals, and producing therefrom eighth signals indicative of said input query only if the structures of the database engines and the data accessible by them are compatible with the input query, said translator means further processing said eighth signals to produce said second signals. | 4. A query processor in accordance with claim 3, further comprising meta-data means for generating seventh signals indicative of the structures of the database engines and the data accessible by them, wherein said translator means further comprises semantic analyzer means for comparing said sixth signals and said seventh signals, and producing therefrom eighth signals indicative of said input query only if the structures of the database engines and the data accessible by them are compatible with the input query, said translator means further processing said eighth signals to produce said second signals. 5. A query processor in accordance with claim 4, wherein said translator means further comprises normalizer means for receiving said eighth signals and producing therefrom, ninth signals corresponding to said input query cast in terms of base tables and without references to views, said translator means further processing said ninth signals to produce said second signals. | 0.76942 |
7,885,807 | 1 | 3 | 1. Apparatus for translating a body of text in an initial language into a target language, comprising an input device for receiving a body of text comprising a plurality of elements, an analyzer for analyzing said text and identifying one or more possible characters of said initial language corresponding to respective said elements, a data storage system comprising a data handler for generating a text array comprising an array of cells, each cell being representative of an element and its location within said body of text and containing data representative of said element, the data storage system being arranged to map said array of cells onto a linear storage media, a multi-dimensional storage grid containing one or more possible translation into said target language, including alternative translations and spelling variations, corresponding to respective characters of said initial language, an analysis module for receiving a stream of elements from said linear storage media and assigning in respect of each element one or more vector paths indicative of one or more respective translations in said storage grid corresponding to said respective element, the system further being arranged to generate data linking said vectors to respective cells of said text array of said data storage system. | 1. Apparatus for translating a body of text in an initial language into a target language, comprising an input device for receiving a body of text comprising a plurality of elements, an analyzer for analyzing said text and identifying one or more possible characters of said initial language corresponding to respective said elements, a data storage system comprising a data handler for generating a text array comprising an array of cells, each cell being representative of an element and its location within said body of text and containing data representative of said element, the data storage system being arranged to map said array of cells onto a linear storage media, a multi-dimensional storage grid containing one or more possible translation into said target language, including alternative translations and spelling variations, corresponding to respective characters of said initial language, an analysis module for receiving a stream of elements from said linear storage media and assigning in respect of each element one or more vector paths indicative of one or more respective translations in said storage grid corresponding to said respective element, the system further being arranged to generate data linking said vectors to respective cells of said text array of said data storage system. 3. Apparatus according to claim 1 , further comprising a grammar analyzer for retrieving streams of elements from said data storage system, identifying, using said linking data, the vector paths associated with respective elements and determining therewith the possible translations of said elements from said multi-dimensional storage grid, analyzing said possible translations in conjunction with one or more inter-sentence grammatical rules and discarding any possible translations that do not comply with said rules. | 0.698026 |
9,064,006 | 16 | 17 | 16. The system of claim 15 , wherein the statistical machine translation model is trained according to a plurality of mined query pairs each comprising a previous natural language query and an associated previous keyword-based query. | 16. The system of claim 15 , wherein the statistical machine translation model is trained according to a plurality of mined query pairs each comprising a previous natural language query and an associated previous keyword-based query. 17. The system of claim 16 , wherein the previous natural language query is identified according to a domain independent salient phrase. | 0.926247 |
9,336,271 | 3 | 4 | 3. The method recited in claim 1 , further comprising: generating a heuristic query plan for the query; enumerating a heuristic query plan from a multijoin to generate a first plurality of substitutes for the multijoin; assigning a potential to each of the first plurality of substitutes, wherein the potential comprises a potential to produce a low cost query plan; and generating a query plan based on the assigned potential and the first plurality of substitutes. | 3. The method recited in claim 1 , further comprising: generating a heuristic query plan for the query; enumerating a heuristic query plan from a multijoin to generate a first plurality of substitutes for the multijoin; assigning a potential to each of the first plurality of substitutes, wherein the potential comprises a potential to produce a low cost query plan; and generating a query plan based on the assigned potential and the first plurality of substitutes. 4. The method recited in claim 3 , wherein assigning the potential comprises: determining a dataflow for each of the first plurality of substitutes; ranking the first plurality of substitutes in ascending order of the dataflow; and determining the potential based on the ranking. | 0.88198 |
10,042,506 | 13 | 14 | 13. The method of claim 8 , wherein the memory includes a story web generator. | 13. The method of claim 8 , wherein the memory includes a story web generator. 14. The method of claim 13 , wherein the processor is configured to use the story web generator in creating the story web. | 0.974009 |
8,898,557 | 4 | 5 | 4. A computer-implemented method comprising: receiving, at a handheld mobile computing device including one or more processors, a command from a server, the command being associated with a user request received at another computing device for a rendering of a document being edited in document editing software executing at the other computing device, wherein the server provides a user interface element to the other computing device in response to determining that a user is logged into a same account at both the handheld mobile computing device and the other computing device, wherein receipt of the user interface element causes the other computing device to display the user interface element in a print menu of the document editing software, and wherein the user request is indicative of a selection of the user interface element at the other computing device; obtaining, at the handheld mobile computing device, the rendering of the document; automatically displaying, at a touch display of the handheld mobile computing device, the rendering of the document in response to the command; receiving, via the touch display of the handheld mobile computing device, handwritten annotations to the rendering of the document from the user; and generating, at the handheld mobile computing device, an annotated version of the rendering by overlaying the handwritten annotations over the rendering of the document. | 4. A computer-implemented method comprising: receiving, at a handheld mobile computing device including one or more processors, a command from a server, the command being associated with a user request received at another computing device for a rendering of a document being edited in document editing software executing at the other computing device, wherein the server provides a user interface element to the other computing device in response to determining that a user is logged into a same account at both the handheld mobile computing device and the other computing device, wherein receipt of the user interface element causes the other computing device to display the user interface element in a print menu of the document editing software, and wherein the user request is indicative of a selection of the user interface element at the other computing device; obtaining, at the handheld mobile computing device, the rendering of the document; automatically displaying, at a touch display of the handheld mobile computing device, the rendering of the document in response to the command; receiving, via the touch display of the handheld mobile computing device, handwritten annotations to the rendering of the document from the user; and generating, at the handheld mobile computing device, an annotated version of the rendering by overlaying the handwritten annotations over the rendering of the document. 5. The computer-implemented method of claim 4 , wherein the annotated version of the rendering includes a plurality of layers, the plurality of layers including the rendering of the document and one or more layers of the handwritten annotations made by the user via the handheld mobile computing device. | 0.889738 |
8,756,279 | 10 | 11 | 10. A computer-readable storage medium persistently storing a program, wherein the program, when executed, instructs one or more processors to perform the following operations: receive a list of websites having online publications; gather counts of user signals for each online publication on each website; determine content descriptors for each online publication; count the online publications at each website associated with each content descriptor; and count the user signals at each website associated with each content descriptor. | 10. A computer-readable storage medium persistently storing a program, wherein the program, when executed, instructs one or more processors to perform the following operations: receive a list of websites having online publications; gather counts of user signals for each online publication on each website; determine content descriptors for each online publication; count the online publications at each website associated with each content descriptor; and count the user signals at each website associated with each content descriptor. 11. The computer-readable storage medium of claim 10 , further comprising the operation of displaying the content descriptors for each website in a graphic in a graphical user interface, wherein the size of each content descriptor in the graphic reflects the count of online publications associated with the content descriptor and wherein the color of each content descriptor in the graphic reflects the count of user signals associated with the content descriptor. | 0.59282 |
8,549,397 | 5 | 10 | 5. A system comprising: one or more processors; one or more computer storage media for storing instructions, which when executed by the one or more processors, cause the one or more processors to: compute style rules for a plurality of elements of an original markup language video content to define pseudo-classes which preserve a dynamic layout, presentation, rendering, and user interface interaction of a plurality of elements of the content; transcode the plurality of elements and the style rules into a binary format video content with a document object model hierarchy via a routine specific to a predetermined client, the binary format video content including a list of the pseudo-classes for preserving a layout, rendering, user interface (UI) interaction, and dynamic aspect of the original markup language video, wherein the document object model hierarchy includes nodes having pre-cascaded style rules; and a network interface to communicate the binary format video content for presentation over a network to the predetermined client. | 5. A system comprising: one or more processors; one or more computer storage media for storing instructions, which when executed by the one or more processors, cause the one or more processors to: compute style rules for a plurality of elements of an original markup language video content to define pseudo-classes which preserve a dynamic layout, presentation, rendering, and user interface interaction of a plurality of elements of the content; transcode the plurality of elements and the style rules into a binary format video content with a document object model hierarchy via a routine specific to a predetermined client, the binary format video content including a list of the pseudo-classes for preserving a layout, rendering, user interface (UI) interaction, and dynamic aspect of the original markup language video, wherein the document object model hierarchy includes nodes having pre-cascaded style rules; and a network interface to communicate the binary format video content for presentation over a network to the predetermined client. 10. The system as recited in claim 5 , wherein the system is a server at a headend of a MultiSystem Operator. | 0.909917 |
9,910,589 | 2 | 3 | 2. The computer implemented method according to claim 1 further comprising determining priorities of respective characters associated with the plurality of recognition zones based on data related to vocabulary, and wherein the selecting the first character is further based on priorities of the plurality of recognition zones. | 2. The computer implemented method according to claim 1 further comprising determining priorities of respective characters associated with the plurality of recognition zones based on data related to vocabulary, and wherein the selecting the first character is further based on priorities of the plurality of recognition zones. 3. The computer implemented method according to claim 2 , wherein the weights are determined further based on the priorities with reference to the respective characters. | 0.946485 |
7,694,227 | 1 | 7 | 1. A method of obtaining a list of resource links indexed by categories in a interlinked category structure to be presented to a user via a user interface, the resource links pointing to resources on a network, the method comprising the following steps to be carried out by a computer system: monitoring users' interactions with resource links by: for users' interaction with a category in the interlinked category structure, generating a usage entry in a usage table on a server computer, wherein each usage entry includes a set of activity parameters including a link ID and a user ID; analyzing a user's interaction with the resource links placed in said category, including retrieving, from the usage table, the user's entries for resource links within said category; and calculating a user rating for the user in said category; rating resource links from categories in the category structure, the rating including: retrieving resource links placed within a given category; and rating the retrieved resource links using accumulated sets of activity parameters in the usage table, the resource links' ratings being based on calculated user ratings of a plurality of users who have previously interacted with a resource link within the given category. | 1. A method of obtaining a list of resource links indexed by categories in a interlinked category structure to be presented to a user via a user interface, the resource links pointing to resources on a network, the method comprising the following steps to be carried out by a computer system: monitoring users' interactions with resource links by: for users' interaction with a category in the interlinked category structure, generating a usage entry in a usage table on a server computer, wherein each usage entry includes a set of activity parameters including a link ID and a user ID; analyzing a user's interaction with the resource links placed in said category, including retrieving, from the usage table, the user's entries for resource links within said category; and calculating a user rating for the user in said category; rating resource links from categories in the category structure, the rating including: retrieving resource links placed within a given category; and rating the retrieved resource links using accumulated sets of activity parameters in the usage table, the resource links' ratings being based on calculated user ratings of a plurality of users who have previously interacted with a resource link within the given category. 7. A method according to claim 1 , wherein the resource links ratings are based at least in part on a timestamp submitted as part of the activity parameters. | 0.78841 |
8,127,220 | 11 | 20 | 11. A computer-implemented method, comprising: receiving a search query; providing a list of search results in response to the search query; receiving selection of one of the search results in the list of search results; identifying links in a document corresponding to the selected search result; determining a score for one of the links based on a degree of match between the search query and a content of a linked document pointed to by the one of the links; modifying the document based on the determined score for the one of the links; and providing the modified document. | 11. A computer-implemented method, comprising: receiving a search query; providing a list of search results in response to the search query; receiving selection of one of the search results in the list of search results; identifying links in a document corresponding to the selected search result; determining a score for one of the links based on a degree of match between the search query and a content of a linked document pointed to by the one of the links; modifying the document based on the determined score for the one of the links; and providing the modified document. 20. The method of claim 11 , wherein modifying the document includes: annotating the one of the links, within the document, based on the determined score for the one of the links. | 0.951306 |
10,083,073 | 1 | 2 | 1. A computer-implemented method for monitoring performance in a distributed computing environment, comprising: providing a repository that stores a plurality of existing event records, where each existing event record describes an event in the distributed computing environment; receiving, by an event correlator, an incoming event record which describes an event in the distributed computing environment; determining whether the incoming event record indicates an anomalous operation condition of an entity in the distributed computing environment by comparing the event in the incoming event record to a plurality of historic events and discarding the event record in response to a determination that the event record does not indicate an anomalous operation condition; forming a pair of records between the incoming event record and each existing event record in the plurality of existing event records; determining a first causality factor for each pair of records, where the causality factor describes probability that event described in the incoming event record is cause of an event described in a respective existing event record; determining a second causality factor for each pair of records, where the causality factor describes probability that event described in the incoming event record is an effect of an event described in a respective existing event record; and creating an event causality record from a given record pair and storing the event causality record in the repository when either the first causality factor or the second causality factor from the given record pair exceeds a threshold, where the event causality record describes a causal relationship between two events which occurred in the distributed computing environment. | 1. A computer-implemented method for monitoring performance in a distributed computing environment, comprising: providing a repository that stores a plurality of existing event records, where each existing event record describes an event in the distributed computing environment; receiving, by an event correlator, an incoming event record which describes an event in the distributed computing environment; determining whether the incoming event record indicates an anomalous operation condition of an entity in the distributed computing environment by comparing the event in the incoming event record to a plurality of historic events and discarding the event record in response to a determination that the event record does not indicate an anomalous operation condition; forming a pair of records between the incoming event record and each existing event record in the plurality of existing event records; determining a first causality factor for each pair of records, where the causality factor describes probability that event described in the incoming event record is cause of an event described in a respective existing event record; determining a second causality factor for each pair of records, where the causality factor describes probability that event described in the incoming event record is an effect of an event described in a respective existing event record; and creating an event causality record from a given record pair and storing the event causality record in the repository when either the first causality factor or the second causality factor from the given record pair exceeds a threshold, where the event causality record describes a causal relationship between two events which occurred in the distributed computing environment. 2. The method of claim 1 further comprises determining a causality graph for each pair of records, where the causality graph describes possible topological paths between events described in the respective pair of records. | 0.838214 |
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