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9,760,571 | 13 | 14 | 13. The server of claim 12 wherein the catalog defines: an identity of, for each field in the collection, a type of data values populated for the field; if the field is a mixed type, a percentage of data values corresponding to each data type; a count of populated data values for each type; and for each data value, a reference to a location of the data value in the collection. | 13. The server of claim 12 wherein the catalog defines: an identity of, for each field in the collection, a type of data values populated for the field; if the field is a mixed type, a percentage of data values corresponding to each data type; a count of populated data values for each type; and for each data value, a reference to a location of the data value in the collection. 14. The server of claim 13 wherein the collection includes a set of documents, each of the documents including at least one field, and the application is further operable to: for each document compute a field name based on the type and a name of the field in the document; create or find the computed field name in the catalog; update the count and percentage of documents populated with the field; and maintain a mapping from the computed field name to a corresponding field in the tabular DB command. | 0.804059 |
9,342,507 | 18 | 19 | 18. A system for automatically generating text, the system comprising: at least one processor configured to perform: accessing a template that includes at least one tag that identifies at least one list of elements, the at least one list of elements comprising a set of elements; determining a format for the at least one list of elements at least in part by determining, based on a characteristic of the set of elements, whether the at least one list of elements is to be formatted either as an enumerated list contained within a single sentence or as at least a part of a single textual sentence; and using the at least one list of elements and the determined format to automatically generate output text that includes the at least one list of elements formatted according to the determined format, the determined format indicating whether the at least one list of elements is to be formatted either as an enumerated list contained within a single sentence or as at least a part of a single textual sentence. | 18. A system for automatically generating text, the system comprising: at least one processor configured to perform: accessing a template that includes at least one tag that identifies at least one list of elements, the at least one list of elements comprising a set of elements; determining a format for the at least one list of elements at least in part by determining, based on a characteristic of the set of elements, whether the at least one list of elements is to be formatted either as an enumerated list contained within a single sentence or as at least a part of a single textual sentence; and using the at least one list of elements and the determined format to automatically generate output text that includes the at least one list of elements formatted according to the determined format, the determined format indicating whether the at least one list of elements is to be formatted either as an enumerated list contained within a single sentence or as at least a part of a single textual sentence. 19. The system of claim 18 , wherein determining the format comprises determining at least one formatting parameter for the at least one list of elements, and wherein the at least one formatting parameter indirectly specifies whether the at least one list is to be formatted either as an enumerated list contained within a single sentence or as a single textual sentence by specifying a limit on a number of elements permitted in a textual sentence format of the at least one list. | 0.630568 |
9,569,554 | 9 | 11 | 9. The method of claim 8 , wherein reducing the volume includes lowering the resolution of the image. | 9. The method of claim 8 , wherein reducing the volume includes lowering the resolution of the image. 11. The method of claim 9 , wherein lowering the resolution of the image is performed as part of converting the image. | 0.966515 |
9,799,330 | 17 | 19 | 17. A non-transitory computer-readable storage medium having embodied thereon instructions, which, when executed by at least one processor, perform steps of a method, the method comprising: assigning weights to audio streams, the audio streams being provided substantially synchronously by a plurality of audio devices, the weights depending on quality of the audio streams, wherein the assigning weights includes generating an acoustic activity map by locating, identifying and mapping target sounds and noise sources in at least one of a single room and multi-room environment, so as to create a multidimensional acoustic view of the environment; based on the weights, performing noise suppression processing on the audio streams to generate a cleaned voice signal; providing the cleaned voice signal from the noise suppression processing to at least one remote device for further processing; and based on the acoustic activity map, selecting an optimal one of the plurality of audio devices to communicate with the user. | 17. A non-transitory computer-readable storage medium having embodied thereon instructions, which, when executed by at least one processor, perform steps of a method, the method comprising: assigning weights to audio streams, the audio streams being provided substantially synchronously by a plurality of audio devices, the weights depending on quality of the audio streams, wherein the assigning weights includes generating an acoustic activity map by locating, identifying and mapping target sounds and noise sources in at least one of a single room and multi-room environment, so as to create a multidimensional acoustic view of the environment; based on the weights, performing noise suppression processing on the audio streams to generate a cleaned voice signal; providing the cleaned voice signal from the noise suppression processing to at least one remote device for further processing; and based on the acoustic activity map, selecting an optimal one of the plurality of audio devices to communicate with the user. 19. The non-transitory computer-readable medium of claim 17 , wherein one or more of the plurality of audio devices is incorporated in an Internet of Things device. | 0.659751 |
9,152,324 | 8 | 14 | 8. One or more non-transitory computer-readable storage devices storing computer-executable instructions that, when executed by a computing device, cause the computing device to: display a web page, the web page comprising two or more hyperlinks, wherein the at least two of the hyperlinks are initially non-highlighted; following the initial display, receive a series of requests, based on non-alphanumeric character input, to navigate to one of the at least two non-highlighted hyperlinks that are included as part of the web page, wherein one of the two or more hyperlinks appear as a graphical image; determining which of the at least two non-highlighted hyperlinks to navigate to, the determination based on identifying the next hyperlink in an index of hyperlinks, the index comprised of sequential list of each hyperlink in the document; responsive to receiving the series of non-alphanumeric character based requests, present a focus shape to a first of the two or more hyperlinks based on the first received input in the series of non-alphanumeric character based requests, and after presenting the focus shape to a first of the two or more hyperlinks, presenting a focus shape to the second of two or more hyperlinks based on the second received input in the series of non-alphanumeric character based requests; and wherein the hyperlink to which the focus shape has been presented is activated after receiving an activation request. | 8. One or more non-transitory computer-readable storage devices storing computer-executable instructions that, when executed by a computing device, cause the computing device to: display a web page, the web page comprising two or more hyperlinks, wherein the at least two of the hyperlinks are initially non-highlighted; following the initial display, receive a series of requests, based on non-alphanumeric character input, to navigate to one of the at least two non-highlighted hyperlinks that are included as part of the web page, wherein one of the two or more hyperlinks appear as a graphical image; determining which of the at least two non-highlighted hyperlinks to navigate to, the determination based on identifying the next hyperlink in an index of hyperlinks, the index comprised of sequential list of each hyperlink in the document; responsive to receiving the series of non-alphanumeric character based requests, present a focus shape to a first of the two or more hyperlinks based on the first received input in the series of non-alphanumeric character based requests, and after presenting the focus shape to a first of the two or more hyperlinks, presenting a focus shape to the second of two or more hyperlinks based on the second received input in the series of non-alphanumeric character based requests; and wherein the hyperlink to which the focus shape has been presented is activated after receiving an activation request. 14. The one or more non-transitory computer-readable storage devices of claim 8 , wherein the series of non-alphanumeric character based requests are received responsive to input to a keyboard. | 0.782167 |
8,682,647 | 25 | 26 | 25. The method of claim 24 , wherein the score comprises a product of at least (1) the frequency of a plurality of n-grams appearing in the candidate sentence, (2) the measure of commonality between the candidate sentence and the query, and (3) the rank of the candidate sentence according to the ranking of the plurality of documents. | 25. The method of claim 24 , wherein the score comprises a product of at least (1) the frequency of a plurality of n-grams appearing in the candidate sentence, (2) the measure of commonality between the candidate sentence and the query, and (3) the rank of the candidate sentence according to the ranking of the plurality of documents. 26. The method of claim 25 , wherein the measure of commonality comprises a count of common words. | 0.963731 |
7,861,161 | 21 | 28 | 21. A system for a report to be executed on a reporting system comprising of: report selection means embodied on a computer-readable medium that enables a report creator to define one or more of a template, filter, or properties thereof with a prompt object; wherein the prompt object comprises: a question to be asked of a user; a prompt type; and at least one validation property, wherein the prompt object is an object separate from the report such that the prompt object may be used more than once in a single report or may be used in more than one report. | 21. A system for a report to be executed on a reporting system comprising of: report selection means embodied on a computer-readable medium that enables a report creator to define one or more of a template, filter, or properties thereof with a prompt object; wherein the prompt object comprises: a question to be asked of a user; a prompt type; and at least one validation property, wherein the prompt object is an object separate from the report such that the prompt object may be used more than once in a single report or may be used in more than one report. 28. The system of claim 21 wherein the template comprises a set of templates properties and the filter comprises a set of filter properties and wherein every template and filter property may be specified as a prompt object. | 0.802305 |
8,495,490 | 1 | 2 | 1. A method comprising: providing scanned document analysis data including classification of at least one of a term, a subject, and a theme used in a plurality of scanned documents; generating a summary output from said analyzed scanned document data; rendering a visualization of said summary output; saving said summary output as metadata; mining said metadata for comparison with other summary output for archiving and retrieving said plurality of scanned documents according to said summary output; providing scanned document analysis data including frequency of usage of each one of a plurality of terms per page of said document(s); generating a searchable histogram electronic file for each respective term(s) of said plurality of terms; selecting at least one term from said plurality of terms for viewing as a histogram; selecting a particular searchable histogram for said selected term(s) from said generated plurality of searchable histograms; said selected searchable histogram having a first axis representing frequency of usage of said selected term(s) and a second axis representing page number of said document(s); rendering said searchable histogram on a graphical user interface, receiving a first clicking or scrolling signal representing selection of a first page of said document(s) by a user clicking or scrolling a visual icon/indicator on said graphical user interface; rendering concurrently or sequentially on said graphical user interface said searchable histogram and content of said selected first page in response to receiving said first clicking or scrolling signal; receiving a second clicking or scrolling signal representing selection of a second page of said document(s) by a user clicking or scrolling a visual icon/indicator on said graphical user interface; and rendering concurrently or sequentially on said graphical user interface said searchable histogram and content of said second page in response to receiving said second clicking or scrolling signal. | 1. A method comprising: providing scanned document analysis data including classification of at least one of a term, a subject, and a theme used in a plurality of scanned documents; generating a summary output from said analyzed scanned document data; rendering a visualization of said summary output; saving said summary output as metadata; mining said metadata for comparison with other summary output for archiving and retrieving said plurality of scanned documents according to said summary output; providing scanned document analysis data including frequency of usage of each one of a plurality of terms per page of said document(s); generating a searchable histogram electronic file for each respective term(s) of said plurality of terms; selecting at least one term from said plurality of terms for viewing as a histogram; selecting a particular searchable histogram for said selected term(s) from said generated plurality of searchable histograms; said selected searchable histogram having a first axis representing frequency of usage of said selected term(s) and a second axis representing page number of said document(s); rendering said searchable histogram on a graphical user interface, receiving a first clicking or scrolling signal representing selection of a first page of said document(s) by a user clicking or scrolling a visual icon/indicator on said graphical user interface; rendering concurrently or sequentially on said graphical user interface said searchable histogram and content of said selected first page in response to receiving said first clicking or scrolling signal; receiving a second clicking or scrolling signal representing selection of a second page of said document(s) by a user clicking or scrolling a visual icon/indicator on said graphical user interface; and rendering concurrently or sequentially on said graphical user interface said searchable histogram and content of said second page in response to receiving said second clicking or scrolling signal. 2. The method of claim 1 , wherein generating a summary output comprises generating a summary output electronic file comprising a hierarchal list of said term(s), said subject(s), and said theme(s) used in said scanned document(s). | 0.913677 |
9,324,330 | 15 | 16 | 15. The computational method of claim 14 , wherein the pitch shifting employs cross synthesis of a glottal pulse. | 15. The computational method of claim 14 , wherein the pitch shifting employs cross synthesis of a glottal pulse. 16. The computational method of claim 15 , wherein the cross synthesis uses a glottal pulse as source excitation and spectrum of the input speech as target spectrum. | 0.933947 |
9,330,311 | 5 | 9 | 5. A method comprising: receiving an image file representing an image comprising text; determining, by a processing device, a plurality of portions of the image respectively corresponding to a plurality of letters of the text; determining, for a first letter of the plurality of letters, a set of letter properties comprising at least one dependent letter property and at least one independent letter property, wherein each of the at least one dependent letter property of the first letter is dependent on another letter of the plurality of letters and each of the at least one independent letter property of the first letter is independent of all other letters of the plurality of letters; and classifying the first letter into one of a plurality of letterform classes based on the set of letter properties. | 5. A method comprising: receiving an image file representing an image comprising text; determining, by a processing device, a plurality of portions of the image respectively corresponding to a plurality of letters of the text; determining, for a first letter of the plurality of letters, a set of letter properties comprising at least one dependent letter property and at least one independent letter property, wherein each of the at least one dependent letter property of the first letter is dependent on another letter of the plurality of letters and each of the at least one independent letter property of the first letter is independent of all other letters of the plurality of letters; and classifying the first letter into one of a plurality of letterform classes based on the set of letter properties. 9. The method of claim 5 , wherein the at least one independent letter property comprises at least one of an edge trace or an ink trace. | 0.903683 |
7,548,899 | 14 | 17 | 14. A computer-readable medium comprising computer-readable instructions configured to cause a computing device to: send a first menu list of words or phrases associated with a plurality of concepts to a second device; receive a first selection of at least one of the words or phrases in the first menu list from the second device, the received first selection identifying a concept for the query to be formed; identify a second menu list of words or phrases based on the received first selection; send the identified second menu list to the second device; receive a second selection of at least one of the words or phrases in the second menu list from the second device, the second selection identifying a first segment of the query; form the query as a natural language query based at least in part on the received second selection, wherein the natural language query does not include the identified concept; and provide, to the second device, a response to the query. | 14. A computer-readable medium comprising computer-readable instructions configured to cause a computing device to: send a first menu list of words or phrases associated with a plurality of concepts to a second device; receive a first selection of at least one of the words or phrases in the first menu list from the second device, the received first selection identifying a concept for the query to be formed; identify a second menu list of words or phrases based on the received first selection; send the identified second menu list to the second device; receive a second selection of at least one of the words or phrases in the second menu list from the second device, the second selection identifying a first segment of the query; form the query as a natural language query based at least in part on the received second selection, wherein the natural language query does not include the identified concept; and provide, to the second device, a response to the query. 17. The computer-readable medium of claim 14 , wherein the instructions further cause the computing device to: form a request for the response to the formed query; and transmit the request to a third device. | 0.772527 |
7,607,081 | 1 | 5 | 1. A method for representing header and footer structures in a markup language document, comprising: determining properties corresponding to a mini-document of at least one section of a word processing application document generated on a word processing application, wherein the mini-document includes a body portion, wherein the mini-document includes at least one member of a group comprising: a header and a footer; individually mapping the properties of the mini-document into a markup language element that is stored with each of the markup language section properties of the application document, wherein individually mapping the properties includes: setting an option element in the mini-document markup language element, wherein the option element includes at least one member of a group comprising: a header value and a footer value, setting a type attribute in the mini-document markup language element, wherein the type attribute includes a value that indicates an occurrence pattern of the body of the mini-document within the application document, setting page size properties of the application document in the section properties of the application document, wherein the page size properties includes a size value of the page, and setting a margin properties of the application document in the section properties of the application document, wherein the margin properties include a top margin value, a bottom margin value, a left margin value, a right margin value and a position value of the location of the mini-document within the section of the application document; storing each of the individually mapped properties of the mini-document in the markup language document; validating the markup language document in accordance with a native schema of the word processing application having definitions for the mini-document, wherein the definitions for the mini-document include a definition for headers, a definition for footers, a definition for a context free chunk, a definition for a paragraph element, a definition for a table element and a definition for a mini-document type; and parsing and rendering the markup language document on an application other than the word processing application, wherein the application other than the word processing application does not have access to the native schema of the word processing application having the definitions of the mini-document, wherein the individually mapped option element in the section properties causes the rendering of at least one member of a group comprising, a header according to the header value for the section, and a footer according to the footer value for the section, wherein the individually mapped type attribute in the section properties causes the body portion of the mini-document to be rendered in accordance with the occurrence pattern of the section, wherein the value is at least one member of a group comprising: an odd page value for the section and an even page value for the section, wherein the individually mapped page size properties for the section causes the page to be rendered according to the size value of the page of the section, and wherein the individually mapped margin properties for the section causes the rendering of a top margin according to the top margin value, a bottom margin according to the bottom margin value, a left margin according to the left margin value, a right margin according to a right margin value and a mini-document position according to the position value of the location of the mini-document within the section. | 1. A method for representing header and footer structures in a markup language document, comprising: determining properties corresponding to a mini-document of at least one section of a word processing application document generated on a word processing application, wherein the mini-document includes a body portion, wherein the mini-document includes at least one member of a group comprising: a header and a footer; individually mapping the properties of the mini-document into a markup language element that is stored with each of the markup language section properties of the application document, wherein individually mapping the properties includes: setting an option element in the mini-document markup language element, wherein the option element includes at least one member of a group comprising: a header value and a footer value, setting a type attribute in the mini-document markup language element, wherein the type attribute includes a value that indicates an occurrence pattern of the body of the mini-document within the application document, setting page size properties of the application document in the section properties of the application document, wherein the page size properties includes a size value of the page, and setting a margin properties of the application document in the section properties of the application document, wherein the margin properties include a top margin value, a bottom margin value, a left margin value, a right margin value and a position value of the location of the mini-document within the section of the application document; storing each of the individually mapped properties of the mini-document in the markup language document; validating the markup language document in accordance with a native schema of the word processing application having definitions for the mini-document, wherein the definitions for the mini-document include a definition for headers, a definition for footers, a definition for a context free chunk, a definition for a paragraph element, a definition for a table element and a definition for a mini-document type; and parsing and rendering the markup language document on an application other than the word processing application, wherein the application other than the word processing application does not have access to the native schema of the word processing application having the definitions of the mini-document, wherein the individually mapped option element in the section properties causes the rendering of at least one member of a group comprising, a header according to the header value for the section, and a footer according to the footer value for the section, wherein the individually mapped type attribute in the section properties causes the body portion of the mini-document to be rendered in accordance with the occurrence pattern of the section, wherein the value is at least one member of a group comprising: an odd page value for the section and an even page value for the section, wherein the individually mapped page size properties for the section causes the page to be rendered according to the size value of the page of the section, and wherein the individually mapped margin properties for the section causes the rendering of a top margin according to the top margin value, a bottom margin according to the bottom margin value, a left margin according to the left margin value, a right margin according to a right margin value and a mini-document position according to the position value of the location of the mini-document within the section. 5. The method of claim 1 , wherein the markup language document is manipulated on a server to substantially reproduce the mini-document of the application document notwithstanding the presence of an application that generated the markup language document. | 0.748024 |
8,068,595 | 2 | 11 | 2. A method for providing a multi-modal communications infrastructure for automated call center operation, comprising: accepting a multi-modal call from a caller through a telephony interface and automatically assigning the multi-modal call through a session manager to a session under operation of a live agent; receiving voice communications and text messages that simultaneously originate from the caller; converting incoming speech from the voice communications in the multi-modal call into transcribed text; matching at least one of the text messages from the caller with the transcribed text of the incoming speech during the session that is on-going; and progressively processing the transcribed text and the incoming text messaging during the session through an agent application by performing a customer support scenario interactively monitored and controlled by the live agent. | 2. A method for providing a multi-modal communications infrastructure for automated call center operation, comprising: accepting a multi-modal call from a caller through a telephony interface and automatically assigning the multi-modal call through a session manager to a session under operation of a live agent; receiving voice communications and text messages that simultaneously originate from the caller; converting incoming speech from the voice communications in the multi-modal call into transcribed text; matching at least one of the text messages from the caller with the transcribed text of the incoming speech during the session that is on-going; and progressively processing the transcribed text and the incoming text messaging during the session through an agent application by performing a customer support scenario interactively monitored and controlled by the live agent. 11. A method according to claim 2 , further comprising: flagging the incoming text messaging as verbatim caller data; and storing the flagged incoming text messaging. | 0.905467 |
8,290,895 | 20 | 21 | 20. The computer-readable storage medium of claim 19 , wherein the language objects are associated with frequency objects containing frequency values for the language objects. | 20. The computer-readable storage medium of claim 19 , wherein the language objects are associated with frequency objects containing frequency values for the language objects. 21. The computer-readable storage medium of claim 20 , wherein the language objects are assigned frequency values higher than objects contained in a generic word list. | 0.856775 |
9,298,816 | 1 | 2 | 1. A method of presenting search results on a computing device, the method comprising: a computing device transmitting a search query in a natural or structured query language to a search engine server, the search engine server processing the search query through at least one index based upon syntax, semantics, or a combination thereof extracted from the search query, the at least one index including a semantic index representing words and semantic meaning of the words, the search engine server utilizing the semantic index to determine a meaning of the search query; receiving, by the computing device from the search engine server: search results in response to the search query from the computing device, a plurality of facets that matched the search query or are relevant to the meaning of the search query, wherein the plurality of facets includes at least themes, organizations, locations, or document types, and faceted search results for the plurality of facets associated with the search results; displaying on the computing device the search results in a search engine interface of the search engine server; and in addition to the search results and in response to the search query, displaying in the search engine interface by the computing device one or more of the plurality of facets, wherein the plurality of facets includes semantic facets derived from semantic metadata encapsulated to pieces of content referenced in the faceted search results, wherein the semantic metadata includes editorial metadata, semantic annotations, or a combination thereof, wherein at least a first semantic facet of the semantic facets is instantiated from the semantic metadata in response to the search query, wherein at least a second semantic facet of the semantic facets is created from the semantic metadata in an enrichment process and stored in the semantic index, wherein each facet of the plurality of facets is configured for triggering its own faceted search results such that a set of faceted search results are displayed for each facet, wherein the search results and the faceted search results for the plurality of facets together form a current result set for the search query, and wherein each faceted search result of the set of faceted search results is displayed in association with a number of hits for each faceted search result and user interface elements for selectively filtering each faceted search result to navigate, refine, or filter the current result set for the search query. | 1. A method of presenting search results on a computing device, the method comprising: a computing device transmitting a search query in a natural or structured query language to a search engine server, the search engine server processing the search query through at least one index based upon syntax, semantics, or a combination thereof extracted from the search query, the at least one index including a semantic index representing words and semantic meaning of the words, the search engine server utilizing the semantic index to determine a meaning of the search query; receiving, by the computing device from the search engine server: search results in response to the search query from the computing device, a plurality of facets that matched the search query or are relevant to the meaning of the search query, wherein the plurality of facets includes at least themes, organizations, locations, or document types, and faceted search results for the plurality of facets associated with the search results; displaying on the computing device the search results in a search engine interface of the search engine server; and in addition to the search results and in response to the search query, displaying in the search engine interface by the computing device one or more of the plurality of facets, wherein the plurality of facets includes semantic facets derived from semantic metadata encapsulated to pieces of content referenced in the faceted search results, wherein the semantic metadata includes editorial metadata, semantic annotations, or a combination thereof, wherein at least a first semantic facet of the semantic facets is instantiated from the semantic metadata in response to the search query, wherein at least a second semantic facet of the semantic facets is created from the semantic metadata in an enrichment process and stored in the semantic index, wherein each facet of the plurality of facets is configured for triggering its own faceted search results such that a set of faceted search results are displayed for each facet, wherein the search results and the faceted search results for the plurality of facets together form a current result set for the search query, and wherein each faceted search result of the set of faceted search results is displayed in association with a number of hits for each faceted search result and user interface elements for selectively filtering each faceted search result to navigate, refine, or filter the current result set for the search query. 2. The method as claimed in claim 1 , further comprising: displaying search results for a subsequent search using all included or excluded faceted search results as additional search terms; and displaying all the included or excluded faceted search results that have been used as additional search terms in association with a user interlace element for deselecting the additional search terms. | 0.578326 |
9,223,868 | 4 | 5 | 4. The method of claim 1 , wherein: the first profile characterizes one or more respective interactions with electronic documents in each of the first result sets of electronic documents responsive to search queries of a first category, the search queries of the first category are selected from among a plurality of queries including the search queries of the first category and other search queries, the second profile characterizes one or more respective interactions with electronic documents in each of the second result sets of electronic documents responsive to search queries of the first category, and the indication indicates that the first scoring algorithm is better than the second scoring algorithm for scoring electronic documents responsive to search queries of the first category. | 4. The method of claim 1 , wherein: the first profile characterizes one or more respective interactions with electronic documents in each of the first result sets of electronic documents responsive to search queries of a first category, the search queries of the first category are selected from among a plurality of queries including the search queries of the first category and other search queries, the second profile characterizes one or more respective interactions with electronic documents in each of the second result sets of electronic documents responsive to search queries of the first category, and the indication indicates that the first scoring algorithm is better than the second scoring algorithm for scoring electronic documents responsive to search queries of the first category. 5. The method of claim 4 , wherein the first category is navigational queries, commercial queries, long queries, short queries, or general queries. | 0.970303 |
8,506,304 | 6 | 7 | 6. The method of claim 5 wherein the recommendation of a teaching plan includes a student group recommendation for group activities. | 6. The method of claim 5 wherein the recommendation of a teaching plan includes a student group recommendation for group activities. 7. The method of claim 6 wherein the recommendation of a teaching plan includes a recommended lesson plan using resources available to the teacher and students. | 0.971731 |
9,519,682 | 13 | 17 | 13. A non-transitory computer-readable storage device having computer-executable instructions stored thereon such that when the storage device is accessed by a computing device, the instructions are executable by the computing device to perform actions, comprising: identifying, for a given action, a trusted group of user accounts from a plurality of user accounts using a respective trustworthiness score for the given action assigned to each user account of the plurality, wherein the given action refers to an online activity that is performed by one or more users associated with respective user accounts, each user account's trustworthiness score being determined using inputs received from the each user account for the given action, the trustworthiness score being used to identify the trusted group of user accounts whose input is to be used to classify an item, wherein the item refers to an article of the internet that can have an action performed on it, and to identify other user accounts whose input is to be excluded from classifying the item the identifying comprising generating an initial trustworthiness score for a user account of the plurality using a trained trustworthiness classifier and a feature set about the user account, the trained trustworthiness classifier comprising a number of machine-implemented algorithms used to evolve behaviors based on input data, the feature set comprising online user behavioral features and static profile features about the user account, wherein the online user behavioral features comprise online activity features and the static profile features comprise user registration features the initial trustworthiness score for the user account is used at least initially to determine whether or not to include the user account in the trusted group of user accounts for the given action; monitoring inputs for the given action and about an item, the inputs about the item from the one or more trusted groups for the given action are used to classify the item as one of spam and non-spam, such that any input about the item from other than the trusted group of user accounts formed for the given action is excluded from being used to classify the item; and evolving the trusted group based on modified trustworthiness scores of the plurality of user accounts for the given action, each modified trustworthiness score is determined, in part, by a comparison of an input about the item from a corresponding user account and inputs about the item from other user accounts in the plurality of user accounts, wherein evolving the trusted group further comprises at least one of moving at least one user account into the trusted group that previously was not in the trusted group and moving at least one user account out of the trusted group that was previously in the trusted group. | 13. A non-transitory computer-readable storage device having computer-executable instructions stored thereon such that when the storage device is accessed by a computing device, the instructions are executable by the computing device to perform actions, comprising: identifying, for a given action, a trusted group of user accounts from a plurality of user accounts using a respective trustworthiness score for the given action assigned to each user account of the plurality, wherein the given action refers to an online activity that is performed by one or more users associated with respective user accounts, each user account's trustworthiness score being determined using inputs received from the each user account for the given action, the trustworthiness score being used to identify the trusted group of user accounts whose input is to be used to classify an item, wherein the item refers to an article of the internet that can have an action performed on it, and to identify other user accounts whose input is to be excluded from classifying the item the identifying comprising generating an initial trustworthiness score for a user account of the plurality using a trained trustworthiness classifier and a feature set about the user account, the trained trustworthiness classifier comprising a number of machine-implemented algorithms used to evolve behaviors based on input data, the feature set comprising online user behavioral features and static profile features about the user account, wherein the online user behavioral features comprise online activity features and the static profile features comprise user registration features the initial trustworthiness score for the user account is used at least initially to determine whether or not to include the user account in the trusted group of user accounts for the given action; monitoring inputs for the given action and about an item, the inputs about the item from the one or more trusted groups for the given action are used to classify the item as one of spam and non-spam, such that any input about the item from other than the trusted group of user accounts formed for the given action is excluded from being used to classify the item; and evolving the trusted group based on modified trustworthiness scores of the plurality of user accounts for the given action, each modified trustworthiness score is determined, in part, by a comparison of an input about the item from a corresponding user account and inputs about the item from other user accounts in the plurality of user accounts, wherein evolving the trusted group further comprises at least one of moving at least one user account into the trusted group that previously was not in the trusted group and moving at least one user account out of the trusted group that was previously in the trusted group. 17. The non-transitory computer-readable storage device of claim 13 , wherein the one or more other network devices further enables actions, the actions comprising: when a trustworthiness score of a given user account is below a threshold value, identifying the given user account as a robot account; and identifying the given user account as a human account when the trustworthiness score of the given user account is not below the threshold value. | 0.705767 |
5,563,626 | 6 | 9 | 6. A text display system including means for receiving and storing an original text, means for receiving and storing an updated text reflecting the changes to said original text and means for displaying said updated text according to proportionally spaced fonts, said system comprising: means for determining the width of each character when displaying said characters; means for calculating and associating with each character of the updated and original texts a corresponding character end position according to said character width determination; means for associating a flag indicating a character type with each character of the original and updated texts; means for copying all said associated character end positions and flags to a common buffer; means for arranging the character end positions and flags within the common buffer according to the character end positions; means for calculating the difference between contiguous arranged character end positions and storing said differences back in said common buffer; means for identifying the minima of said differences thereby determining where the original and updated texts have the closest match in terms of character end positions; and means responsive to said minima and said character end positions for displaying all updated characters followed by all original characters between consecutive minima thereby incrementally displaying and deleting characters of the updated and original texts respectively such that an original character is deleted only upon prior replacement by an appropriate number of updated text characters resulting in a smooth text update. | 6. A text display system including means for receiving and storing an original text, means for receiving and storing an updated text reflecting the changes to said original text and means for displaying said updated text according to proportionally spaced fonts, said system comprising: means for determining the width of each character when displaying said characters; means for calculating and associating with each character of the updated and original texts a corresponding character end position according to said character width determination; means for associating a flag indicating a character type with each character of the original and updated texts; means for copying all said associated character end positions and flags to a common buffer; means for arranging the character end positions and flags within the common buffer according to the character end positions; means for calculating the difference between contiguous arranged character end positions and storing said differences back in said common buffer; means for identifying the minima of said differences thereby determining where the original and updated texts have the closest match in terms of character end positions; and means responsive to said minima and said character end positions for displaying all updated characters followed by all original characters between consecutive minima thereby incrementally displaying and deleting characters of the updated and original texts respectively such that an original character is deleted only upon prior replacement by an appropriate number of updated text characters resulting in a smooth text update. 9. A text display system as claimed in claim 6 further comprising means responsive to the total width of the updating text for determining whether a single line or a partial or complete screen or display area update is required. | 0.683333 |
9,009,192 | 17 | 19 | 17. The computer-readable storage device of claim 12 , wherein selecting a web resource referenced by a particular search result of the obtained search results as relevant additional content for the first web resource comprises: generating a first score for each of one or more of the identified central entities based at least in part on weights of outgoing edges of respective nodes corresponding to the identified central entities; determining that the particular search result was identified as being responsive to a search query generated for a central entity having a highest first score among the one or more identified central entities; and selecting a web resource referenced by the particular search result. | 17. The computer-readable storage device of claim 12 , wherein selecting a web resource referenced by a particular search result of the obtained search results as relevant additional content for the first web resource comprises: generating a first score for each of one or more of the identified central entities based at least in part on weights of outgoing edges of respective nodes corresponding to the identified central entities; determining that the particular search result was identified as being responsive to a search query generated for a central entity having a highest first score among the one or more identified central entities; and selecting a web resource referenced by the particular search result. 19. The computer-readable storage device of claim 17 , wherein the first score for the particular identified central entity is based at least in part on a frequency of occurrence of the identified central entity in the first resource. | 0.941646 |
9,014,480 | 17 | 18 | 17. One or more non-transitory computer readable storage media comprising a sequence of instructions, which, when executed cause a processor to perform operations, the sequence of instructions comprising: first instructions to create a plurality of sets of positions automatically, by at least performing comparisons using multiple pluralities of pixels hereinafter compared pixels that are located in an image at corresponding positions comprised in the plurality of sets of positions; wherein a first set in the plurality of sets of positions is created without using in any comparison, a plurality of pixels hereinafter skipped pixels that are located in the image at additional positions comprised in the first set; wherein a first region identified by the first set is contiguous in the image, the first region comprising the compared pixels and the skipped pixels identified respectively by the corresponding positions and the additional positions; wherein a second region is contiguous in the image, the second region being identified by positions in a second set, in the plurality of sets of positions created by the creating; second instructions to check, whether a test is satisfied by a first attribute of the first region and a second attribute of the second region; third instructions to prepare a merged set comprising the positions in the first set and the positions in the second set, based on at least an outcome of said test; and fourth instructions to store in at least one memory, the merged set. | 17. One or more non-transitory computer readable storage media comprising a sequence of instructions, which, when executed cause a processor to perform operations, the sequence of instructions comprising: first instructions to create a plurality of sets of positions automatically, by at least performing comparisons using multiple pluralities of pixels hereinafter compared pixels that are located in an image at corresponding positions comprised in the plurality of sets of positions; wherein a first set in the plurality of sets of positions is created without using in any comparison, a plurality of pixels hereinafter skipped pixels that are located in the image at additional positions comprised in the first set; wherein a first region identified by the first set is contiguous in the image, the first region comprising the compared pixels and the skipped pixels identified respectively by the corresponding positions and the additional positions; wherein a second region is contiguous in the image, the second region being identified by positions in a second set, in the plurality of sets of positions created by the creating; second instructions to check, whether a test is satisfied by a first attribute of the first region and a second attribute of the second region; third instructions to prepare a merged set comprising the positions in the first set and the positions in the second set, based on at least an outcome of said test; and fourth instructions to store in at least one memory, the merged set. 18. The one or more non-transitory computer readable storage media of claim 17 wherein the sequence of instructions comprise: fifth instructions to low-pass filter the image, hereinafter original image, prior to execution of the first instructions, to obtain a low-pass image; wherein comparisons performed by execution of the first instructions are performed using pixels located adjacent to one another in the low-pass image, thereby to exclude from the comparisons the skipped pixels of the original image. | 0.660667 |
8,887,076 | 1 | 2 | 1. A computer-implemented method for providing a user with a user interface for building a flowchart graphically representing a database query, the method comprising: presenting to the user, within the user interface, a plurality of flowchart step types, each of the plurality of flowchart step types associated with a different logical expression format; receiving, at a processor, a selection of one of the plurality of flowchart step types from the user; presenting to the user, within the user interface, at least one expression option for the logical expression format of the selected flowchart step type; receiving, at the processor, at least one input for the at least one expression option from the user; generating, at the processor, a graphical flowchart step associated with a logical expression, the logical expression based on the at least one input and the logical expression format of the selected flowchart step type; displaying to the user the graphical flowchart step within the user interface; receiving, at the processor, a plurality of input connections associated with the graphical flowchart step from the user; receiving, at the processor, a plurality of pass output connections associated with the graphical flowchart step from the user; receiving, at the processor, a plurality of fail output connections associated with the graphical flowchart step from the user; and automatically generating, at the processor, a database query corresponding to the logical expression, the plurality of input connections, the plurality of pass output connections, and the plurality of fail output connections associated with the displayed graphical flowchart step. | 1. A computer-implemented method for providing a user with a user interface for building a flowchart graphically representing a database query, the method comprising: presenting to the user, within the user interface, a plurality of flowchart step types, each of the plurality of flowchart step types associated with a different logical expression format; receiving, at a processor, a selection of one of the plurality of flowchart step types from the user; presenting to the user, within the user interface, at least one expression option for the logical expression format of the selected flowchart step type; receiving, at the processor, at least one input for the at least one expression option from the user; generating, at the processor, a graphical flowchart step associated with a logical expression, the logical expression based on the at least one input and the logical expression format of the selected flowchart step type; displaying to the user the graphical flowchart step within the user interface; receiving, at the processor, a plurality of input connections associated with the graphical flowchart step from the user; receiving, at the processor, a plurality of pass output connections associated with the graphical flowchart step from the user; receiving, at the processor, a plurality of fail output connections associated with the graphical flowchart step from the user; and automatically generating, at the processor, a database query corresponding to the logical expression, the plurality of input connections, the plurality of pass output connections, and the plurality of fail output connections associated with the displayed graphical flowchart step. 2. The method of claim 1 , wherein generating the graphical flowchart step includes generating a graphical flowchart step including an input, a fail output, and a pass output. | 0.621212 |
8,886,636 | 6 | 7 | 6. A computer-implemented method for determining a type of landing page to which to transfer web searchers that enter a particular query, the queries related to landing pages that link from respective advertisements, the method comprising: extracting, by a computer, content of each of a plurality of landing pages to be classified by a web crawler of a classifier, the content comprising words of the landing page; extracting, by a computer, text from the content by a page rendering program of the classifier; establishing, by a computer, a feature space based on the extracted text, representing the extracted landing page; reducing, by a computer, the feature space by applying a supervised attribute selection technique to the classifier; and training, by a computer, a machine learning model of the classifier using a learning algorithm; classifying, by a computer, each of a plurality of target landing pages into one of a plurality of classes with the classifier trained by the machine learning model using content extracted from each of the plurality of target landing pages, wherein the plurality of classes comprise homepage, search transfer, and category browse; gathering, by a computer, characteristics on one or more query associated with each target landing page; partitioning, by a computer, the plurality of target landing pages according to a plurality of query characteristics; determining, by a computer, conversion rates of advertisements on at least some of the plurality of target landing pages; correlating, by a computer, the plurality of classes of landing pages within each landing page partition with corresponding conversion rates; and choosing a target landing page of a particular class to associate with an identified query within a search engine based on the corresponding conversion rate of that target landing page class as associated with the characteristics of the identified query. | 6. A computer-implemented method for determining a type of landing page to which to transfer web searchers that enter a particular query, the queries related to landing pages that link from respective advertisements, the method comprising: extracting, by a computer, content of each of a plurality of landing pages to be classified by a web crawler of a classifier, the content comprising words of the landing page; extracting, by a computer, text from the content by a page rendering program of the classifier; establishing, by a computer, a feature space based on the extracted text, representing the extracted landing page; reducing, by a computer, the feature space by applying a supervised attribute selection technique to the classifier; and training, by a computer, a machine learning model of the classifier using a learning algorithm; classifying, by a computer, each of a plurality of target landing pages into one of a plurality of classes with the classifier trained by the machine learning model using content extracted from each of the plurality of target landing pages, wherein the plurality of classes comprise homepage, search transfer, and category browse; gathering, by a computer, characteristics on one or more query associated with each target landing page; partitioning, by a computer, the plurality of target landing pages according to a plurality of query characteristics; determining, by a computer, conversion rates of advertisements on at least some of the plurality of target landing pages; correlating, by a computer, the plurality of classes of landing pages within each landing page partition with corresponding conversion rates; and choosing a target landing page of a particular class to associate with an identified query within a search engine based on the corresponding conversion rate of that target landing page class as associated with the characteristics of the identified query. 7. The method of claim 6 , wherein the classes further comprise miscellaneous, wherein miscellaneous includes landing pages not falling into a classification of homepage, search transfer, or category browse. | 0.793 |
8,418,165 | 1 | 4 | 1. A system comprising: a processor; a memory; one or more designers and a visualizer, the one or more designers and the visualizer configured to visually formulate application package designs that customize the appearance and layout of corresponding application packages; a package generator for generating application packages from application package designs, generated application packages being in a format expected by product deployment software; and one or more computer readable storage devices having stored thereon computer executable instructions that, when executed by the processor, cause the system to: customize an application package design, including: present the structure of an application package through an arrangement of user-interface elements in a view of the visualizer, the user-interface elements corresponding to application package element references, the application package element references referencing application package elements; receive user input within the visualizer view; in response to the user input: visually alter one or more user-interface elements in the arrangement of user-interface elements; and alter the structure of the application package by the one or more designers altering application package element references corresponding the visually altered one or more user-interface elements; and generate a customized application package from the customized application design, generation of the customized application package including: create an application package element manifest by traversing the altered structure of application package in accordance with the application package element references to identify application package elements that are to be included in the customized application package; transform the application package element manifest into one or more manifest files in a format that is compatible with a packaging schema for the product deployment software by mapping between types and properties in an object model and elements and attributes in the packaging schema; preview the customized application package on disk by creating, from the one or more manifest files, a directory hierarchy comprising the identified application package elements and placing the identified application package elements in locations relative to the directory hierarchy on at least one server computer of the plurality of server computers; and use the directory hierarchy to bundle the identified application package elements into one file for deploying the collaborative server application across the plurality of server computers, the one file in a format expected by the product deployment software. | 1. A system comprising: a processor; a memory; one or more designers and a visualizer, the one or more designers and the visualizer configured to visually formulate application package designs that customize the appearance and layout of corresponding application packages; a package generator for generating application packages from application package designs, generated application packages being in a format expected by product deployment software; and one or more computer readable storage devices having stored thereon computer executable instructions that, when executed by the processor, cause the system to: customize an application package design, including: present the structure of an application package through an arrangement of user-interface elements in a view of the visualizer, the user-interface elements corresponding to application package element references, the application package element references referencing application package elements; receive user input within the visualizer view; in response to the user input: visually alter one or more user-interface elements in the arrangement of user-interface elements; and alter the structure of the application package by the one or more designers altering application package element references corresponding the visually altered one or more user-interface elements; and generate a customized application package from the customized application design, generation of the customized application package including: create an application package element manifest by traversing the altered structure of application package in accordance with the application package element references to identify application package elements that are to be included in the customized application package; transform the application package element manifest into one or more manifest files in a format that is compatible with a packaging schema for the product deployment software by mapping between types and properties in an object model and elements and attributes in the packaging schema; preview the customized application package on disk by creating, from the one or more manifest files, a directory hierarchy comprising the identified application package elements and placing the identified application package elements in locations relative to the directory hierarchy on at least one server computer of the plurality of server computers; and use the directory hierarchy to bundle the identified application package elements into one file for deploying the collaborative server application across the plurality of server computers, the one file in a format expected by the product deployment software. 4. The system of claim 1 , wherein the customized application package comprises a collaborative server application comprising a Web-based collaboration function, a process management module, a search module and a content management platform. | 0.832871 |
9,575,960 | 4 | 8 | 4. A computer-implemented method, comprising: identifying a semantic meaning associated with one or more words in an electronic document being displayed on a display of a computing device, the one or more words being located at a specific location of the electronic document; identifying an audio file associated with the semantic meaning; determining a gaze direction of a user relative to the display; determining an estimated location on the display corresponding to the gaze direction; determining that the estimated location is within a threshold distance from the specific location of the one or more words; and playing the audio file with a volume based at least in part upon the semantic meaning of the one or more words and determining that the estimated location is within the threshold distance from the specific location of the one or more words. | 4. A computer-implemented method, comprising: identifying a semantic meaning associated with one or more words in an electronic document being displayed on a display of a computing device, the one or more words being located at a specific location of the electronic document; identifying an audio file associated with the semantic meaning; determining a gaze direction of a user relative to the display; determining an estimated location on the display corresponding to the gaze direction; determining that the estimated location is within a threshold distance from the specific location of the one or more words; and playing the audio file with a volume based at least in part upon the semantic meaning of the one or more words and determining that the estimated location is within the threshold distance from the specific location of the one or more words. 8. The computer-implemented method of claim 4 , further comprising: receiving feedback relating to the audio file. | 0.876623 |
8,001,100 | 1 | 12 | 1. A computer implemented method for locating information about a target entity in disparate multilevel hierarchical knowledge repositories, the computer mplemented method comprising: responsive to an occurrence of problem with an information technology solution associated with a target entity, searching the disparate multilevel hierarchical knowledge repositories for metadata about the target entity; identifying, using a computer system, from the metadata about the target entity a plurality of related entities that are related to the target entity and a set of repositories in the disparate multilevel hierarchical knowledge repositories comprising metadata about the plurality of related entities, wherein the plurality of related entities and the target entity are components comprising the information technology solution; using links in the metadata about the target entity to search the set of repositories to locate the plurality of related entities; searching the metadata about the target entity and the metadata about the plurality of related entities for a resolution to the problem with the information technology solution; responsive to locating the resolution to the problem in the disparate multilevel hierarchical knowledge repositories, storing a link to the resolution in the metadata about the target entity; searching the disparate multilevel hierarchical knowledge repositories for owners of at least one of the target entity and the plurality of related entities; notifying the owners of at least one of the target entity and the plurality of related entities about the problem and the resolution to the problem; and storing the link to the resolution to the problem in the metadata about the plurality of related entities. | 1. A computer implemented method for locating information about a target entity in disparate multilevel hierarchical knowledge repositories, the computer mplemented method comprising: responsive to an occurrence of problem with an information technology solution associated with a target entity, searching the disparate multilevel hierarchical knowledge repositories for metadata about the target entity; identifying, using a computer system, from the metadata about the target entity a plurality of related entities that are related to the target entity and a set of repositories in the disparate multilevel hierarchical knowledge repositories comprising metadata about the plurality of related entities, wherein the plurality of related entities and the target entity are components comprising the information technology solution; using links in the metadata about the target entity to search the set of repositories to locate the plurality of related entities; searching the metadata about the target entity and the metadata about the plurality of related entities for a resolution to the problem with the information technology solution; responsive to locating the resolution to the problem in the disparate multilevel hierarchical knowledge repositories, storing a link to the resolution in the metadata about the target entity; searching the disparate multilevel hierarchical knowledge repositories for owners of at least one of the target entity and the plurality of related entities; notifying the owners of at least one of the target entity and the plurality of related entities about the problem and the resolution to the problem; and storing the link to the resolution to the problem in the metadata about the plurality of related entities. 12. The method of claim 1 , wherein the target entity and the plurality of related entities are components deployed in a disparate multilevel hierarchical infrastructure, wherein the disparate multilevel hierarchical knowledge repositories comprise information about each of the components deployed in the disparate multilevel hierarchical infrastructure, and wherein identifying from the metadata about the target entity the plurality of related entities that are related to the target entity and the set of repositories in the disparate multilevel hierarchical knowledge repositories comprising metadata about the plurality of related entities comprises: identifying, from the metadata about the target entity, a name, a description, and a type of the target entity; and searching the disparate multilevel hierarchical knowledge repositories for entities in the disparate multilevel hierarchical infrastructure that match at least one of the name, the description, and the type of the target entity to identify the plurality of related entities. | 0.500477 |
7,509,581 | 21 | 22 | 21. A storage medium storing a hierarchical data structure configured to be processed by multimedia data processing apparatus to facilitate browsing content in an audio-visual program, the stored hierarchical data structure comprising: a first structural part which stores segment information about the audio-visual program, the segment information including segment location information identifying a plurality of audio-visual segments in the audio-visual program, wherein the segment location information defines each audio-visual segment by a temporal position in a multimedia stream of the audio-visual program and wherein each audio-visual segment represents a continuous temporal content portion in the audio-visual program; a distinct second structural part which stores segment group information defining first and second segment groups for the audio-visual program, each of which defines a respective set of non-contiguous audio-visual segments that are selected from the plurality of audio-visual segments and identified in the segment group information by references to the corresponding segments in the segment information of the audio-visual program, wherein said segment group information specifies a respective group type and a respective duration for each of said first and second segment groups, the respective group types indicating that the first and second segment groups represent respective first and second content summaries related to objects or events as depicted in the audio-visual program, and wherein the segment group information includes segment order information defining that (i) the audio-visual segments within the first segment group are ordered relative to each other according to a time sequence that is significant for the first content summary's representation of the corresponding events or objects in the audio-visual program and (ii) the audio-visual segments within the second segment group are not ordered relative to each other according to any time sequence that is significant for the second content summary's representation of the corresponding events or objects in the audio-visual program. | 21. A storage medium storing a hierarchical data structure configured to be processed by multimedia data processing apparatus to facilitate browsing content in an audio-visual program, the stored hierarchical data structure comprising: a first structural part which stores segment information about the audio-visual program, the segment information including segment location information identifying a plurality of audio-visual segments in the audio-visual program, wherein the segment location information defines each audio-visual segment by a temporal position in a multimedia stream of the audio-visual program and wherein each audio-visual segment represents a continuous temporal content portion in the audio-visual program; a distinct second structural part which stores segment group information defining first and second segment groups for the audio-visual program, each of which defines a respective set of non-contiguous audio-visual segments that are selected from the plurality of audio-visual segments and identified in the segment group information by references to the corresponding segments in the segment information of the audio-visual program, wherein said segment group information specifies a respective group type and a respective duration for each of said first and second segment groups, the respective group types indicating that the first and second segment groups represent respective first and second content summaries related to objects or events as depicted in the audio-visual program, and wherein the segment group information includes segment order information defining that (i) the audio-visual segments within the first segment group are ordered relative to each other according to a time sequence that is significant for the first content summary's representation of the corresponding events or objects in the audio-visual program and (ii) the audio-visual segments within the second segment group are not ordered relative to each other according to any time sequence that is significant for the second content summary's representation of the corresponding events or objects in the audio-visual program. 22. The storage medium of claim 21 , wherein said segment group information includes a level information. | 0.90113 |
8,769,491 | 23 | 25 | 23. One or more non-transitory computer-readable media storing instructions, the instructions comprising: one or more instructions that, when executed by one or more computing devices, cause the one or more computing devices to: obtain a scripting language code that is associated with a collection of code for executing a first task and a second task; select, for each of the first task and the second task, one of a plurality of threads based on a plurality of annotations included in the collection of code; dispatch the first task to a first thread, of the plurality of threads, in a scripting language environment based on a first annotation, of the plurality of annotations included in the collection of code, identifying a first type of thread to which the first task should be dispatched; dispatch the second task to a second thread, of the plurality of threads, in a non-scripting language environment based on a second annotation, of the plurality of annotations included in the collection of code, identifying a second type of thread to which the second task should be dispatched, the first task or the second task not being dispatched to one or more of threads, of the plurality of threads, based on a third annotation, of the plurality of annotations, the third annotation specifying an identity of the one or more threads and indicating that the first task or the second task should not be dispatched to the identified one or more threads; and cause an execution of the scripting language code, during the execution of the scripting language code, the first task being executed via the first thread in the scripting language environment and the second task being executed via the second thread in the non-scripting language environment. | 23. One or more non-transitory computer-readable media storing instructions, the instructions comprising: one or more instructions that, when executed by one or more computing devices, cause the one or more computing devices to: obtain a scripting language code that is associated with a collection of code for executing a first task and a second task; select, for each of the first task and the second task, one of a plurality of threads based on a plurality of annotations included in the collection of code; dispatch the first task to a first thread, of the plurality of threads, in a scripting language environment based on a first annotation, of the plurality of annotations included in the collection of code, identifying a first type of thread to which the first task should be dispatched; dispatch the second task to a second thread, of the plurality of threads, in a non-scripting language environment based on a second annotation, of the plurality of annotations included in the collection of code, identifying a second type of thread to which the second task should be dispatched, the first task or the second task not being dispatched to one or more of threads, of the plurality of threads, based on a third annotation, of the plurality of annotations, the third annotation specifying an identity of the one or more threads and indicating that the first task or the second task should not be dispatched to the identified one or more threads; and cause an execution of the scripting language code, during the execution of the scripting language code, the first task being executed via the first thread in the scripting language environment and the second task being executed via the second thread in the non-scripting language environment. 25. The one or more non-transitory computer-readable media of claim 23 , where the first annotation includes performance information or security information associated with the collection of code; and where the one or more instructions to dispatch the first task to the first thread include: one or more instructions that, when executed by the one or more computing devices, cause the one or more computing devices to dispatch the first task to the first thread further based on the performance information or the security information. | 0.783926 |
9,342,487 | 1 | 4 | 1. A method comprising: determining geometric constraints for speech bubbles within an image, the image including characters, wherein the geometric constraints are based on boundaries of the characters within the image and boundaries of the image; determining features of the characters in the image; receiving speech content for the characters; identifying a conversation order of the speech content with respect to the characters; and generating a layout of the speech bubbles that defines a location and size of each speech bubble, with respect to the image, based on the geometric constraints, the features of the characters, the speech content, and the conversation order. | 1. A method comprising: determining geometric constraints for speech bubbles within an image, the image including characters, wherein the geometric constraints are based on boundaries of the characters within the image and boundaries of the image; determining features of the characters in the image; receiving speech content for the characters; identifying a conversation order of the speech content with respect to the characters; and generating a layout of the speech bubbles that defines a location and size of each speech bubble, with respect to the image, based on the geometric constraints, the features of the characters, the speech content, and the conversation order. 4. The method of claim 1 , further comprising: receiving user-defined constraints for one or more of the speech bubbles, the user-defined constraints defining a specific location, shape, or size of the one or more of the speech bubbles wherein generating the layout of the speech bubbles is further based on the user-defined constraints. | 0.708981 |
5,446,886 | 1 | 2 | 1. A distributed database system for a communication network having a plurality of nodes, each of which nodes includes a distributed database, said distributed database system comprising: local process means for extracting relations from each database of said communication network by performing local processes at each of said nodes of said communication system when a query including multi-attribute relations is input from one of said nodes; degree setting means for setting a degree number of each of said extracted relations from said local process means based on (A) tuple numbers of single-attribute relations derived from said multi-attribute relations and (B) a tuple number of each of said multi-attribute relations; relation set means for arranging a plurality of relation sets, each of which relation sets contains relations having the same degree number in ascending order by grouping said extracted relations from said local process means according to the degree number set by said degree setting means, wherein said relation sets include a first relation set containing relations with the lowest degree number; extraction means for extracting single-attribute relations from each of said relation sets arranged by said relation set means so that said single-attribute relations are added to said first relation set; semijoin operating means for repeatedly semijoining two relations of a relation set when a quantity of transfer data after said semijoining is detected to be smaller than a quantity of transfer data before said semijoining, and for adding derived relations resulting from said semijoining to a following relation set among the plurality of relation sets arranged by said relation set means; and control means or allowing said semijoin operating means to sequentially perform said semijoining and said adding for all of the plurality of relation sets arranged by said relation set means, starting from said first relation set and ending at a relation set having the highest degree number, so that each derived relation resulting from said semijoining is added to the transfer data. | 1. A distributed database system for a communication network having a plurality of nodes, each of which nodes includes a distributed database, said distributed database system comprising: local process means for extracting relations from each database of said communication network by performing local processes at each of said nodes of said communication system when a query including multi-attribute relations is input from one of said nodes; degree setting means for setting a degree number of each of said extracted relations from said local process means based on (A) tuple numbers of single-attribute relations derived from said multi-attribute relations and (B) a tuple number of each of said multi-attribute relations; relation set means for arranging a plurality of relation sets, each of which relation sets contains relations having the same degree number in ascending order by grouping said extracted relations from said local process means according to the degree number set by said degree setting means, wherein said relation sets include a first relation set containing relations with the lowest degree number; extraction means for extracting single-attribute relations from each of said relation sets arranged by said relation set means so that said single-attribute relations are added to said first relation set; semijoin operating means for repeatedly semijoining two relations of a relation set when a quantity of transfer data after said semijoining is detected to be smaller than a quantity of transfer data before said semijoining, and for adding derived relations resulting from said semijoining to a following relation set among the plurality of relation sets arranged by said relation set means; and control means or allowing said semijoin operating means to sequentially perform said semijoining and said adding for all of the plurality of relation sets arranged by said relation set means, starting from said first relation set and ending at a relation set having the highest degree number, so that each derived relation resulting from said semijoining is added to the transfer data. 2. A distributed database system according to claim 1, further comprising: first means for detecting whether or not a derived relation, resulting from said semijoining by said semijoin operating means, is a high-level relation; and second means for dividing said derived relation into low-level relations when said derived relation is detected to be a high-level relation. | 0.734665 |
9,355,370 | 19 | 20 | 19. The method of claim 18 wherein the at least one selected optional clause contains a plurality of subordinate optional clauses. | 19. The method of claim 18 wherein the at least one selected optional clause contains a plurality of subordinate optional clauses. 20. The method of claim 19 wherein the at least one selected optional clause and the plurality of subordinate optional clauses are organized in a tree structure. | 0.959096 |
9,536,223 | 17 | 18 | 17. A non-transitory computer-readable storage medium comprising a plurality of instructions for visually finding N-grams in near-time, the plurality of instructions configured to execute on at least one computer processor to enable the at least one computer processor to: in response to a user request, generate digital information processable by a client device to display a GUI, wherein the GUI includes a first element for receiving user input specifying one or more query terms, a second element for receiving a user selection specifying a dataset, a third element for displaying a velocity graph, and a fourth element for displaying a list of candidate n-grams; transmit the digital information for generating the GUI to the client device; in response to receiving, from the client device, a user input specifying a particular one or more query terms and a user selection specifying a particular dataset: search for and retrieve from the dataset, documents that include the one or more query terms; detect candidate n-grams of the particular one or more query terms, wherein the detecting includes applying programmatic heuristics based on co-occurrence with the particular one or more query terms in the retrieved documents; select one or more of the candidate n-grams, wherein the selecting is based on co-occurrence statistics; and generate information processable by the client device to display, in the third element, a velocity graph that displays the number of retrieved documents as a function of time and, in the fourth element, a list of the selected candidate n-grams of the particular one or more query terms; and transmit, to the client device, the digital information for displaying the velocity graph and the candidate n-grams. | 17. A non-transitory computer-readable storage medium comprising a plurality of instructions for visually finding N-grams in near-time, the plurality of instructions configured to execute on at least one computer processor to enable the at least one computer processor to: in response to a user request, generate digital information processable by a client device to display a GUI, wherein the GUI includes a first element for receiving user input specifying one or more query terms, a second element for receiving a user selection specifying a dataset, a third element for displaying a velocity graph, and a fourth element for displaying a list of candidate n-grams; transmit the digital information for generating the GUI to the client device; in response to receiving, from the client device, a user input specifying a particular one or more query terms and a user selection specifying a particular dataset: search for and retrieve from the dataset, documents that include the one or more query terms; detect candidate n-grams of the particular one or more query terms, wherein the detecting includes applying programmatic heuristics based on co-occurrence with the particular one or more query terms in the retrieved documents; select one or more of the candidate n-grams, wherein the selecting is based on co-occurrence statistics; and generate information processable by the client device to display, in the third element, a velocity graph that displays the number of retrieved documents as a function of time and, in the fourth element, a list of the selected candidate n-grams of the particular one or more query terms; and transmit, to the client device, the digital information for displaying the velocity graph and the candidate n-grams. 18. The non-transitory computer-readable storage medium of claim 17 , wherein the plurality of instructions are configured to execute on the at least one computer processor to enable the at least one computer processor to: in response to receiving, from the client device, a user input specifying a user selected set of candidate n-grams from the selected candidate n-grams: search for and retrieve from the dataset, a second set of documents that include the user selected set of candidate n-grams; generate information processable by the client device to display, in the third element, an updated velocity graph that displays the number of retrieved documents that include the user selected set of candidate n-grams as a function of time; and transmit, to the client device, the digital information for displaying the updated velocity graph. | 0.67096 |
8,214,349 | 45 | 55 | 45. A computer implemented system for processing data, the system comprising: a processor for parsing one or more source documents to identify at least one term based on one or more predetermined rules; a module for identifying content for the at least one term, linking the content with the at least one term, and automatically associating the at least one term in the one or more source documents with at least one link; and an interface for displaying the linked content based upon a user interaction with at least a portion of the one or more source documents; wherein the at least one link denotes an association between the at least one term and the linked content; wherein one or more data objects associated with a database are syndicated to one or more remote computers for providing a representation of at least a portion of the database at the one or more remote computers. | 45. A computer implemented system for processing data, the system comprising: a processor for parsing one or more source documents to identify at least one term based on one or more predetermined rules; a module for identifying content for the at least one term, linking the content with the at least one term, and automatically associating the at least one term in the one or more source documents with at least one link; and an interface for displaying the linked content based upon a user interaction with at least a portion of the one or more source documents; wherein the at least one link denotes an association between the at least one term and the linked content; wherein one or more data objects associated with a database are syndicated to one or more remote computers for providing a representation of at least a portion of the database at the one or more remote computers. 55. The system of claim 45 , wherein one or more of the predetermined rules are based on presence or lack thereof of an entry in the database. | 0.645 |
7,991,715 | 19 | 26 | 19. A system for image classification into a plurality of categories, comprising: means for, performing machine learning on a learning set of images; means for, generating a model based on the machine learning of the learning set of images; means for, determining an accuracy metric of the model using a verification set of images as one or more parameters in the model; and means for, generating a set of probability values; wherein each of the probability value of the set of probability values is generated for a pair of categories based on the accuracy metric. | 19. A system for image classification into a plurality of categories, comprising: means for, performing machine learning on a learning set of images; means for, generating a model based on the machine learning of the learning set of images; means for, determining an accuracy metric of the model using a verification set of images as one or more parameters in the model; and means for, generating a set of probability values; wherein each of the probability value of the set of probability values is generated for a pair of categories based on the accuracy metric. 26. The system of claim 19 , wherein the n categories are associated with the n-lowest probability values of the set of probability values. | 0.78483 |
9,152,612 | 1 | 6 | 1. A computer-based method of processing a document having a plurality of input controls, the method comprising: a) in response to a command to display the plurality of input controls, attaching the plurality of input controls to the document; b) in response to a command to hide the plurality of input controls, detaching the plurality of input controls from the document; c) inserting a substitute control in the document and displaying the substitute control in response to the command to hide the plurality of input controls, the command to display the plurality of input controls is invoked by a user selection of the substitute control; and d) sending a value of each input control to a server. | 1. A computer-based method of processing a document having a plurality of input controls, the method comprising: a) in response to a command to display the plurality of input controls, attaching the plurality of input controls to the document; b) in response to a command to hide the plurality of input controls, detaching the plurality of input controls from the document; c) inserting a substitute control in the document and displaying the substitute control in response to the command to hide the plurality of input controls, the command to display the plurality of input controls is invoked by a user selection of the substitute control; and d) sending a value of each input control to a server. 6. The computer-based method of claim 1 , further comprising employing a script associated with the document to insert a field into the document and store the value of each input control in the field. | 0.898477 |
8,892,549 | 6 | 7 | 6. The method of claim 1 , where determining the topic score for the topic with respect to the document includes determining the topic score based on features of occurrence of the topic in the document. | 6. The method of claim 1 , where determining the topic score for the topic with respect to the document includes determining the topic score based on features of occurrence of the topic in the document. 7. The method of claim 6 , where features of an occurrence include one or more of: a location within the document of the occurrence; and typographical properties of the occurrence. | 0.957061 |
9,135,653 | 1 | 19 | 1. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender comprising: extracting a user identifier from a cookie received with the first activity data; and if a match for the user identifier is not found in the social graph, performing a probabilistic fingerprinting approach using attributes comprising at least one of device identifiers; IP addresses; operating systems; browsers types; browser versions; or user navigational, geo-temporal, and behavioral patterns; using the second activity information to identify a second node in the social graph as being representative of the recipient; determining a category for the first link as a first category type; in the social graph, identifying a first edge between the first and second nodes as being representative of the first category type; determining a first value associated with the first edge based on at least one of the first or second activity information; and adjusting the first value to create a second value associated with the first edge based on a passage of time from at least one of the first or second activity information. | 1. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender comprising: extracting a user identifier from a cookie received with the first activity data; and if a match for the user identifier is not found in the social graph, performing a probabilistic fingerprinting approach using attributes comprising at least one of device identifiers; IP addresses; operating systems; browsers types; browser versions; or user navigational, geo-temporal, and behavioral patterns; using the second activity information to identify a second node in the social graph as being representative of the recipient; determining a category for the first link as a first category type; in the social graph, identifying a first edge between the first and second nodes as being representative of the first category type; determining a first value associated with the first edge based on at least one of the first or second activity information; and adjusting the first value to create a second value associated with the first edge based on a passage of time from at least one of the first or second activity information. 19. The method of claim 1 further comprising: at a first time, storing the first value in the social graph associated with the first edge. | 0.857438 |
9,430,829 | 15 | 16 | 15. The non-transitory computer-readable storage medium of claim 14 , the method comprising: reducing the dimensionality of the set of HC features, where the dimensionality of the set of HC features is reduced using principal component analysis (PCA) or minimum redundancy maximum relevance (mRMR) feature selection, and selecting an optimum set of HC features. | 15. The non-transitory computer-readable storage medium of claim 14 , the method comprising: reducing the dimensionality of the set of HC features, where the dimensionality of the set of HC features is reduced using principal component analysis (PCA) or minimum redundancy maximum relevance (mRMR) feature selection, and selecting an optimum set of HC features. 16. The non-transitory computer-readable storage medium of claim 15 , where the optimum set of HC features comprises 98% of the component variations or the top 160 features selected using mRMR feature selection. | 0.957253 |
7,734,287 | 16 | 26 | 16. A method for facilitating diagnosis and maintenance of one or more control networks, comprising; wirelessly communicating over a wireless channel between a wireless ground station and a wireless interface coupled to an onboard vehicle control network located on a mobile conveyance; coupling the wireless ground station to a local area computer network comprising a server computer, a database comprising diagnostic information relating to said onboard vehicle control network, and a wide area network interface, whereby additional diagnostic information relating to said onboard vehicle control network is obtainable from one or more remote computers; conveying instructions from the handheld wireless diagnostic unit to the onboard vehicle control network in response to inputs entered at a manual input interface of the handheld wireless diagnostic unit; wirelessly communicating between a portable handheld wireless diagnostic unit and said onboard vehicle control network via said wireless interface and with said local area computer network via said ground station thereby receiving the diagnostic information pertaining to the onboard vehicle control network from the local area computer network via said wireless interface, wherein said portable handheld wireless diagnostic unit is not physically connected to said onboard vehicle control network; and displaying communications received by the portable handheld wireless diagnostic unit on a graphical display of the portable handheld wireless diagnostic unit. | 16. A method for facilitating diagnosis and maintenance of one or more control networks, comprising; wirelessly communicating over a wireless channel between a wireless ground station and a wireless interface coupled to an onboard vehicle control network located on a mobile conveyance; coupling the wireless ground station to a local area computer network comprising a server computer, a database comprising diagnostic information relating to said onboard vehicle control network, and a wide area network interface, whereby additional diagnostic information relating to said onboard vehicle control network is obtainable from one or more remote computers; conveying instructions from the handheld wireless diagnostic unit to the onboard vehicle control network in response to inputs entered at a manual input interface of the handheld wireless diagnostic unit; wirelessly communicating between a portable handheld wireless diagnostic unit and said onboard vehicle control network via said wireless interface and with said local area computer network via said ground station thereby receiving the diagnostic information pertaining to the onboard vehicle control network from the local area computer network via said wireless interface, wherein said portable handheld wireless diagnostic unit is not physically connected to said onboard vehicle control network; and displaying communications received by the portable handheld wireless diagnostic unit on a graphical display of the portable handheld wireless diagnostic unit. 26. The method of claim 16 , wherein the instructions conveyed to the onboard vehicle control network allow the onboard vehicle control network to be monitored through the graphical display on the portable handheld wireless diagnostic unit. | 0.602649 |
9,424,344 | 1 | 8 | 1. An apparatus for performing a natural language search, the apparatus comprising: a processor configured to search an index, said index contains information which references a domain model, using key words from a user's natural language question and the context of the user's question, and to save a plurality of documents obtained in response to the search of the index; the processor further configured to map each of the documents as a node into an object graph, wherein each node is associated with a parent node, except when the node is a root node; the processor further configured to identify the root node of each document; the processor further configured to identify the path of each node from the node to the node's root node, wherein said path comprises a plurality of nodes that connect the node to the root node; the processor further configured to identify a plurality of matching paths, each of said matching paths, wherein each matching path provides an answer to the user's natural language question, each of said plurality of paths that comprises a discrete path of nodes; the processor further configured to filter out paths depending on a set of the user's pre-determined criterion; the processor further configured to rank the remaining paths; and a display configured to display, in response to the filtering and ranking, a selected answer to the user. | 1. An apparatus for performing a natural language search, the apparatus comprising: a processor configured to search an index, said index contains information which references a domain model, using key words from a user's natural language question and the context of the user's question, and to save a plurality of documents obtained in response to the search of the index; the processor further configured to map each of the documents as a node into an object graph, wherein each node is associated with a parent node, except when the node is a root node; the processor further configured to identify the root node of each document; the processor further configured to identify the path of each node from the node to the node's root node, wherein said path comprises a plurality of nodes that connect the node to the root node; the processor further configured to identify a plurality of matching paths, each of said matching paths, wherein each matching path provides an answer to the user's natural language question, each of said plurality of paths that comprises a discrete path of nodes; the processor further configured to filter out paths depending on a set of the user's pre-determined criterion; the processor further configured to rank the remaining paths; and a display configured to display, in response to the filtering and ranking, a selected answer to the user. 8. The apparatus of claim 1 , wherein the paths may be ranked at least in part by the length of the path. | 0.784836 |
8,381,299 | 24 | 26 | 24. The method of claim 23 , wherein the plurality of n-grams in the training dataset also includes a second plurality of distinct training n-grams that are each a second size, and the method further comprises: computing a second plurality of appearance frequencies, wherein each of the second plurality of appearance frequencies corresponds to one of the second plurality of distinct training n-grams; obtaining a second pseudo count associated with the second plurality of appearance frequencies; computing a third total count of the number of n-grams of the plurality of n-grams in the training dataset that are the second size; computing a second maximum possible count of distinct n-grams of the second size in the plurality of n-grams; computing, a fourth total count of the second plurality of distinct training n-grams; computing a second smoothing factor; computing a second probability that the second plurality of distinct training n-grams are found in the training dataset using at least one of: the second plurality of appearance frequencies, the second pseudo count, the third total count, the fourth total count, and the second smoothing factor; computing a second consistency score of the plurality of n-grams in the training dataset that are the second size using the second maximum possible count and the second probability; and classifying the input dataset using the second consistency score. | 24. The method of claim 23 , wherein the plurality of n-grams in the training dataset also includes a second plurality of distinct training n-grams that are each a second size, and the method further comprises: computing a second plurality of appearance frequencies, wherein each of the second plurality of appearance frequencies corresponds to one of the second plurality of distinct training n-grams; obtaining a second pseudo count associated with the second plurality of appearance frequencies; computing a third total count of the number of n-grams of the plurality of n-grams in the training dataset that are the second size; computing a second maximum possible count of distinct n-grams of the second size in the plurality of n-grams; computing, a fourth total count of the second plurality of distinct training n-grams; computing a second smoothing factor; computing a second probability that the second plurality of distinct training n-grams are found in the training dataset using at least one of: the second plurality of appearance frequencies, the second pseudo count, the third total count, the fourth total count, and the second smoothing factor; computing a second consistency score of the plurality of n-grams in the training dataset that are the second size using the second maximum possible count and the second probability; and classifying the input dataset using the second consistency score. 26. The method of claim 24 , further comprising computing a third probability that the second plurality of distinct training n-grams are found in the training dataset given a presence of the first plurality of distinct training n-grams. | 0.955252 |
7,818,179 | 21 | 35 | 21. An automated method for providing awareness of speech habits of a speaker comprising: providing a speech processing system wearable or hand-held by the speaker; processing by the speech processing system speech input from the speaker during a speaking session; processing by the speech processing system speech input from a different speaker during the speaking session; segmenting in real time by the speech processing system the speech input from the speaker from the speech input from the different speaker; analyzing by the speech processing system speech processing results of the speaker using pre-specified criteria to identify a speech habit of the speaker; and alerting the speaker in real time while the speaker is speaking during the speaking session from which the speech input of the speaker and the speech input of the different speaker is segmented, wherein the speech input of the speaker is analyzed to detect one or more words or expressions or sounds, if any, which are specified in a vocabulary list, in the speech input of the user, wherein an identified speech habit comprises exceeding a range of volume of speaking a word or expression specified in the vocabulary list, and wherein a counter is incremented corresponding to a number of instances of exceeding a range of volume in the speech input from the speaker and the counter is compared to a repetition threshold for determining a speech habit in the speech input from the speaker based upon a predetermined value of the counter within a predetermined time period. | 21. An automated method for providing awareness of speech habits of a speaker comprising: providing a speech processing system wearable or hand-held by the speaker; processing by the speech processing system speech input from the speaker during a speaking session; processing by the speech processing system speech input from a different speaker during the speaking session; segmenting in real time by the speech processing system the speech input from the speaker from the speech input from the different speaker; analyzing by the speech processing system speech processing results of the speaker using pre-specified criteria to identify a speech habit of the speaker; and alerting the speaker in real time while the speaker is speaking during the speaking session from which the speech input of the speaker and the speech input of the different speaker is segmented, wherein the speech input of the speaker is analyzed to detect one or more words or expressions or sounds, if any, which are specified in a vocabulary list, in the speech input of the user, wherein an identified speech habit comprises exceeding a range of volume of speaking a word or expression specified in the vocabulary list, and wherein a counter is incremented corresponding to a number of instances of exceeding a range of volume in the speech input from the speaker and the counter is compared to a repetition threshold for determining a speech habit in the speech input from the speaker based upon a predetermined value of the counter within a predetermined time period. 35. The automated method of claim 21 , wherein: speech processing results obtained during the speaking session are storable, and analysis of the speech processing results is performable after the speaking session has ended, wherein a predetermined number of spoken words before and after a detected word/expression or sound in the storable speech processing results is recorded to provide a context for the detected word/expression or sound. | 0.692039 |
8,886,521 | 1 | 4 | 1. A non-transitory computer readable medium with an executable program stored thereon, wherein the program instructs a microprocessor to perform the following steps to use speech commands to produce a formatted report of a predetermined type, comprising: identifying a set of phrases frequently used to complete discrete sections of the report; parsing the phrases, where parsing comprises: constructing the phrases using variables; assigning each set of variables an identifier; identifying unique, comfortable-to-say, short identifiers for each phrase including words that accurately bring the phrase to mind; labeling each phrase as a logical “and” or “or”; grouping identifiers into logical, comfortable, spoken sets, wherein one or more groupings are identified, appropriate for different user experience levels and coordinated so it is easy for the user to move to the next level; labeling each set as a logical “and” or “or”; and identifying punctuation locations; comparing identifier words throughout the report to eliminate ambiguities; and constructing text macros that follow the parsed text, enabling the user to speak the identifiers to indicate full, formatted text for inclusion in the report. | 1. A non-transitory computer readable medium with an executable program stored thereon, wherein the program instructs a microprocessor to perform the following steps to use speech commands to produce a formatted report of a predetermined type, comprising: identifying a set of phrases frequently used to complete discrete sections of the report; parsing the phrases, where parsing comprises: constructing the phrases using variables; assigning each set of variables an identifier; identifying unique, comfortable-to-say, short identifiers for each phrase including words that accurately bring the phrase to mind; labeling each phrase as a logical “and” or “or”; grouping identifiers into logical, comfortable, spoken sets, wherein one or more groupings are identified, appropriate for different user experience levels and coordinated so it is easy for the user to move to the next level; labeling each set as a logical “and” or “or”; and identifying punctuation locations; comparing identifier words throughout the report to eliminate ambiguities; and constructing text macros that follow the parsed text, enabling the user to speak the identifiers to indicate full, formatted text for inclusion in the report. 4. The non-transitory computer readable medium of claim 1 , wherein the report is a medical report. | 0.784783 |
7,663,628 | 1 | 13 | 1. An apparatus comprising a computer processor for animating a moving and speaking enhanced-believability character in real time, comprising: i. a plurality of behavior generators each responsible for a respective aspect of facial behavior, at least some of said generators being configured with a respective time definer defining time intervals and generating behavior elements in accordance with said defined time intervals; ii. a unifying scripter, associated with said behavior generators, said unifying scripter operable to combine said generated elements into a unified animation script for said enhanced believability character; and iii. a renderer, associated with said unifying scripter, said renderer operable to render said enhanced believability character in accordance with said unified animation script, iv. an executor, associated with said renderer, operable to execute animating of said rendered enhanced believability character, wherein said behavior generators are configured to continue to generate behavior elements during execution of said animating of said rendered enhanced believability character in accordance with said defined time intervals and said renderer continues to render the enhanced believability character in accordance with respective ones of said generated behavior elements as said behavior elements are added to said unified animation script during said execution of the animating of the rendered enhanced believability character, said unifying scripter randomly selecting elements from different ones of said behavior generators in response to stimuli for addition to said unified animation script. | 1. An apparatus comprising a computer processor for animating a moving and speaking enhanced-believability character in real time, comprising: i. a plurality of behavior generators each responsible for a respective aspect of facial behavior, at least some of said generators being configured with a respective time definer defining time intervals and generating behavior elements in accordance with said defined time intervals; ii. a unifying scripter, associated with said behavior generators, said unifying scripter operable to combine said generated elements into a unified animation script for said enhanced believability character; and iii. a renderer, associated with said unifying scripter, said renderer operable to render said enhanced believability character in accordance with said unified animation script, iv. an executor, associated with said renderer, operable to execute animating of said rendered enhanced believability character, wherein said behavior generators are configured to continue to generate behavior elements during execution of said animating of said rendered enhanced believability character in accordance with said defined time intervals and said renderer continues to render the enhanced believability character in accordance with respective ones of said generated behavior elements as said behavior elements are added to said unified animation script during said execution of the animating of the rendered enhanced believability character, said unifying scripter randomly selecting elements from different ones of said behavior generators in response to stimuli for addition to said unified animation script. 13. An apparatus according to claim 1 , wherein said renderer is configured to render said character on a frame-by-frame basis. | 0.660428 |
7,769,578 | 14 | 15 | 14. The computer program product of claim 9 , further comprising: computer useable program code for displaying a search result list of Web pages relevant to said unknown word as found by said Internet search engine in response to said instruction given by a user for executing said search for said unknown word for which said link has been set by said setting of said link; computer useable program code for displaying an unknown word related Web page which has been selected from said search result list by said user; and computer useable program code for generating a translation word registration screen which allows said user to edit and register a translation word for said unknown word, and registering said translation word for said unknown word in said at least one dictionary. | 14. The computer program product of claim 9 , further comprising: computer useable program code for displaying a search result list of Web pages relevant to said unknown word as found by said Internet search engine in response to said instruction given by a user for executing said search for said unknown word for which said link has been set by said setting of said link; computer useable program code for displaying an unknown word related Web page which has been selected from said search result list by said user; and computer useable program code for generating a translation word registration screen which allows said user to edit and register a translation word for said unknown word, and registering said translation word for said unknown word in said at least one dictionary. 15. The computer program product of claim 14 , further comprising computer useable program code for translating said unknown word related Web page displayed by said displaying of said unknown word related Web page, into said second language. | 0.866851 |
9,921,945 | 4 | 5 | 4. The method of claim 3 , wherein the step of the presenting the results of the comparing further comprises: displaying, in a result window in a graphical user interface display, indications of success or failure of matching the total numbers of the plurality of the subsets of the first plurality of XML data statements generated by converting an associated one of the different JSON script statements to the corresponding total numbers of the subsets of the second plurality of XML statements generated in response to an associated one of the different SQL query statements, and of matching the data values of the individual ones of the subsets of the first plurality of XML statements to the data values of the corresponding ones of the subsets of the second plurality of XML statements. | 4. The method of claim 3 , wherein the step of the presenting the results of the comparing further comprises: displaying, in a result window in a graphical user interface display, indications of success or failure of matching the total numbers of the plurality of the subsets of the first plurality of XML data statements generated by converting an associated one of the different JSON script statements to the corresponding total numbers of the subsets of the second plurality of XML statements generated in response to an associated one of the different SQL query statements, and of matching the data values of the individual ones of the subsets of the first plurality of XML statements to the data values of the corresponding ones of the subsets of the second plurality of XML statements. 5. The method of claim 4 , wherein the step of the presenting the results of the comparing further comprises, in response to a selection of one of the result window JSON script statements, SQL query statements, the XML statements of the subsets of the first plurality of XML statements or the XML statements of the second plurality of XML statements: invoking a detail window in the graphical user interface display that provides detail data of the selected one of the JSON script statements, SQL query statements, the XML statements of the subsets of the first plurality of XML statements and the XML statements of the second plurality of XML statements; and invoking a spreadsheet window in the graphical user interface displays at least one of the XML statements of the subsets of the first plurality of XML statements and the XML statements of the second plurality of XML statements that are relevant to the selected one of the JSON script statements, SQL query statements, the XML statements of the subsets of the first plurality of XML statements and the XML statements of the second plurality of XML statements. | 0.826774 |
8,538,687 | 1 | 5 | 1. A system for guidance and navigation in a building, comprising: a module for obtaining locations of one or more people in the building; a module for selecting a route based on the locations in a building; a module for processing the route into waypoints and segments; a module for associating semantic information with waypoints; a module for processing the waypoints and segments into navigation commands formed from a sentence template; and a module for providing and associating audio tones with waypoints; and wherein: the system comprising the modules is implemented on non-transitory computer readable media; and the audio tones are for distinguishing waypoints from one another and pulse rates for indicating various distances of the recipient of the audio from a waypoint. | 1. A system for guidance and navigation in a building, comprising: a module for obtaining locations of one or more people in the building; a module for selecting a route based on the locations in a building; a module for processing the route into waypoints and segments; a module for associating semantic information with waypoints; a module for processing the waypoints and segments into navigation commands formed from a sentence template; and a module for providing and associating audio tones with waypoints; and wherein: the system comprising the modules is implemented on non-transitory computer readable media; and the audio tones are for distinguishing waypoints from one another and pulse rates for indicating various distances of the recipient of the audio from a waypoint. 5. The system of claim 1 wherein: the module for selecting a route in a building recalls locations of a person to identify a route of ingress followed by the person; and the module for selecting a route computes a reverse of the route of ingress and selects the reverse as a route of egress. | 0.746957 |
8,775,325 | 8 | 10 | 8. The method of claim 1 , wherein the social advertisement and a plurality of stories are sent for display on the client device of the user. | 8. The method of claim 1 , wherein the social advertisement and a plurality of stories are sent for display on the client device of the user. 10. The method of claim 8 , wherein the feed is presented such that the viewing user cannot determine that the story selected for display as a social advertisement is sponsored by an advertiser. | 0.954736 |
7,558,841 | 2 | 3 | 2. The method of claim 1 , further comprising sending a status message to the user interface when the search response packet does not contain the at least one search result to the search query for data. | 2. The method of claim 1 , further comprising sending a status message to the user interface when the search response packet does not contain the at least one search result to the search query for data. 3. The method of claim 2 , wherein the status message comprises a notification that no results were returned for the search query for data. | 0.972333 |
8,620,909 | 1 | 7 | 1. A computer-implemented method for contextual personalized search, the method comprising: using a computer system to execute method steps comprising: accessing a knowledge base comprising a hierarchy of nodes, each node associated with a concept, each concept being an instance of a category, wherein one or more documents are mapped to each of the nodes of the knowledge base; receiving an input query for a search for one or more of the documents mapped to the nodes, the input query comprising a plurality of components; mapping at least some of the components of the search query into the knowledge base, each of the at least some of the components mapped to at least one of the nodes of the knowledge base having a concept that matches the component as a query concept; matching the query concepts to documents mapped to the knowledge base that match the query concepts, the matching performed by: traversing the hierarchy of the knowledge base to match nodes of each of the query concepts across other nodes in the hierarchy of the knowledge base to a plurality of target nodes, at least one of the query concepts being in a first category and being a) matched using transitivity from the first category through at least one second category to at least one of the target nodes in a third category, or being b) matched using transitive closure to a plurality of the target nodes in the first category; selecting, as matches for the input query, each of the documents mapped to one of the target nodes, the selected documents being target documents for the input query; scoring each of the target documents against each of the query concepts to provide a score for each of the target documents; and generating a search result for the input query, the search result comprising at least some of the target documents in ranked order based on the score for each target document. | 1. A computer-implemented method for contextual personalized search, the method comprising: using a computer system to execute method steps comprising: accessing a knowledge base comprising a hierarchy of nodes, each node associated with a concept, each concept being an instance of a category, wherein one or more documents are mapped to each of the nodes of the knowledge base; receiving an input query for a search for one or more of the documents mapped to the nodes, the input query comprising a plurality of components; mapping at least some of the components of the search query into the knowledge base, each of the at least some of the components mapped to at least one of the nodes of the knowledge base having a concept that matches the component as a query concept; matching the query concepts to documents mapped to the knowledge base that match the query concepts, the matching performed by: traversing the hierarchy of the knowledge base to match nodes of each of the query concepts across other nodes in the hierarchy of the knowledge base to a plurality of target nodes, at least one of the query concepts being in a first category and being a) matched using transitivity from the first category through at least one second category to at least one of the target nodes in a third category, or being b) matched using transitive closure to a plurality of the target nodes in the first category; selecting, as matches for the input query, each of the documents mapped to one of the target nodes, the selected documents being target documents for the input query; scoring each of the target documents against each of the query concepts to provide a score for each of the target documents; and generating a search result for the input query, the search result comprising at least some of the target documents in ranked order based on the score for each target document. 7. The method of claim 1 , wherein matching using transitive closure comprises using an attribute index of a concept referring to a set of multiple concepts within the same category forming a parent-child relationship, the index comprising computing transitive closure along a specified direction in the parent-child relationship for indexing all reachable concepts moving in the specified direction given a specific concept in the category. | 0.729779 |
8,812,974 | 13 | 16 | 13. An apparatus comprising: a communications fabric; a memory coupled to the communications fabric, wherein the memory contains computer executable program code; a communications unit coupled to the communications fabric; an input/output unit coupled to the communications fabric; a display coupled to the communications fabric; and a processor unit coupled to the communications fabric, wherein the processor unit executes the computer executable program code to cause the apparatus to: create a widget properties dialog; receive properties and validation rules from each source of one or more sources that are associated with the widget properties dialog to form received information, wherein each source is one of a dashboard application or a content provider; create a group of tabs in the widget properties dialog using the received information, wherein the group of tabs contains a general tab and a group of content tabs, wherein the general tab is associated the dashboard application, wherein each content tab is specific to an instance of a content provider that comprises one of the one or more sources of the received information for the respective content tab, and wherein each content tab is specific to an instance of a content type that is associated with at least one content-specific feature of an object received from the instance of the content provider for the respective content tab; determine whether a change to the widget properties dialog is confirmed, wherein the change includes one or more alterations to property information from the one or more sources; after the change to the widget properties dialog is confirmed, validate each tab in the group of tabs using the validation rules to generate a changed widget, wherein validating each tab comprises using the validation rules to validate the one or more alterations to the property information of the change; and present the changed widget for display in a user interface. | 13. An apparatus comprising: a communications fabric; a memory coupled to the communications fabric, wherein the memory contains computer executable program code; a communications unit coupled to the communications fabric; an input/output unit coupled to the communications fabric; a display coupled to the communications fabric; and a processor unit coupled to the communications fabric, wherein the processor unit executes the computer executable program code to cause the apparatus to: create a widget properties dialog; receive properties and validation rules from each source of one or more sources that are associated with the widget properties dialog to form received information, wherein each source is one of a dashboard application or a content provider; create a group of tabs in the widget properties dialog using the received information, wherein the group of tabs contains a general tab and a group of content tabs, wherein the general tab is associated the dashboard application, wherein each content tab is specific to an instance of a content provider that comprises one of the one or more sources of the received information for the respective content tab, and wherein each content tab is specific to an instance of a content type that is associated with at least one content-specific feature of an object received from the instance of the content provider for the respective content tab; determine whether a change to the widget properties dialog is confirmed, wherein the change includes one or more alterations to property information from the one or more sources; after the change to the widget properties dialog is confirmed, validate each tab in the group of tabs using the validation rules to generate a changed widget, wherein validating each tab comprises using the validation rules to validate the one or more alterations to the property information of the change; and present the changed widget for display in a user interface. 16. The apparatus of claim 13 , wherein the general tab is further associated with information associated with a dashboard application and information common across the group of content tabs. | 0.851246 |
9,990,926 | 6 | 7 | 6. The method of claim 1 , further comprising: parsing, by the processor, a second speech sample, spoken by another user, into another keyword phrase sample and another command phrase sample; identifying, by the text-dependent speaker ID circuit, the other user as the speaker of the other keyword phrase sample; associating, by the processor, the other command phrase sample with the identified other user; determining, by the processor, if the other command phrase sample in conjunction with one or more earlier command phrase samples associated with the other user is sufficient command phrase sampling to enroll the other user in the text-independent speaker ID circuit, the other command phrase sample and the one or more earlier command phrase samples associated with the other user together making up at least two command phrase samples associated with the other user; and enrolling, by the processor, the other user in the text-independent speaker ID circuit using the at least two command phrase samples associated with the other user after the determining there is sufficient command phrase sampling to enroll the other user. | 6. The method of claim 1 , further comprising: parsing, by the processor, a second speech sample, spoken by another user, into another keyword phrase sample and another command phrase sample; identifying, by the text-dependent speaker ID circuit, the other user as the speaker of the other keyword phrase sample; associating, by the processor, the other command phrase sample with the identified other user; determining, by the processor, if the other command phrase sample in conjunction with one or more earlier command phrase samples associated with the other user is sufficient command phrase sampling to enroll the other user in the text-independent speaker ID circuit, the other command phrase sample and the one or more earlier command phrase samples associated with the other user together making up at least two command phrase samples associated with the other user; and enrolling, by the processor, the other user in the text-independent speaker ID circuit using the at least two command phrase samples associated with the other user after the determining there is sufficient command phrase sampling to enroll the other user. 7. The method of claim 6 , further comprising identifying, by the text-independent speaker ID circuit, the other user as the speaker of a third speech sample, spoken by the other user after the enrolling of the other user in the text-independent speaker ID circuit. | 0.906294 |
9,037,531 | 2 | 4 | 2. The method of claim 1 , further comprising: identifying the preferences of the particular user; and generating the user preference profile information identifying the preferences of the particular user. | 2. The method of claim 1 , further comprising: identifying the preferences of the particular user; and generating the user preference profile information identifying the preferences of the particular user. 4. The method of claim 2 , wherein the preferences of the particular user are identified by analyzing user actions of the particular user on an online social network. | 0.901308 |
9,798,813 | 1 | 2 | 1. A method of resolving uncoordinated person objects and person-related objects in a database, the method including: receiving a query directed to a first person for objects stored in a database, in which multiple users in multiple departments created uncoordinated person objects that do not share a common key, and in which the person objects are linked to person-related objects; identifying a plurality of candidate person objects responsive to the query for the first person, wherein the identified candidate person objects share at least some matching data; transmitting data for display to a user that lists the candidate person objects; receiving data from the user specifying linking among the candidate person objects; linking the specified candidate person objects to a coordinating customer relations management (CRM) object using a system-generated unique person identifier as a common key and preserving linkage to respective person-related objects associated with the specified candidate person objects, thereby creating a first person-related set; identifying one of the person objects in the first person-related set as a lead active person object; receiving a subsequent request for CRM data related to the first person, retrieving the coordinating CRM object, and using the links from the coordinating CRM object to at least some coordinated person objects in the first person-related set; and transmitting responsive data for display that lists data from the coordinated person objects, featuring data from the lead active person object. | 1. A method of resolving uncoordinated person objects and person-related objects in a database, the method including: receiving a query directed to a first person for objects stored in a database, in which multiple users in multiple departments created uncoordinated person objects that do not share a common key, and in which the person objects are linked to person-related objects; identifying a plurality of candidate person objects responsive to the query for the first person, wherein the identified candidate person objects share at least some matching data; transmitting data for display to a user that lists the candidate person objects; receiving data from the user specifying linking among the candidate person objects; linking the specified candidate person objects to a coordinating customer relations management (CRM) object using a system-generated unique person identifier as a common key and preserving linkage to respective person-related objects associated with the specified candidate person objects, thereby creating a first person-related set; identifying one of the person objects in the first person-related set as a lead active person object; receiving a subsequent request for CRM data related to the first person, retrieving the coordinating CRM object, and using the links from the coordinating CRM object to at least some coordinated person objects in the first person-related set; and transmitting responsive data for display that lists data from the coordinated person objects, featuring data from the lead active person object. 2. The method of claim 1 , wherein the lead active person object is identified based on most recent account activity in the first person-related set. | 0.807494 |
9,122,710 | 1 | 8 | 1. A computer-implemented method for automatically identifying references to a new business within content returned from an online source, the method comprising: receiving content data from the online source; automatically determining, using an analysis of the content data, whether the content data includes at least one reference to the new business, wherein the analysis of the content data includes implementing a particular pattern recognition algorithm that is configured to process one or more text patterns extracted from the content data; in an instance in which the content data includes the new business reference, determining whether data representing the new business is already stored in a business repository; and in an instance in which the data representing the new business is not already stored in the business repository, automatically determining, based on at least one data quality signal associated with the content data, whether the new business reference is verified; and storing data representing the new business in the business repository in an instance in which the new business reference is verified. | 1. A computer-implemented method for automatically identifying references to a new business within content returned from an online source, the method comprising: receiving content data from the online source; automatically determining, using an analysis of the content data, whether the content data includes at least one reference to the new business, wherein the analysis of the content data includes implementing a particular pattern recognition algorithm that is configured to process one or more text patterns extracted from the content data; in an instance in which the content data includes the new business reference, determining whether data representing the new business is already stored in a business repository; and in an instance in which the data representing the new business is not already stored in the business repository, automatically determining, based on at least one data quality signal associated with the content data, whether the new business reference is verified; and storing data representing the new business in the business repository in an instance in which the new business reference is verified. 8. The method of claim 1 , wherein the content data is unstructured. | 0.967711 |
8,583,421 | 1 | 5 | 1. A method of key press prediction on a touch-based device, comprising: registering a position of a touch press attempt on an icon among a plurality of icons presented on the touch-base device; calculating a distance from a reference point of the icon to the position; calculating a psychomotor probability for each icon in the plurality of icons; calculating a linguistic probability for each icon in the plurality of icons; calculating a predictive index for each icon in the plurality of icons based on the psychomotor probability and the linguistic probability; and registering as a user selected icon, an icon with one among a highest predictive index and a probability higher than a predetermined absolute value, wherein for the psychomotor probability calculation, a distribution of finger presses is defined by one among a distance of an x-y position from a center of an icon or key or by a distance of an x-y position from a centroid of pertinent finger presses related to the icon or key, and wherein the distribution of finger presses is a parameter that is standardized using z-scores which allow the determination of a likelihood of an intended key press for specific keys. | 1. A method of key press prediction on a touch-based device, comprising: registering a position of a touch press attempt on an icon among a plurality of icons presented on the touch-base device; calculating a distance from a reference point of the icon to the position; calculating a psychomotor probability for each icon in the plurality of icons; calculating a linguistic probability for each icon in the plurality of icons; calculating a predictive index for each icon in the plurality of icons based on the psychomotor probability and the linguistic probability; and registering as a user selected icon, an icon with one among a highest predictive index and a probability higher than a predetermined absolute value, wherein for the psychomotor probability calculation, a distribution of finger presses is defined by one among a distance of an x-y position from a center of an icon or key or by a distance of an x-y position from a centroid of pertinent finger presses related to the icon or key, and wherein the distribution of finger presses is a parameter that is standardized using z-scores which allow the determination of a likelihood of an intended key press for specific keys. 5. The method of claim 1 , wherein the method performs post-hoc auto-correction after detection of completion of a word. | 0.781818 |
4,241,329 | 8 | 10 | 8. In a speech analysis system in which an audio signal is spectrum analyzed for recognizing at least one predetermined keyword in a continuous audio signal, each said keyword being characterized by a template having at least one target pattern representing a plurality of short-term power spectra spaced apart in real time, an analysis method comprising the steps of repeatedly evaluating electrical signals representing a set of parameters determining a short-term power spectrum of said audio signal within each of a plurality of equal duration sampling intervals thereby to generate an uninterrupted time-ordered sequence of short-term audio power spectrum frames, repeatedly selecting from said sequence of frames, one first frame and at least one later occurring frame to form a multi-frame pattern, comparing each thus formed multi-frame pattern with each first target pattern of each keyword template, deciding whether each said multi-frame pattern corresponds to a first target pattern of a keyword template, for each multi-frame pattern which, according to said deciding step, corresponds to a said first target pattern of a potential candidate keyword, selecting later occurring short-term power spectra to form later occurring multi-frame patterns, deciding whether said later occurring multi-frame patterns correspond respectively to successive target patterns of said potential candidate keyword template, identifying electrical signals representing a candidate keyword template when said selected multi-frame patterns correspond respectively to the target patterns of a said keyword template, normalizing electrical signals representing the time duration spacings between multi-frame patterns corresponding to said candidate word, and applying a prosodic test to said normalized time duration spacings, wherein said normalized time duration spacings for a candidate word must meet the timing criteria imposed by said prosodic test before a said candidate word is accepted as a recognized keyword. | 8. In a speech analysis system in which an audio signal is spectrum analyzed for recognizing at least one predetermined keyword in a continuous audio signal, each said keyword being characterized by a template having at least one target pattern representing a plurality of short-term power spectra spaced apart in real time, an analysis method comprising the steps of repeatedly evaluating electrical signals representing a set of parameters determining a short-term power spectrum of said audio signal within each of a plurality of equal duration sampling intervals thereby to generate an uninterrupted time-ordered sequence of short-term audio power spectrum frames, repeatedly selecting from said sequence of frames, one first frame and at least one later occurring frame to form a multi-frame pattern, comparing each thus formed multi-frame pattern with each first target pattern of each keyword template, deciding whether each said multi-frame pattern corresponds to a first target pattern of a keyword template, for each multi-frame pattern which, according to said deciding step, corresponds to a said first target pattern of a potential candidate keyword, selecting later occurring short-term power spectra to form later occurring multi-frame patterns, deciding whether said later occurring multi-frame patterns correspond respectively to successive target patterns of said potential candidate keyword template, identifying electrical signals representing a candidate keyword template when said selected multi-frame patterns correspond respectively to the target patterns of a said keyword template, normalizing electrical signals representing the time duration spacings between multi-frame patterns corresponding to said candidate word, and applying a prosodic test to said normalized time duration spacings, wherein said normalized time duration spacings for a candidate word must meet the timing criteria imposed by said prosodic test before a said candidate word is accepted as a recognized keyword. 10. The method of claim 8 wherein said applying step comprises the steps of applying a likelihood statistic function to said normalized spacings and accepting said candidate word if the likelihood statistic exceeds a predetermined minimum threshold. | 0.844569 |
8,260,809 | 1 | 6 | 1. A computer-implemented system comprising: one or more processors; a recognition component that is executable by the one or more processors to receive a partial query input as voice signals of a user with at least one other sensed input type comprising text, image or audio; a classifier component, executable by the one or more processors, that processes the partial query input and infers in real-time multiple different search goals based on the partial query input by accessing one or more query databases that store query information and from which similar or matching character sets, terms or phrases are derived for generating at least one complete query, the classifier comprising a support vector machine to find a hyperspace in a space of possible inputs to distinguish triggering input events from non-triggering input events, the classifier explicitly trained using generic training data and implicitly trained by observing user behavior; a query formulation component, executable by the one or more processors, that generates the at least one complete query based on the multiple different search goals; and a search engine, executable by the one or more processors, that receives the at least one complete query, presents the at least one complete query to the user for editing, and processes the at least one complete query to return search results for each of the at least one complete query, the search results based on a confidence value output by the voice recognition component indicating the confidence of converted voice signals relative to the partial query input as voice signals of the user. | 1. A computer-implemented system comprising: one or more processors; a recognition component that is executable by the one or more processors to receive a partial query input as voice signals of a user with at least one other sensed input type comprising text, image or audio; a classifier component, executable by the one or more processors, that processes the partial query input and infers in real-time multiple different search goals based on the partial query input by accessing one or more query databases that store query information and from which similar or matching character sets, terms or phrases are derived for generating at least one complete query, the classifier comprising a support vector machine to find a hyperspace in a space of possible inputs to distinguish triggering input events from non-triggering input events, the classifier explicitly trained using generic training data and implicitly trained by observing user behavior; a query formulation component, executable by the one or more processors, that generates the at least one complete query based on the multiple different search goals; and a search engine, executable by the one or more processors, that receives the at least one complete query, presents the at least one complete query to the user for editing, and processes the at least one complete query to return search results for each of the at least one complete query, the search results based on a confidence value output by the voice recognition component indicating the confidence of converted voice signals relative to the partial query input as voice signals of the user. 6. The system of claim 1 , wherein the classifier infers the multiple different search goals based on the partial query input as voice signals of the user and at least one other sensed input type. | 0.646209 |
8,849,835 | 9 | 15 | 9. A non-transitory computer readable storage medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more computing devices, cause the one or more computing devices to: generate first scores indicating respective likelihood values that data stored in a first entry in a first database and data stored in second entries in a second database occur in a common document, the second database being separate from the first database, each of the first entry and the second entries including respective fields, and a particular field, of the respective fields, including information regarding a particular attribute of an object being represented by the first entry; identify, based on the first scores, two or more of the second entries in the second database; generate second scores for the two or more of the second entries, the two or more of the second entries including a particular second entry, the second scores including a second score for the particular second entry, the respective fields including first fields in the first entry and second fields in the particular second entry, the first fields including the particular field, and the second score for the particular second entry being generated based on comparing data stored in the first fields in the first entry and data stored in the second fields of the particular second entry; determine that the second score satisfies a threshold; identify the particular second entry, of the two or more of the second entries, based on determining that the second score satisfies the threshold; and store information associating the first entry and the particular second entry. | 9. A non-transitory computer readable storage medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more computing devices, cause the one or more computing devices to: generate first scores indicating respective likelihood values that data stored in a first entry in a first database and data stored in second entries in a second database occur in a common document, the second database being separate from the first database, each of the first entry and the second entries including respective fields, and a particular field, of the respective fields, including information regarding a particular attribute of an object being represented by the first entry; identify, based on the first scores, two or more of the second entries in the second database; generate second scores for the two or more of the second entries, the two or more of the second entries including a particular second entry, the second scores including a second score for the particular second entry, the respective fields including first fields in the first entry and second fields in the particular second entry, the first fields including the particular field, and the second score for the particular second entry being generated based on comparing data stored in the first fields in the first entry and data stored in the second fields of the particular second entry; determine that the second score satisfies a threshold; identify the particular second entry, of the two or more of the second entries, based on determining that the second score satisfies the threshold; and store information associating the first entry and the particular second entry. 15. The non-transitory computer readable storage medium of claim 9 , where the instructions further comprise: one or more instructions to: identify entries that are common to both the first database and the second database; generate respective occurrence counts for the identified entries, the respective occurrence counts indicating corresponding quantities of documents, among a plurality of documents, associated with data stored in the identified entries; and select, as the first entry, one of the identified entries having a largest one of the respective occurrence counts. | 0.650784 |
9,740,750 | 16 | 17 | 16. The system of claim 11 , wherein determining a winning and losing score improvement list in each selected pair from the search query data for the search query comprises: selecting a user preferred search result in the one or more search results associated with the search query based on the user selection data associated with the search query; and determining that the user preferred search result has a higher ranking in the search results responsive to the search query for one of the score improvement lists of the selected pair; and assigning the score improvement list having the higher ranking user preferred search result as the winning score improvement list. | 16. The system of claim 11 , wherein determining a winning and losing score improvement list in each selected pair from the search query data for the search query comprises: selecting a user preferred search result in the one or more search results associated with the search query based on the user selection data associated with the search query; and determining that the user preferred search result has a higher ranking in the search results responsive to the search query for one of the score improvement lists of the selected pair; and assigning the score improvement list having the higher ranking user preferred search result as the winning score improvement list. 17. The system of claim 16 , wherein selecting the user preferred search result comprises selecting a search result of the one or more search results that has been selected by a majority of users, or selecting a search result of the one or more search results with greatest user time spent on the resource associated with the search result. | 0.919086 |
8,983,900 | 13 | 14 | 13. A non-transitory computer-readable medium having computer-executable instructions stored thereon that, when executed by a processor, cause the processor to perform a method for combining online transactional processing and online analytical processing in an in-memory database, comprising: retrieving two or more tables from an online transaction processing; identifying related tables among the two or more tables; determining relationships between the related tables, wherein determining the relationships comprises analyzing metadata of the related tables; determining a measure based on the relationships; and outputting the measure. | 13. A non-transitory computer-readable medium having computer-executable instructions stored thereon that, when executed by a processor, cause the processor to perform a method for combining online transactional processing and online analytical processing in an in-memory database, comprising: retrieving two or more tables from an online transaction processing; identifying related tables among the two or more tables; determining relationships between the related tables, wherein determining the relationships comprises analyzing metadata of the related tables; determining a measure based on the relationships; and outputting the measure. 14. The non-transitory computer-readable medium of claim 13 , wherein the tables of the online transaction processing are replicated in the in-memory database. | 0.769565 |
9,400,789 | 17 | 23 | 17. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: clustering a plurality of first documents into one or more first document groups, wherein each of the one or more first document groups is associated with a respective author proper name; after clustering the plurality of first documents into the one or more first document groups: receiving author information from an author; generating a query that specifies a particular name of the author and one or more items of the author information received from the author; generating a result list of one or more documents that satisfy the query, the documents being ranked according to a document rank; ranking the one or more first document groups based on how many documents in the result list are included in each of the one or more first document groups, the ranking favoring first document groups having more documents from the result over first document groups having fewer documents from the result list; and providing data describing the one or more first document groups in an order according to the ranking for selection by the author for inclusion in an author profile for the author that identifies documents classified as being authored by the author. | 17. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: clustering a plurality of first documents into one or more first document groups, wherein each of the one or more first document groups is associated with a respective author proper name; after clustering the plurality of first documents into the one or more first document groups: receiving author information from an author; generating a query that specifies a particular name of the author and one or more items of the author information received from the author; generating a result list of one or more documents that satisfy the query, the documents being ranked according to a document rank; ranking the one or more first document groups based on how many documents in the result list are included in each of the one or more first document groups, the ranking favoring first document groups having more documents from the result over first document groups having fewer documents from the result list; and providing data describing the one or more first document groups in an order according to the ranking for selection by the author for inclusion in an author profile for the author that identifies documents classified as being authored by the author. 23. The computer program product of claim 17 , wherein ranking the one or more first document groups comprises: for each of the one or more first document groups: determining a count of documents that are in both the first document group and among the one or more documents that satisfy the query; determining a respective rank for each of the documents that are in both the first document group and among the one or more documents that satisfy the query; and determining a name matching score, wherein the name matching score represents a similarity between the name associated with the first document group and the particular name of the author; calculating a respective score for the first document group based on the count of documents, the respective rank for each of the documents that are in both the first document group and among the one or more documents that satisfy the query, and the name matching score; and ranking the one or more first document groups based on their respective scores. | 0.500499 |
8,396,736 | 1 | 14 | 1. A method, performed by a computer system, for generating a process model representation for each of a plurality of activity chunks in a process such that each process model representation is arranged to be displayed on a single page, the method comprising: receiving, by one or more processors of the computer system, a Work Product/Activities/Roles (WAR) template for a process, the WAR template defining each work product that is used by the process, each activity performed by the process, and each role that performs an activity in the process, each activity being associated with one of a plurality of activity chunks defined for the process; generating, by one or more processors of the computer system, and for each of the activity chunks, a process activity template, each process activity template defining: any inputs used by the activity chunk; entry criteria defining when the activity chunk is to be performed; which role is responsible for performing each activity in the activity chunk; any outputs produced by the activity chunk; and exit criteria defining when the activity chunk is completed; generating, by one or more processors of the computer system, and for each process activity template, a process model representation, each process model representation being arranged to be displayed on a single page, each process model representation comprising: a graphical representation of the flow between the activities in the represented activity chunk; and a graphical representation of the inputs, entry criteria, roles involved in performing the activities of the represented activity chunk, outputs, and exit criteria. | 1. A method, performed by a computer system, for generating a process model representation for each of a plurality of activity chunks in a process such that each process model representation is arranged to be displayed on a single page, the method comprising: receiving, by one or more processors of the computer system, a Work Product/Activities/Roles (WAR) template for a process, the WAR template defining each work product that is used by the process, each activity performed by the process, and each role that performs an activity in the process, each activity being associated with one of a plurality of activity chunks defined for the process; generating, by one or more processors of the computer system, and for each of the activity chunks, a process activity template, each process activity template defining: any inputs used by the activity chunk; entry criteria defining when the activity chunk is to be performed; which role is responsible for performing each activity in the activity chunk; any outputs produced by the activity chunk; and exit criteria defining when the activity chunk is completed; generating, by one or more processors of the computer system, and for each process activity template, a process model representation, each process model representation being arranged to be displayed on a single page, each process model representation comprising: a graphical representation of the flow between the activities in the represented activity chunk; and a graphical representation of the inputs, entry criteria, roles involved in performing the activities of the represented activity chunk, outputs, and exit criteria. 14. The method of claim 1 , wherein each process activity template also defines a purpose and a process context of the activity chunk. | 0.875465 |
7,698,298 | 1 | 5 | 1. A system for electronically managing remote review of documents for legal purposes, comprising: a repository of electronically stored documents; a host system comprising: an export tool configured to export one or more of the documents for remote review by a reviewer lacking access to the repository; and an import tool configured to import designations of the reviewer back into the repository thereby enabling electronic integration of remotely made decisions into the repository; and a portable storage device including instructions for executing an electronic decision tool for remote use by the reviewer, the decision tool configured to enable the reviewer to electronically designate discovery categorizations or discovery treatments of the documents, the designated discovery categorizations or discovery treatments assisting a disclosing party receiving a discovery request for document production from a requesting party in identifying documents to be produced to the requesting party in response to the discovery request for document production, such that privileged document content is protected from inadvertent production and waiver of at least one of attorney client privilege and attorney work product doctrine; the electronic decision tool electronically recording designated discovery categories or discovery treatments and creating an electronic file of the designated discovery categories or discovery treatments, the electronic file of the designated discovery categories or discovery treatments being a stand-alone file independent of the documents and electronic copies of the documents. | 1. A system for electronically managing remote review of documents for legal purposes, comprising: a repository of electronically stored documents; a host system comprising: an export tool configured to export one or more of the documents for remote review by a reviewer lacking access to the repository; and an import tool configured to import designations of the reviewer back into the repository thereby enabling electronic integration of remotely made decisions into the repository; and a portable storage device including instructions for executing an electronic decision tool for remote use by the reviewer, the decision tool configured to enable the reviewer to electronically designate discovery categorizations or discovery treatments of the documents, the designated discovery categorizations or discovery treatments assisting a disclosing party receiving a discovery request for document production from a requesting party in identifying documents to be produced to the requesting party in response to the discovery request for document production, such that privileged document content is protected from inadvertent production and waiver of at least one of attorney client privilege and attorney work product doctrine; the electronic decision tool electronically recording designated discovery categories or discovery treatments and creating an electronic file of the designated discovery categories or discovery treatments, the electronic file of the designated discovery categories or discovery treatments being a stand-alone file independent of the documents and electronic copies of the documents. 5. The system of claim 1 wherein the import tool is further configured to identify discrepancies between prior designated discovery categories or discovery treatments and present designated discovery categories or discovery treatments. | 0.554924 |
7,516,198 | 6 | 7 | 6. The network node of claim 1 , wherein the application resource is configured for caching the selected network parameters and identifiers for identification of subsequent packets received for the identified flow of data packets and outputting according to the selected network parameters. | 6. The network node of claim 1 , wherein the application resource is configured for caching the selected network parameters and identifiers for identification of subsequent packets received for the identified flow of data packets and outputting according to the selected network parameters. 7. The network node of claim 6 , wherein the application resource is configured for assigning the selected network parameters to the subsequent packets received for the identified flow of data packets based on the cached selected network parameters and identifiers, independent of the XML tags specifying the prescribed user-selected quality of service attributes within the subsequent packets. | 0.875631 |
8,452,795 | 14 | 18 | 14. A computer-implemented method, comprising: obtaining a plurality of class instance pairs derived from a plurality of documents by applying one or more extraction patterns to the plurality of documents, each class-instance pair comprising class text naming an entity class and entity text naming a particular instance of the entity class; calculating a weight for each class-instance pair according to a frequency score and a diversity score for the class-instance pair, wherein the frequency score of the class-instance pair is based on a number of times the class-instance pair was derived from the plurality of documents, and wherein the diversity score of the class-instance pair is based on a number of distinct extraction patterns used to extract the class-instance pair; receiving a plurality of candidate text queries; generating one or more query specializations from the plurality of candidate text queries and the plurality of class-instance pairs, wherein each query specialization is the text of one of the candidate text queries modified so that an n-gram in the text of the candidate text query is replaced by the entity text from a class-instance pair having class text matching the n-gram, wherein generating a query specialization from a candidate text query and the class instance pairs comprises: extracting a plurality of n-grams from the candidate text query and extracting a respective context for each extracted n-gram from the candidate text query, the respective context for an extracted n-gram including a prefix context and a suffix context; comparing the extracted n-grams to the class text of the class-instance pairs; identifying an n-gram that matches class text of a first class-instance pair; and generating the query specialization from the entity text of the first class-instance pair and the respective context for the identified n-gram; and storing specialization data, the specialization data associating each of one or more of the candidate text queries with one or more query specializations identified from the candidate text query. | 14. A computer-implemented method, comprising: obtaining a plurality of class instance pairs derived from a plurality of documents by applying one or more extraction patterns to the plurality of documents, each class-instance pair comprising class text naming an entity class and entity text naming a particular instance of the entity class; calculating a weight for each class-instance pair according to a frequency score and a diversity score for the class-instance pair, wherein the frequency score of the class-instance pair is based on a number of times the class-instance pair was derived from the plurality of documents, and wherein the diversity score of the class-instance pair is based on a number of distinct extraction patterns used to extract the class-instance pair; receiving a plurality of candidate text queries; generating one or more query specializations from the plurality of candidate text queries and the plurality of class-instance pairs, wherein each query specialization is the text of one of the candidate text queries modified so that an n-gram in the text of the candidate text query is replaced by the entity text from a class-instance pair having class text matching the n-gram, wherein generating a query specialization from a candidate text query and the class instance pairs comprises: extracting a plurality of n-grams from the candidate text query and extracting a respective context for each extracted n-gram from the candidate text query, the respective context for an extracted n-gram including a prefix context and a suffix context; comparing the extracted n-grams to the class text of the class-instance pairs; identifying an n-gram that matches class text of a first class-instance pair; and generating the query specialization from the entity text of the first class-instance pair and the respective context for the identified n-gram; and storing specialization data, the specialization data associating each of one or more of the candidate text queries with one or more query specializations identified from the candidate text query. 18. The method of claim 14 , further comprising excluding from the extracted n-grams any n-grams that do not match at least one of class text and entity text in the class-instance pairs. | 0.925659 |
8,359,292 | 10 | 11 | 10. The configured medium of claim 7 , wherein the process follows the entry-group-clustering procedure, namely, the process groups nodes into an entry group on the basis of node names, an entry node is a border node of the entry group nodes in the DAG, and the cost accounting shows the entry group name together with the entry node name. | 10. The configured medium of claim 7 , wherein the process follows the entry-group-clustering procedure, namely, the process groups nodes into an entry group on the basis of node names, an entry node is a border node of the entry group nodes in the DAG, and the cost accounting shows the entry group name together with the entry node name. 11. The configured medium of claim 10 , wherein the entry node name identifies a method in a call stack DAG, namely, the method which was called upon entry to code that is represented by the entry group name. | 0.916197 |
5,379,366 | 46 | 47 | 46. The method for representing information in a computer system according to claim 11, further comprising the steps of: establishing user interaction with said knowledge representation database through interaction with a display of said computer system; selecting a view, class, and type of display for a designated active concept record and automatically deriving the selected type of display by reading a subset of the records in said knowledge representation database relative to said active concept, based on stored relationships therein, which subset defines the concepts constituting said selected type of display; assigning icons to said subset of the records according to said selected type of display; organizing and locating said icons in the display space of said computer system according to said selected class, and creating connection icons for interconnections between concept icons located in said display space according to said selected view; detecting user interaction with the icons in said display space; evaluating said icon interaction through the use of decision trees for evaluation of the view, command history, system flags, and icon association for identification of the appropriate process or procedure for response to said interaction; and applying said appropriate process or procedure for response and developing a response to said interaction. | 46. The method for representing information in a computer system according to claim 11, further comprising the steps of: establishing user interaction with said knowledge representation database through interaction with a display of said computer system; selecting a view, class, and type of display for a designated active concept record and automatically deriving the selected type of display by reading a subset of the records in said knowledge representation database relative to said active concept, based on stored relationships therein, which subset defines the concepts constituting said selected type of display; assigning icons to said subset of the records according to said selected type of display; organizing and locating said icons in the display space of said computer system according to said selected class, and creating connection icons for interconnections between concept icons located in said display space according to said selected view; detecting user interaction with the icons in said display space; evaluating said icon interaction through the use of decision trees for evaluation of the view, command history, system flags, and icon association for identification of the appropriate process or procedure for response to said interaction; and applying said appropriate process or procedure for response and developing a response to said interaction. 47. The method for representing information in a computer system according to claim 46, wherein said icon is interpreted as the entities comprising said icon. | 0.9886 |
9,082,125 | 17 | 18 | 17. The method of claim 16 , wherein the analyzing the solicitee responses to the first script template from the first portion of the solicitees comprises: receiving communications over a network, each communication including a solicitee response indicator, wherein for a given communication the solicitee response indicator therein indicates whether a given solicitee has responded to a given solicitation by accepting or rejecting an offer, wherein the given solicitation is related to a given script template of the plurality of script templates; updating a solicitation response table, wherein the solicitation response table comprises a script template identifier having accumulated solicitee responses associated therewith, wherein responsive to the communication module receiving the given communication, the updating module uses the solicitee response indicator that is included therein to update the accumulated solicitee response associated with the given script template; and wherein the step of analyzing includes determining statistics related to accumulated solicitee responses for multiple script identifiers. | 17. The method of claim 16 , wherein the analyzing the solicitee responses to the first script template from the first portion of the solicitees comprises: receiving communications over a network, each communication including a solicitee response indicator, wherein for a given communication the solicitee response indicator therein indicates whether a given solicitee has responded to a given solicitation by accepting or rejecting an offer, wherein the given solicitation is related to a given script template of the plurality of script templates; updating a solicitation response table, wherein the solicitation response table comprises a script template identifier having accumulated solicitee responses associated therewith, wherein responsive to the communication module receiving the given communication, the updating module uses the solicitee response indicator that is included therein to update the accumulated solicitee response associated with the given script template; and wherein the step of analyzing includes determining statistics related to accumulated solicitee responses for multiple script identifiers. 18. The method of claim 17 , further comprising: providing a user with the statistical information; and receiving template selection input from the user, wherein the step of selecting includes employing the user supplied template selection input in the selection of the script template. | 0.933519 |
9,607,267 | 4 | 5 | 4. The method of claim 1 , further comprising determining an assignment of each endorsement to an aspect using a collapsed Gibbs sampling method. | 4. The method of claim 1 , further comprising determining an assignment of each endorsement to an aspect using a collapsed Gibbs sampling method. 5. The method of claim 4 where collapsed Gibbs sampling method uses the equation: P ( y i = k | e i = l , e - i , y - 1 ) ∝ n k | u , - 1 + α ′ ɛ ( u ) + α ′ K × n e | k , - i + β ′ n . | k , i + β ′ ɛ where n k|u,-i is the number of times aspect k is observed for user u, n e|k,-i is the number of times entity e is sampled from aspect k, |ε(u)| is number of entities endorsed by user u, and n •|k,-i is the total number if entities generated from aspect k, such that the above quantities are computed over all endorsement-slots except the i th one. | 0.899471 |
8,244,533 | 7 | 9 | 7. A speech recognition device comprising: a speech data generation section for identifying a start position of a speech region of speech data for which speech recognition is to be performed and generating, from said speech data for which speech recognition is to be performed, a plurality of pieces of speech data including said speech region and a varying period of a preceding non-speech region, where start positions of non-speech regions differ for the plurality of pieces of speech data; a speech recognition engine for performing speech recognition on each of said pieces of speech data to obtain a plurality of recognized results; and a recognized result selection section for selecting a most numerous recognized result from among the plurality of obtained recognized results; wherein said speech data generation section generates a plurality of pieces of speech data whose start positions of non-speech regions differ from speech data for which speech recognition is to be performed by sequentially shifting the start position of said non-speech region to a position preceding by a predetermined time from the start position of the speech region. | 7. A speech recognition device comprising: a speech data generation section for identifying a start position of a speech region of speech data for which speech recognition is to be performed and generating, from said speech data for which speech recognition is to be performed, a plurality of pieces of speech data including said speech region and a varying period of a preceding non-speech region, where start positions of non-speech regions differ for the plurality of pieces of speech data; a speech recognition engine for performing speech recognition on each of said pieces of speech data to obtain a plurality of recognized results; and a recognized result selection section for selecting a most numerous recognized result from among the plurality of obtained recognized results; wherein said speech data generation section generates a plurality of pieces of speech data whose start positions of non-speech regions differ from speech data for which speech recognition is to be performed by sequentially shifting the start position of said non-speech region to a position preceding by a predetermined time from the start position of the speech region. 9. A speech recognition device according to claim 7 , further comprising: an analog to digital converter for converting an input speech signal from analog to digital at a predetermined sampling time interval; and a speech buffer for storing the converted speech data in an order of sampling, wherein said speech data generation section generates a plurality of pieces of speech data whose start positions of non-speech regions differ, by changing positions at which reading from the speech buffer starts. | 0.668857 |
8,694,972 | 9 | 12 | 9. The system of claim 8 wherein the mapping facility examines a second collection of metadata, wherein: the second collection of metadata is for a second foreign class, the second foreign class is created in a second type of foreign object system, the second collection of metadata describes how to access second foreign object instance data, the second foreign object instance data is associated with a second foreign object instance from the second foreign class, and the mapping facility creates second foreign class metadata corresponding to the second collection of metadata, the second foreign class metadata created in a form supported by the single language computing environment; and further comprising: a second object instance, the second object instance: instantiated using the class definition, and referencing the second foreign class metadata and the second foreign object instance. | 9. The system of claim 8 wherein the mapping facility examines a second collection of metadata, wherein: the second collection of metadata is for a second foreign class, the second foreign class is created in a second type of foreign object system, the second collection of metadata describes how to access second foreign object instance data, the second foreign object instance data is associated with a second foreign object instance from the second foreign class, and the mapping facility creates second foreign class metadata corresponding to the second collection of metadata, the second foreign class metadata created in a form supported by the single language computing environment; and further comprising: a second object instance, the second object instance: instantiated using the class definition, and referencing the second foreign class metadata and the second foreign object instance. 12. The system of claim 9 , further comprising: a first virtual machine hosting the first foreign object system; and a second virtual machine hosting the second type of foreign object system. | 0.949148 |
8,457,968 | 8 | 9 | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: receiving an N-best list of speech recognition candidates; receiving a list of current partitions and a belief for each of the current partitions, wherein a partition is a group of dialog states; iterating, in an outer loop, over each of the speech recognition candidates in the N-best list; performing, in an inner loop, a split, update, and recombination process to generate a fixed number of partitions after each speech recognition candidate in the N-best list; and recognizing speech based on the N-best list and the fixed number of partitions. | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: receiving an N-best list of speech recognition candidates; receiving a list of current partitions and a belief for each of the current partitions, wherein a partition is a group of dialog states; iterating, in an outer loop, over each of the speech recognition candidates in the N-best list; performing, in an inner loop, a split, update, and recombination process to generate a fixed number of partitions after each speech recognition candidate in the N-best list; and recognizing speech based on the N-best list and the fixed number of partitions. 9. The system of claim 8 , wherein the split process performs all possible splits on all partitions. | 0.65035 |
7,840,912 | 3 | 4 | 3. The method of claim 1 wherein the dictionary entry comprises multiple motion icons, each motion icon including a graphical depiction of a motion and a textual description of a corresponding meaning. | 3. The method of claim 1 wherein the dictionary entry comprises multiple motion icons, each motion icon including a graphical depiction of a motion and a textual description of a corresponding meaning. 4. The method of claim 3 wherein the motion icons are arranged consistently for a plurality of dictionary entries corresponding to a plurality of chords. | 0.947059 |
8,970,896 | 1 | 5 | 1. A method comprising using at least one hardware processor for: analyzing text in a digital document, to identify a text segment referring to a figure of the digital document; mapping said text segment to said figure; identifying, in said text segment, reference to one or more non-grayscale colors of said figure, to determine a level of importance of said one or more non-grayscale colors to legibility of said figure; and printing said digital document in accordance with the level of importance. | 1. A method comprising using at least one hardware processor for: analyzing text in a digital document, to identify a text segment referring to a figure of the digital document; mapping said text segment to said figure; identifying, in said text segment, reference to one or more non-grayscale colors of said figure, to determine a level of importance of said one or more non-grayscale colors to legibility of said figure; and printing said digital document in accordance with the level of importance. 5. The method according to claim 1 , further comprising decolorizing said figure, wherein said printing is printing in grayscale. | 0.854402 |
8,463,808 | 1 | 4 | 1. A method comprising: generating a query conceptual graph for a search query, the query conceptual graph comprising: a plurality of graph terms, a graph term representing a concept type; a plurality of conceptual relation nodes that each comprise text describing a relationship between two or more of the plurality of graph terms; and a plurality of arcs that each indicate a direction of the relationship described by the text of a corresponding conceptual relation node of the plurality of conceptual relation nodes; identifying at least one set of conceptually similar terms for at least one graph term of the query conceptual graph, the at least one set of conceptually similar terms mapped to the corresponding concept type represented by the respective at least one graph term; searching a plurality of documents in accordance with a search query based at least in part on the query conceptual graph and on the set of conceptually similar terms; selecting a document from the plurality of documents as a potential match to the search query if, when the query conceptual graph is compared to a document conceptual graph for the document, there is at least one corresponding term associated with the query conceptual graph that matches at least one corresponding term associated with the document conceptual graph, wherein the corresponding term associated with each respective conceptual graph comprises at least one or more of: terms representing a concept type, and terms that are conceptually similar to the terms representing concept types; accessing one or more onomasticons, each onomasticon comprising a list of one or more mappings, each mapping comprising a mapping of a predetermined concept type to a corresponding set of conceptually similar terms; and validating that the potential match is a valid match if a set of conceptually similar terms of the query conceptual graph, and a set of conceptually similar terms of the document conceptual graph that is associated with the potentially matching document, map to the same concept type in one or more onomasticons. | 1. A method comprising: generating a query conceptual graph for a search query, the query conceptual graph comprising: a plurality of graph terms, a graph term representing a concept type; a plurality of conceptual relation nodes that each comprise text describing a relationship between two or more of the plurality of graph terms; and a plurality of arcs that each indicate a direction of the relationship described by the text of a corresponding conceptual relation node of the plurality of conceptual relation nodes; identifying at least one set of conceptually similar terms for at least one graph term of the query conceptual graph, the at least one set of conceptually similar terms mapped to the corresponding concept type represented by the respective at least one graph term; searching a plurality of documents in accordance with a search query based at least in part on the query conceptual graph and on the set of conceptually similar terms; selecting a document from the plurality of documents as a potential match to the search query if, when the query conceptual graph is compared to a document conceptual graph for the document, there is at least one corresponding term associated with the query conceptual graph that matches at least one corresponding term associated with the document conceptual graph, wherein the corresponding term associated with each respective conceptual graph comprises at least one or more of: terms representing a concept type, and terms that are conceptually similar to the terms representing concept types; accessing one or more onomasticons, each onomasticon comprising a list of one or more mappings, each mapping comprising a mapping of a predetermined concept type to a corresponding set of conceptually similar terms; and validating that the potential match is a valid match if a set of conceptually similar terms of the query conceptual graph, and a set of conceptually similar terms of the document conceptual graph that is associated with the potentially matching document, map to the same concept type in one or more onomasticons. 4. The method of claim 1 , the identifying the at least one set of conceptually similar terms for the at least one graph term further comprising: determining a plurality of conceptually similar term options in accordance with a semantic sense for a search query concept of the search query; and identifying the at least one set of conceptually similar terms from the plurality of conceptually similar term options. | 0.674528 |
8,825,468 | 7 | 8 | 7. The apparatus of claim 6 wherein the avatar further includes audio elements played on the speaker. | 7. The apparatus of claim 6 wherein the avatar further includes audio elements played on the speaker. 8. The apparatus of claim 7 wherein the audio elements includes a recorded human voice. | 0.985154 |
8,064,576 | 21 | 22 | 21. An integrated communication system, comprising: a communication server that couples among networks of different types, the communication server configured to receive audio data via a first network, wherein the audio data comprises a voicemail message sent to a user of the communication server configured to transform the audio data to text, the communication server comprising: a memory; a processor in communication with the memory, the processor operable to execute a filter/transcribe module, the filter/transcribe module configured to: perform a filtering operation on the voicemail message from a caller to a user comprising searching for predetermined words; perform a rough transcription of the voicemail message; generate an email message to the user containing the rough transcription; receive a request to provide a refined transcription of the voicemail message; request the refined transcription to be performed, wherein requesting comprises sending an audio file of the voicemail message, via one of the networks, to an entity to perform the refined transcription; and an interface module that couples to the communication server, wherein the interface module pulls a plurality of user information from a messaging server of a network, wherein the user information includes information relevant to at least the network. | 21. An integrated communication system, comprising: a communication server that couples among networks of different types, the communication server configured to receive audio data via a first network, wherein the audio data comprises a voicemail message sent to a user of the communication server configured to transform the audio data to text, the communication server comprising: a memory; a processor in communication with the memory, the processor operable to execute a filter/transcribe module, the filter/transcribe module configured to: perform a filtering operation on the voicemail message from a caller to a user comprising searching for predetermined words; perform a rough transcription of the voicemail message; generate an email message to the user containing the rough transcription; receive a request to provide a refined transcription of the voicemail message; request the refined transcription to be performed, wherein requesting comprises sending an audio file of the voicemail message, via one of the networks, to an entity to perform the refined transcription; and an interface module that couples to the communication server, wherein the interface module pulls a plurality of user information from a messaging server of a network, wherein the user information includes information relevant to at least the network. 22. The system of claim 21 , wherein performing a filtering operation includes comparing words in the audio data to one or more items of the plurality of user information. | 0.502907 |
8,113,825 | 1 | 9 | 1. A computer-controlled pyrotechnic matrix display device, comprising: a frame a backplate having a first surface and a second surface, the backplate disposed in the frame; an array of pixels, comprised of individual tubes set within the frame, arranged in a grid having at least two dimensions, each dimension having at least two pixels; an array of solenoid valves for controlling a flow of a flammable gas from a common input to termini of individual pixel tubes and directly into open air, the solenoid valves located on a first side of the backplate; an array of pilot light tubes positioned in front of the termini of the pixel tubes such that flammable gas exiting the pixel tubes contacts flames from the pilot light tubes and combusts, thereby creating a fireball, the pilot light tubes located on a second side of the backplate; a computer having control software to permit convenient scripting and control of all functions, which outputs control data through a parallel, serial, or USB port, said software controlling creation of designs in at least said two dimensions using said pixels; and a circuit board which processes incoming control data from the software and uses the data to actuate and de-actuate the solenoid valves with precise timing. | 1. A computer-controlled pyrotechnic matrix display device, comprising: a frame a backplate having a first surface and a second surface, the backplate disposed in the frame; an array of pixels, comprised of individual tubes set within the frame, arranged in a grid having at least two dimensions, each dimension having at least two pixels; an array of solenoid valves for controlling a flow of a flammable gas from a common input to termini of individual pixel tubes and directly into open air, the solenoid valves located on a first side of the backplate; an array of pilot light tubes positioned in front of the termini of the pixel tubes such that flammable gas exiting the pixel tubes contacts flames from the pilot light tubes and combusts, thereby creating a fireball, the pilot light tubes located on a second side of the backplate; a computer having control software to permit convenient scripting and control of all functions, which outputs control data through a parallel, serial, or USB port, said software controlling creation of designs in at least said two dimensions using said pixels; and a circuit board which processes incoming control data from the software and uses the data to actuate and de-actuate the solenoid valves with precise timing. 9. The device according to claim 1 , wherein the pilot light tubes are about six inches apart. | 0.885645 |
8,484,015 | 9 | 10 | 9. A method for use in a natural language (NL) system that generates answers to NL queries, the method comprising: generating, using one or more computing devices, a set of one or more potential alternative NL queries that are related to a first NL query; providing, using one or more computing devices, the set of one or more potential alternative NL queries to an NL query answering system implemented by one or more computing devices; receiving, from the NL query answering system, one or more respective answers to the one or more potential alternative NL queries in the set, wherein the one or more respective answers are based on data stored in a first database; generating, using one or more computing devices, one or more web pages corresponding to the one or more respective answers, wherein each web page is configured to display the respective answer; and storing in a second database the one or more web pages. | 9. A method for use in a natural language (NL) system that generates answers to NL queries, the method comprising: generating, using one or more computing devices, a set of one or more potential alternative NL queries that are related to a first NL query; providing, using one or more computing devices, the set of one or more potential alternative NL queries to an NL query answering system implemented by one or more computing devices; receiving, from the NL query answering system, one or more respective answers to the one or more potential alternative NL queries in the set, wherein the one or more respective answers are based on data stored in a first database; generating, using one or more computing devices, one or more web pages corresponding to the one or more respective answers, wherein each web page is configured to display the respective answer; and storing in a second database the one or more web pages. 10. The method of claim 9 , wherein generating, using one or more computing devices, a set of one or more potential alternative NL queries that are related to a first NL query comprises: receiving the first NL query; interpreting, using one or more computing devices, the first NL query to generate a disambiguated second query; and algorithmically varying, using one or more computing devices, the disambiguated second query to generate one or more third queries. | 0.819455 |
8,364,509 | 1 | 56 | 1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user. | 1. A method of measuring performance parameters and reporting on at least one aspect of respective performance parameters of a plurality of agents, the method comprising at least the following: measuring in an agent training system at least a plurality of data, including data representing agent performance parameters for each of the plurality, of agents, wherein the plurality of data representing agent performance parameters includes data related to at least one of either sections or teams to which an agent is assigned or associated, personal development meetings (PDMs) during which the agent receives constructive criticism or other remedial instruction related to improving job performance, wherein the plurality of data is related to improving the job performance of at least one of the plurality of agents on an individual agent-basis or a group-level agent-basis; receiving from the agent training system the plurality of data from a first input representing respective performance parameters pertaining to the plurality of agents on the individual agent-basis or the group-level agent-basis working at least one call center; organizing the at least plurality of data related to improving the job performance received from the first input in a data store in at least one of a plurality of user-specified parameters; storing the at least plurality of data related to improving the job performance received from the first input in the data store arranged in at least one of the plurality of user-specified parameters for subsequent query and retrieval; receiving at least one query of the data store by a user pertaining to the improving job performance of at least one of the agents on the individual agent-basis or the group-level agent-basis; processing an output determined by the at least first input of at least the plurality of the data related to the improving job performance in response to the query and processing the output results in the plurality of data related to remedial instruction related to improving a job performance arranged in one of the plurality of user-specified parameters, including at least one of a productivity parameter, a conversion parameter, a schedule adherence parameter, and a number of calls parameter by a given agent; and presenting at least one report as determined by the output of the query to the at least one user. 56. The method of claim 1 , wherein receiving at least one query includes receiving at least one query for data pertaining to a specific member of a specific group of agents. | 0.765499 |
7,693,904 | 1 | 7 | 1. A method of determining a relation between search queries, the method comprising: maintaining a database that associates a search session with at least one search query which has been received from a user terminal during said search session, wherein the database is updated at predetermined time intervals, said database being stored in a memory; determining a total number of search sessions for each user terminal during a first time interval, by referring to said database; determining a first number of search sessions where a first search query is received from said each user terminal during said first time interval, by referring to said database; determining a second number of search sessions where a second search query is received from said each user terminal during said first time interval, by referring to said database; determining a third number of search sessions where both said first search query and said second search query are received from said each user terminal during said first time interval, by referring to said database; calculating conditional probability from comparing said determined first number of search sessions where said first search query is received with said determined third number of search sessions where both said first search query and said second search query are received; calculating correlation by using said total number of search sessions, said first number of search sessions, said second number of search sessions, and said third number of search sessions; and determining a relation between said first search query and said second search query, based, at least in part, upon said calculated conditional probability and said calculated correlation, wherein said steps of calculating conditional probability and calculating correlation are performed by a processor. | 1. A method of determining a relation between search queries, the method comprising: maintaining a database that associates a search session with at least one search query which has been received from a user terminal during said search session, wherein the database is updated at predetermined time intervals, said database being stored in a memory; determining a total number of search sessions for each user terminal during a first time interval, by referring to said database; determining a first number of search sessions where a first search query is received from said each user terminal during said first time interval, by referring to said database; determining a second number of search sessions where a second search query is received from said each user terminal during said first time interval, by referring to said database; determining a third number of search sessions where both said first search query and said second search query are received from said each user terminal during said first time interval, by referring to said database; calculating conditional probability from comparing said determined first number of search sessions where said first search query is received with said determined third number of search sessions where both said first search query and said second search query are received; calculating correlation by using said total number of search sessions, said first number of search sessions, said second number of search sessions, and said third number of search sessions; and determining a relation between said first search query and said second search query, based, at least in part, upon said calculated conditional probability and said calculated correlation, wherein said steps of calculating conditional probability and calculating correlation are performed by a processor. 7. The method of claim 1 , wherein the search session is set when a search window is initially provided to the user terminal, and terminated when data is not transmitted from the user terminal during a predetermined time, and an additional search session is started when an additional search query is received from the user terminal after the search session is terminated. | 0.81889 |
5,444,840 | 5 | 6 | 5. A computer-implemented method of retrievably storing contents of a plurality of documents having images imprinted thereon comprising optically scanning the documents to form a digital representation of the images on the documents, machine selecting search words from each document to be used in locating the document from mass storage, converting the selected search words to code, storing the converted search words in a memory, storing the image representation of each document, establishing from images of the scanned documents a font table in image of alphanumeric characters in a plurality of different fonts each character in each font correlated with an equivalent character in code, searching for a document by the steps of manually selecting a search word, manually entering the selected search word in code, constructing by machine an image of the selected search word from the font table in at least one font, comparing the constructed search word with the image representations of scanned documents until a match in a stored document image is found, and displaying an image thereof of the matched document. | 5. A computer-implemented method of retrievably storing contents of a plurality of documents having images imprinted thereon comprising optically scanning the documents to form a digital representation of the images on the documents, machine selecting search words from each document to be used in locating the document from mass storage, converting the selected search words to code, storing the converted search words in a memory, storing the image representation of each document, establishing from images of the scanned documents a font table in image of alphanumeric characters in a plurality of different fonts each character in each font correlated with an equivalent character in code, searching for a document by the steps of manually selecting a search word, manually entering the selected search word in code, constructing by machine an image of the selected search word from the font table in at least one font, comparing the constructed search word with the image representations of scanned documents until a match in a stored document image is found, and displaying an image thereof of the matched document. 6. A method according to claim 5 wherein the digital representation of each document includes a plurality of pixel lines forming lines of characters in the image, and wherein the step of selecting search words includes evaluating the first pixel line in each character line to detect characters having the height characteristics of capital letters, evaluating each detected character to determine if it is a capital letter, and selecting each word identified as a capital letter, except those beginning sentences, for use as a search word. | 0.750463 |
7,684,068 | 1 | 2 | 1. An email server for performing automatic capture archiving of electronic documents in a network environment, at least one client computer in the network environment being coupled over a network to at least one document management workstation having at least one database disposed to receive electronic copies of documents transferred over the network, the at least one document management workstation being in communication with at least one of a copy, print, and facsimile operation, said email server being operatively disposed to: receive a copy of every email document transferred over the network from the at least one client computer, each email document being transferred over the network in response to a single user input command; cause electronic image data to be generated for each received copy of an email document, the electronic image data being generated in a format acceptable for storage in the at least one database for the at least one document management workstation; and cause the generated electronic image data to be stored in the at least one database to perform capture archiving of the email document, wherein the at least one database further comprises image data from capture archiving of electronic document images from the at least one of a copy, print, and facsimile operation, wherein the aforementioned steps are carried out transparent to the user and without further input from the user notwithstanding the single user input command, wherein the aforementioned steps are carried out at substantially a time that the email document is transferred over the network. | 1. An email server for performing automatic capture archiving of electronic documents in a network environment, at least one client computer in the network environment being coupled over a network to at least one document management workstation having at least one database disposed to receive electronic copies of documents transferred over the network, the at least one document management workstation being in communication with at least one of a copy, print, and facsimile operation, said email server being operatively disposed to: receive a copy of every email document transferred over the network from the at least one client computer, each email document being transferred over the network in response to a single user input command; cause electronic image data to be generated for each received copy of an email document, the electronic image data being generated in a format acceptable for storage in the at least one database for the at least one document management workstation; and cause the generated electronic image data to be stored in the at least one database to perform capture archiving of the email document, wherein the at least one database further comprises image data from capture archiving of electronic document images from the at least one of a copy, print, and facsimile operation, wherein the aforementioned steps are carried out transparent to the user and without further input from the user notwithstanding the single user input command, wherein the aforementioned steps are carried out at substantially a time that the email document is transferred over the network. 2. The email server of claim 1 , wherein the at least one of the copy, print, and facsimile operation comprises at least one of a copier operation, printer operation, and facsimile machine operation that archived image data for at least one of the copier operation, printer operation, and facsimile machine operation. | 0.501572 |
9,002,866 | 16 | 17 | 16. The method of claim 14 , wherein obtaining a plurality of candidate corrected spellings for the entity name comprises: generating a name query from the entity name and the two or more context terms; and searching context-entity name data for the candidate corrected spellings responsive to the name query. | 16. The method of claim 14 , wherein obtaining a plurality of candidate corrected spellings for the entity name comprises: generating a name query from the entity name and the two or more context terms; and searching context-entity name data for the candidate corrected spellings responsive to the name query. 17. The method of claim 16 , wherein the context-entity name data is an index that associates each of a plurality of context terms with a respective list of entity names. | 0.951149 |
8,244,706 | 1 | 8 | 1. A computer implemented method of retrieving information comprising: in a user interface, representing a real world item by a semantic entity; detecting user interaction with the user interface, including detecting the user graphically interacting with the semantic entity as displayed in the user interface; throughout the detected user graphical interaction with the semantic entity as displayed in the user interface, obtaining semantic data of the displayed semantic entity, said obtaining semantic data including disambiguating references to the displayed semantic entity; using the obtained and disambiguated semantic data and searching one or more knowledge bases for information about the displayed semantic entity, resulting in search results having information directly concerning the displayed semantic entity instead of the search results having material that merely mentions a name of the real world item being represented by the display semantic entity, said search results being more relevant than that of text-based, non-semantic searches; and automatically displaying to a user the information about the displayed semantic entity from the search results, wherein the searching and displaying are free of user request and support collaborative reasoning about the real world item by supporting collection and organization of information directly concerning the displayed semantic entity. | 1. A computer implemented method of retrieving information comprising: in a user interface, representing a real world item by a semantic entity; detecting user interaction with the user interface, including detecting the user graphically interacting with the semantic entity as displayed in the user interface; throughout the detected user graphical interaction with the semantic entity as displayed in the user interface, obtaining semantic data of the displayed semantic entity, said obtaining semantic data including disambiguating references to the displayed semantic entity; using the obtained and disambiguated semantic data and searching one or more knowledge bases for information about the displayed semantic entity, resulting in search results having information directly concerning the displayed semantic entity instead of the search results having material that merely mentions a name of the real world item being represented by the display semantic entity, said search results being more relevant than that of text-based, non-semantic searches; and automatically displaying to a user the information about the displayed semantic entity from the search results, wherein the searching and displaying are free of user request and support collaborative reasoning about the real world item by supporting collection and organization of information directly concerning the displayed semantic entity. 8. A method as claimed in claim 1 wherein the searching is of any combination of an internal datastore and external datastore. | 0.838046 |
7,747,682 | 11 | 13 | 11. A nametag embodied in a distributed computer system, the nametag comprising at least one logical item name field holding a logical item name, at least one corresponding volatile copy item name field, and at least two corresponding nonvolatile copy item name fields. | 11. A nametag embodied in a distributed computer system, the nametag comprising at least one logical item name field holding a logical item name, at least one corresponding volatile copy item name field, and at least two corresponding nonvolatile copy item name fields. 13. The nametag of claim 11 , further comprising a chronological value indicating when at least one value in at least one item name field becomes or became valid. | 0.575916 |
8,468,122 | 30 | 32 | 30. The system of claim 29 wherein the one or more computing devices are configured to generate at least one of the query candidates by translation of a natural language question entered at the user device, and wherein translation of the natural language question includes generation of at least one sub-string from a string of text corresponding to the natural language question, and selection of at least one of a plurality of query template components corresponding to the at least one sub-string. | 30. The system of claim 29 wherein the one or more computing devices are configured to generate at least one of the query candidates by translation of a natural language question entered at the user device, and wherein translation of the natural language question includes generation of at least one sub-string from a string of text corresponding to the natural language question, and selection of at least one of a plurality of query template components corresponding to the at least one sub-string. 32. The system of claim 30 wherein the one or more computing devices are further configured to translate the natural language question by generation of a query template including the plurality of query template components by designation of a plurality of predefined text sub-strings and a plurality of variables to which the predefined text sub-strings correspond, and by definition of a query generator with respect to the variables, the query generator being operable to generate the query from selected ones of the predefined text sub-strings substituted for the corresponding variables. | 0.792691 |
9,087,293 | 1 | 3 | 1. A method implemented in a computer system comprising one or more processors in operable communication with one or more non-transitory, tangible, computer-readable storage media, at least a first one of the non-transitory, tangible computer-readable storage media storing instructions executable by at least one processor, the method comprising: receiving, at the processor, a conceptual graph comprising one or more concept types, one or more relationship types, and one or more arcs; causing the processor to execute one or more instructions configured to: categorize each concept type of the one or more concept types according to the one or more relationship types and the one or more arcs, wherein the categorizing each concept type further comprises: determining that each concept type is directly connected to two or more relationship types by two or more arcs pointing in different directions; and categorizing the each concept type as a context linking concept; record in a second respective one of the non-transitory, tangible, storage media, the categorization of the each concept type of the one or more concept types; identify, based on a respective database of terms stored in a third respective one of the non-transitory, tangible storage media, one or more related terms of at least one particular concept type of the one or more concept types according to the categorization; and searching a plurality of documents in a fourth respective one of the non-transitory, tangible, storage media, for matches to the identified one or more related terms of the at least one particular concept type according to the categorization. | 1. A method implemented in a computer system comprising one or more processors in operable communication with one or more non-transitory, tangible, computer-readable storage media, at least a first one of the non-transitory, tangible computer-readable storage media storing instructions executable by at least one processor, the method comprising: receiving, at the processor, a conceptual graph comprising one or more concept types, one or more relationship types, and one or more arcs; causing the processor to execute one or more instructions configured to: categorize each concept type of the one or more concept types according to the one or more relationship types and the one or more arcs, wherein the categorizing each concept type further comprises: determining that each concept type is directly connected to two or more relationship types by two or more arcs pointing in different directions; and categorizing the each concept type as a context linking concept; record in a second respective one of the non-transitory, tangible, storage media, the categorization of the each concept type of the one or more concept types; identify, based on a respective database of terms stored in a third respective one of the non-transitory, tangible storage media, one or more related terms of at least one particular concept type of the one or more concept types according to the categorization; and searching a plurality of documents in a fourth respective one of the non-transitory, tangible, storage media, for matches to the identified one or more related terms of the at least one particular concept type according to the categorization. 3. The method of claim 1 , the categorizing each concept type further comprising: determining that each concept type fits a concept object pattern; and categorizing each concept type as a concept object. | 0.871843 |
8,560,827 | 4 | 5 | 4. The method of claim 1 wherein using the processor to receive state data from a system comprises using the processor to receive state data from a system in a replication environment. | 4. The method of claim 1 wherein using the processor to receive state data from a system comprises using the processor to receive state data from a system in a replication environment. 5. The method of claim 4 wherein using the processor to optimize the concrete model to solve for system configuration parameters of the system comprises using the processor to optimize the concrete model to solve for system configuration parameters of the system comprising at least one of preferred data protection appliances (DPAs), journal compression, snapshot consolidation policy, image access log size, bandwidth allocation and compression levels. | 0.674319 |
9,135,267 | 1 | 2 | 1. A method of establishing a bridge between two documents on a server, comprising: receiving, at the server, a first document represented by a hierarchical data structure model having a plurality of first nodes; generating, by a processor, a second document represented by a flat data structure model having a plurality of flat data structure elements, the second document being an online collaboratively editable document; and establishing, by the processor, the bridge between the first document and the second document, including: linking the plurality of first nodes to the plurality of flat data structure elements, such that at least a portion of contents of the plurality of first nodes is copied to the plurality of flat data structure elements; and maintaining the bridge, such that an edit to the first document, represented in at least one of the first nodes, is applied to at least one corresponding flat data structure element, thereby applying the edit to the second document. | 1. A method of establishing a bridge between two documents on a server, comprising: receiving, at the server, a first document represented by a hierarchical data structure model having a plurality of first nodes; generating, by a processor, a second document represented by a flat data structure model having a plurality of flat data structure elements, the second document being an online collaboratively editable document; and establishing, by the processor, the bridge between the first document and the second document, including: linking the plurality of first nodes to the plurality of flat data structure elements, such that at least a portion of contents of the plurality of first nodes is copied to the plurality of flat data structure elements; and maintaining the bridge, such that an edit to the first document, represented in at least one of the first nodes, is applied to at least one corresponding flat data structure element, thereby applying the edit to the second document. 2. The method of claim 1 , further comprising: detecting an edit to the first document; and applying the edit to the second document, based on the bridge linking the plurality of first nodes and the plurality of flat data structure elements. | 0.860532 |
8,166,001 | 3 | 5 | 3. The method of claim 1 further comprising: tracking an indication of members of the set of control statements that are not linked to a corresponding policy. | 3. The method of claim 1 further comprising: tracking an indication of members of the set of control statements that are not linked to a corresponding policy. 5. The method of claim 3 further comprising: for each of the members, displaying an indication of a corresponding operational guideline of the plurality of operational guidelines. | 0.951013 |
9,317,403 | 17 | 18 | 17. The method as claimed in claim 16 comprising the steps of: creating a command line in a computer script; the command line: comprising the label; and, being associated with the reference digital image. | 17. The method as claimed in claim 16 comprising the steps of: creating a command line in a computer script; the command line: comprising the label; and, being associated with the reference digital image. 18. The method as claimed in claim 17 wherein the command line comprises instructions to: search a further digital image for the group of pixels corresponding to the reference digital image; and, execute a computer application event associated with one or more pixels in the further digital image using the position data. | 0.852482 |
8,832,132 | 1 | 6 | 1. A computer-implemented method of providing a search result set relevant to a search query, the method comprising: hosting a social network comprising a plurality of communities, each community having a plurality of users; storing a user profile for each user including a first user and a second user, the user profile identifying the user's membership in at least one of the communities; receiving the search query directed to a content index that is independent of the social network from the first user who is a member of at least one of the communities; determining personalization information including a first search term and a second search term, the first search term being determined from the first user's user profile and data from the second user's user profile, the second user's user profile having a degree of separation from the first user's user profile in the social network, and the second search term being based at least in part on the first user's membership in the at least one of the communities and a level of personalization selected by the first user for personalizing the search query received from the first user, wherein the level of personalization indicates a total number of the communities from which the second search term is retrieved; combining the search query received from the first user and the first and second search terms to form a personalized search query; and searching the content index using the personalized search query to produce the search result set comprising documents relevant to the personalized search query. | 1. A computer-implemented method of providing a search result set relevant to a search query, the method comprising: hosting a social network comprising a plurality of communities, each community having a plurality of users; storing a user profile for each user including a first user and a second user, the user profile identifying the user's membership in at least one of the communities; receiving the search query directed to a content index that is independent of the social network from the first user who is a member of at least one of the communities; determining personalization information including a first search term and a second search term, the first search term being determined from the first user's user profile and data from the second user's user profile, the second user's user profile having a degree of separation from the first user's user profile in the social network, and the second search term being based at least in part on the first user's membership in the at least one of the communities and a level of personalization selected by the first user for personalizing the search query received from the first user, wherein the level of personalization indicates a total number of the communities from which the second search term is retrieved; combining the search query received from the first user and the first and second search terms to form a personalized search query; and searching the content index using the personalized search query to produce the search result set comprising documents relevant to the personalized search query. 6. The method of claim 1 , wherein determining personalization information including the first search term comprises identifying information explicitly provided by the first user for personalizing the search query. | 0.597744 |
8,533,194 | 2 | 7 | 2. An electronic document analysis method using a processor for analyzing N electronic documents, the method comprising: performing at least a portion of a first computerized text-classifier based document categorization process on the N electronic documents, using a first computerized text-classifier, thereby to generate at least one output; and using said at least one output to perform at least a second computerized text-classifier based document categorization process on at least M additional electronic documents, wherein said using comprises applying the first computerized text-classifier based document categorization process to at least the M additional electronic documents, only if the processor has determined that the first computerized text-classifier, when applied to at least the M additional electronic documents, satisfies a predetermined categorization quality criterion, and otherwise, applying a document categorization process which is not based on the first computerized text-classifier based document categorization process, to at least the M additional electronic documents, wherein a single set, X, of control documents is used: both to make a first determination of whether or not the first computerized text-classifier, when applied to at least the M additional electronic documents, satisfies a predetermined categorization quality criterion, and also to make a second determination of whether or not said document categorization process which is applied to said M additional electronic documents and which is not based on the first computerized text-classifier based document, satisfies a predetermined categorization quality criterion, thereby to utilize a single categorization process applied to said single set X rather than conducting separate, first and second, categorization processes on separate, first and second, control sets to be used when making said first and second determinations respectively. | 2. An electronic document analysis method using a processor for analyzing N electronic documents, the method comprising: performing at least a portion of a first computerized text-classifier based document categorization process on the N electronic documents, using a first computerized text-classifier, thereby to generate at least one output; and using said at least one output to perform at least a second computerized text-classifier based document categorization process on at least M additional electronic documents, wherein said using comprises applying the first computerized text-classifier based document categorization process to at least the M additional electronic documents, only if the processor has determined that the first computerized text-classifier, when applied to at least the M additional electronic documents, satisfies a predetermined categorization quality criterion, and otherwise, applying a document categorization process which is not based on the first computerized text-classifier based document categorization process, to at least the M additional electronic documents, wherein a single set, X, of control documents is used: both to make a first determination of whether or not the first computerized text-classifier, when applied to at least the M additional electronic documents, satisfies a predetermined categorization quality criterion, and also to make a second determination of whether or not said document categorization process which is applied to said M additional electronic documents and which is not based on the first computerized text-classifier based document, satisfies a predetermined categorization quality criterion, thereby to utilize a single categorization process applied to said single set X rather than conducting separate, first and second, categorization processes on separate, first and second, control sets to be used when making said first and second determinations respectively. 7. A method according to claim 2 further comprising: using at least one output of the second text-classifier based electronic document categorization process to perform legal e-discovery. | 0.864099 |
7,676,746 | 10 | 19 | 10. A method for enabling in-context authoring of substitute content for one or more non-textual objects, comprising: accessing an electronic document including content data that includes sentences and at least one non-textual object contextually placed in a first position within the sentences; and presenting substitute content positioned in the first position within the sentences, wherein the substitute content corresponds to the at least one non-textual object; presenting at least a portion of the sentences positioned adjacent to the first position to enable a user to contextually review the substitute content with respect to the sentences; editing the substitute content positioned in the first position within the sentences and in response to editing commands; and storing the substitute content in the electronic document. | 10. A method for enabling in-context authoring of substitute content for one or more non-textual objects, comprising: accessing an electronic document including content data that includes sentences and at least one non-textual object contextually placed in a first position within the sentences; and presenting substitute content positioned in the first position within the sentences, wherein the substitute content corresponds to the at least one non-textual object; presenting at least a portion of the sentences positioned adjacent to the first position to enable a user to contextually review the substitute content with respect to the sentences; editing the substitute content positioned in the first position within the sentences and in response to editing commands; and storing the substitute content in the electronic document. 19. A computer-readable storage medium holding code for preforming the method according to claim 10 . | 0.904717 |
7,917,847 | 51 | 56 | 51. The terminal device according to claim 49 , wherein the controller further performs a function of judging whether or not predetermined user operation is performed, wherein the predetermined user operation includes operation for canceling the switching of the onscreen representation, and wherein the switching of the onscreen representation is cancelled if it is judged by the judging that the predetermined user operation is performed, and the switching of the onscreen representation is performed if it is judged by the judging that the predetermined user operation is not performed. | 51. The terminal device according to claim 49 , wherein the controller further performs a function of judging whether or not predetermined user operation is performed, wherein the predetermined user operation includes operation for canceling the switching of the onscreen representation, and wherein the switching of the onscreen representation is cancelled if it is judged by the judging that the predetermined user operation is performed, and the switching of the onscreen representation is performed if it is judged by the judging that the predetermined user operation is not performed. 56. The terminal device according to claim 51 , wherein the onscreen representation in the first browsing mode is made during a first stage from a start of the obtaining operation of the page to a time of completion of acquisition of text data of the page, and wherein the operation for canceling the switching of the onscreen representation is allowed in a certain time period from completion of acquisition of the definition information. | 0.791151 |
9,865,251 | 8 | 13 | 8. A multi-lingual speech synthesizer for processing a multi-lingual text message in a mixture of a first language and a second language into a multi-lingual voice message, the synthesizer comprising: a storage device configured to store a first language model database having a plurality of first language phoneme labels and first language cognate connection tone information, and a second language model database having a plurality of second language phoneme labels and second language cognate connection tone information; a broadcasting device configured to broadcast the multi-lingual voice message; a processor, connected to the storage device and the broadcasting device, configured to: separate the multi-lingual text message into at least one first language section and at least one second language section; convert the at least one first language section into at least one first language phoneme label and converting the at least one second language section into at least one second language phoneme label; look up the first language model database using the at least one first language phoneme label thereby obtaining at least one first language phoneme label sequence, and look up the second language database model using the at least one second language phoneme label thereby obtaining at least one second language phoneme label sequence; assemble the at least one first language phoneme label sequence and at least one second language phoneme label sequence into a multi-lingual phoneme label sequence according to an order of words in the multi-lingual text message; divide the multi-lingual phoneme label sequence into a plurality of first pronunciation units, each of the plurality of first pronunciation units is in a single language and includes consecutive phoneme labels of a corresponding one of the at least one first language phoneme label sequence and the at least one second language phoneme label sequence; for each of the first pronunciation units, determine whether a number of available candidates for a corresponding one of the first pronunciation units in a corresponding one of the first language model database and the second language model database is equal to or more than a predetermined number corresponding to the one of the first pronunciation units; when the number of available candidates for each of the first pronunciation units in the corresponding one of the first language model database and the second language model database is equal to or more than the corresponding predetermined number, calculate a join cost of each candidate path, wherein each candidate path passes through one of the available candidates of each of the first pronunciation units; determine a connecting path between every two immediately adjacent first pronunciation units based on the join cost of each candidate path; produce inter-lingual connection tone information at a boundary between every two immediately adjacent phoneme label sequences; combine the multi-lingual phoneme label sequence, the first language cognate connection tone information at a boundary between every two immediately adjacent phoneme label of the at least one first language phoneme label sequence, the second language cognate connection tone information at a boundary between every two immediately adjacent phoneme labels of the at least one second language phoneme label sequence, and inter-lingual connection tone information to obtain the multi-lingual voice message, and output the multi-lingual voice message to the broadcasting device. | 8. A multi-lingual speech synthesizer for processing a multi-lingual text message in a mixture of a first language and a second language into a multi-lingual voice message, the synthesizer comprising: a storage device configured to store a first language model database having a plurality of first language phoneme labels and first language cognate connection tone information, and a second language model database having a plurality of second language phoneme labels and second language cognate connection tone information; a broadcasting device configured to broadcast the multi-lingual voice message; a processor, connected to the storage device and the broadcasting device, configured to: separate the multi-lingual text message into at least one first language section and at least one second language section; convert the at least one first language section into at least one first language phoneme label and converting the at least one second language section into at least one second language phoneme label; look up the first language model database using the at least one first language phoneme label thereby obtaining at least one first language phoneme label sequence, and look up the second language database model using the at least one second language phoneme label thereby obtaining at least one second language phoneme label sequence; assemble the at least one first language phoneme label sequence and at least one second language phoneme label sequence into a multi-lingual phoneme label sequence according to an order of words in the multi-lingual text message; divide the multi-lingual phoneme label sequence into a plurality of first pronunciation units, each of the plurality of first pronunciation units is in a single language and includes consecutive phoneme labels of a corresponding one of the at least one first language phoneme label sequence and the at least one second language phoneme label sequence; for each of the first pronunciation units, determine whether a number of available candidates for a corresponding one of the first pronunciation units in a corresponding one of the first language model database and the second language model database is equal to or more than a predetermined number corresponding to the one of the first pronunciation units; when the number of available candidates for each of the first pronunciation units in the corresponding one of the first language model database and the second language model database is equal to or more than the corresponding predetermined number, calculate a join cost of each candidate path, wherein each candidate path passes through one of the available candidates of each of the first pronunciation units; determine a connecting path between every two immediately adjacent first pronunciation units based on the join cost of each candidate path; produce inter-lingual connection tone information at a boundary between every two immediately adjacent phoneme label sequences; combine the multi-lingual phoneme label sequence, the first language cognate connection tone information at a boundary between every two immediately adjacent phoneme label of the at least one first language phoneme label sequence, the second language cognate connection tone information at a boundary between every two immediately adjacent phoneme labels of the at least one second language phoneme label sequence, and inter-lingual connection tone information to obtain the multi-lingual voice message, and output the multi-lingual voice message to the broadcasting device. 13. The multi-lingual speech synthesizer of claim 8 , wherein the join cost of each candidate path is a weighted sum of a target cost of each candidate audio frequency data in each of the first pronunciation units, an acoustic spectrum cost of each connection between the candidate audio frequency data in every two immediately adjacent first pronunciation units, a tone cost of each connection between the candidate audio frequency data in every two immediately adjacent first pronunciation units, a pacemaking cost of each connection between the candidate audio frequency data in every two immediately adjacent first pronunciation units, and an intensity cost of each connection between the candidate audio frequency data in every two immediately adjacent first pronunciation units. | 0.738667 |
5,444,841 | 4 | 5 | 4. The combination of claim 3 further including means responsive to replication of said data field for storing positions of said one or more display elements. | 4. The combination of claim 3 further including means responsive to replication of said data field for storing positions of said one or more display elements. 5. The combination of claim 4 further including means responsive to the storage of said positions for displaying said display elements at corresponding positions in said document representation. | 0.932779 |
8,280,823 | 283 | 288 | 283. The graphical user interface of claim 274 , wherein the term of experience is rounded down to a unit of time. | 283. The graphical user interface of claim 274 , wherein the term of experience is rounded down to a unit of time. 288. The graphical user interface of claim 283 , wherein the required term of experience, or an alternative required term of experience, is rounded up to a unit of time. | 0.961363 |
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