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8,238,719 | 1 | 5 | 1. A method of processing a sports video, comprising the steps of: analyzing the sports video to detect at least one semantic event, each of which is associated with a segment length; assigning a segment length to the at least one semantic event according to importance of a corresponding event; extracting a scene segment associated with the at least one semantic event out of the sports video according to the segment length; and generating a summarized video according to the detected at least one semantic event; wherein the segment length of each semantic event varies according to importance and weight of each semantic event and varies according to a context analysis result showing the relative importance of each semantic event comparing to its prior and subsequent events throughout the sports video; and the step of extracting the scene segment associated with the at least one semantic event out of the sports video according to the segment length comprises: generating the semantic event according to at least one of base bag, score, and out in a score board region. | 1. A method of processing a sports video, comprising the steps of: analyzing the sports video to detect at least one semantic event, each of which is associated with a segment length; assigning a segment length to the at least one semantic event according to importance of a corresponding event; extracting a scene segment associated with the at least one semantic event out of the sports video according to the segment length; and generating a summarized video according to the detected at least one semantic event; wherein the segment length of each semantic event varies according to importance and weight of each semantic event and varies according to a context analysis result showing the relative importance of each semantic event comparing to its prior and subsequent events throughout the sports video; and the step of extracting the scene segment associated with the at least one semantic event out of the sports video according to the segment length comprises: generating the semantic event according to at least one of base bag, score, and out in a score board region. 5. The method of claim 1 , wherein he sports video is a baseball sports video. | 0.926692 |
8,621,349 | 16 | 20 | 16. A non-transitory computer-readable medium having instructions stored thereon that, if executed by a mobile device, cause the mobile device to perform functions comprising: performing a optical capture from a book; identifying the book from the optical capture, by at least: identifying a text fragment within the optical capture, and locating a position in the book containing the identified text fragment; retrieving a media sequence associated with the book; and presenting the retrieved media sequence by at least presenting the retrieved media sequence at a time in the time-indexed media sequence that corresponds to the located position in the book. | 16. A non-transitory computer-readable medium having instructions stored thereon that, if executed by a mobile device, cause the mobile device to perform functions comprising: performing a optical capture from a book; identifying the book from the optical capture, by at least: identifying a text fragment within the optical capture, and locating a position in the book containing the identified text fragment; retrieving a media sequence associated with the book; and presenting the retrieved media sequence by at least presenting the retrieved media sequence at a time in the time-indexed media sequence that corresponds to the located position in the book. 20. The non-transitory compute-readable medium of claim 16 , wherein the mobile device comprises a cell phone. | 0.778226 |
7,499,931 | 1 | 6 | 1. A computer readable medium including computer instructions for regulating communication of information in a data structure between components of a computer program, the medium comprising executable instructions to perform the steps: providing at least one XPath query to an XML processor where the XPath query comprises forward, backward, following-sibling, and preceding-sibling axes; providing an XML document to the XML processor; and the following steps performed by the XML processor: deriving a set of XPath expressions from the XML document, wherein the XPath expressions are represented as a rooted XPath expression tree with labeled vertices and edges, and wherein the XPath expression tree comprises at least one axis selected from a group consisting of: backward, ancestor, parent, following, preceding, following-sibling, and preceding-sibling axes; constructing a projection of the XML document for evaluation of the XPath query, the projection based on the XPath expression tree, wherein the constructing step comprises: 1) normalizing the X-Path expression tree into a canonical form, wherein the normalizing step comprises: a) rewriting instances of following, preceding, following-sibling and preceding-sibling axes in the XPath expression tree into order-blind axes, such as parent and ancestor, by introducing new vertices such that there are no more instances of following and preceding in the rewritten XPath expression tree; and b) merging vertices of the rewritten XPath expression tree to remove redundancies; 2) traversing the XML document in a depth-first manner to build a tree representation of the XML document, the traversing step comprising: a) generating start events when the traversal first visits an element; b) generating end events once the traversal of a subtree rooted at that element is finished; c) concurrently with generating the events, constructing nodes for all elements that may participate in an embedding; and d) adding all ancestor nodes of the elements that may participate in an embedding; evaluating the at least one XPath query against the tree representation in a bottom-up manner to produce a result such that the result of the evaluation of the XPath query on the projection of the XML document is the same as a result of evaluation of the XPath query on the XML document and comprises all nodes that are solutions of the XPath query, and their backward axes; and serializing the result. | 1. A computer readable medium including computer instructions for regulating communication of information in a data structure between components of a computer program, the medium comprising executable instructions to perform the steps: providing at least one XPath query to an XML processor where the XPath query comprises forward, backward, following-sibling, and preceding-sibling axes; providing an XML document to the XML processor; and the following steps performed by the XML processor: deriving a set of XPath expressions from the XML document, wherein the XPath expressions are represented as a rooted XPath expression tree with labeled vertices and edges, and wherein the XPath expression tree comprises at least one axis selected from a group consisting of: backward, ancestor, parent, following, preceding, following-sibling, and preceding-sibling axes; constructing a projection of the XML document for evaluation of the XPath query, the projection based on the XPath expression tree, wherein the constructing step comprises: 1) normalizing the X-Path expression tree into a canonical form, wherein the normalizing step comprises: a) rewriting instances of following, preceding, following-sibling and preceding-sibling axes in the XPath expression tree into order-blind axes, such as parent and ancestor, by introducing new vertices such that there are no more instances of following and preceding in the rewritten XPath expression tree; and b) merging vertices of the rewritten XPath expression tree to remove redundancies; 2) traversing the XML document in a depth-first manner to build a tree representation of the XML document, the traversing step comprising: a) generating start events when the traversal first visits an element; b) generating end events once the traversal of a subtree rooted at that element is finished; c) concurrently with generating the events, constructing nodes for all elements that may participate in an embedding; and d) adding all ancestor nodes of the elements that may participate in an embedding; evaluating the at least one XPath query against the tree representation in a bottom-up manner to produce a result such that the result of the evaluation of the XPath query on the projection of the XML document is the same as a result of evaluation of the XPath query on the XML document and comprises all nodes that are solutions of the XPath query, and their backward axes; and serializing the result. 6. The computer readable medium of claim 1 wherein the backward axes further comprise at least an ancestor axis. | 0.656442 |
8,077,812 | 1 | 8 | 1. An apparatus for detecting a data pattern from a plurality of received signals, the apparatus comprising: a mapper providing a sequence of scan values derived from a sequence of count values, each scan value selecting one of a set of candidates in a varying pattern, wherein the mapper generates the sequence of scan values so as to select each of the set of candidates in a waveform-shaped periodic scan pattern; a difference term generator providing, for each of the sequence of count values, a difference term between a current metric value and a previous metric value based on a set of coefficients for a received symbol; an accumulator combining, for each of a sequence of count values, the difference term with one or more previous difference terms to provide one of a set of metric values; and a comparator generating, based on the set of metric values corresponding to the sequence of scan values, soft-output values corresponding to the data pattern. | 1. An apparatus for detecting a data pattern from a plurality of received signals, the apparatus comprising: a mapper providing a sequence of scan values derived from a sequence of count values, each scan value selecting one of a set of candidates in a varying pattern, wherein the mapper generates the sequence of scan values so as to select each of the set of candidates in a waveform-shaped periodic scan pattern; a difference term generator providing, for each of the sequence of count values, a difference term between a current metric value and a previous metric value based on a set of coefficients for a received symbol; an accumulator combining, for each of a sequence of count values, the difference term with one or more previous difference terms to provide one of a set of metric values; and a comparator generating, based on the set of metric values corresponding to the sequence of scan values, soft-output values corresponding to the data pattern. 8. The apparatus as recited in claim 1 , wherein the comparator generates each soft-output value based on the minimum of the corresponding error metric for the received symbol over the set of candidates. | 0.669381 |
8,817,020 | 1 | 3 | 1. An image processing apparatus comprising: a computer processor comprising: a depth estimation unit which estimates depth of an input three dimensional (3D) image; a text area detection unit which detects a text area included in the 3D image; a mask generation unit which generates a text mask corresponding to the detected text area; and a depth correction unit which corrects a depth of the text area to be a first depth value based on the estimated depth of the input 3D image and the generated text mask. | 1. An image processing apparatus comprising: a computer processor comprising: a depth estimation unit which estimates depth of an input three dimensional (3D) image; a text area detection unit which detects a text area included in the 3D image; a mask generation unit which generates a text mask corresponding to the detected text area; and a depth correction unit which corrects a depth of the text area to be a first depth value based on the estimated depth of the input 3D image and the generated text mask. 3. The image processing apparatus as claimed in claim 1 , wherein the depth correction unit performs depth temporal smoothing for the text area of which the depth has been corrected. | 0.681818 |
8,812,946 | 1 | 2 | 1. A computerized method for generating an online collaborative editable document to be rendered by a web browser, comprising: receiving, at a server, a raw online collaborative editable document, having one or more data objects including one or more graphical elements and one or more textual elements, wherein the raw online collaborative editable document is configured to be rendered in a graphical format in a web browser and the raw document includes one or more presentation slides, one or more spreadsheets, or one or more word-processing document pages; identifying, at the server, the one or more graphical elements from the raw document, and generating a graphical data file including the one or more identified graphical elements; identifying, at the server, the one or more textual elements from the raw document, and generating a textual data file including the one or more identified textual elements, wherein the textual data file includes Hypertext Markup Language (HTML) data and Cascading Style Sheets (CSS) data, wherein generating the textual data file including the one or more textual elements includes identifying the one or more textual elements in the document and generating the textual data file having HTML data and CSS data representative of content and appearance of only the one or more identified textual elements; identifying, at the server, alignment of the one or more graphical elements and alignment of the one or more textual elements; adding, at the server, HTML and CSS data to the textual data file to include the graphical data file, thereby generating a composite document, wherein the CSS data aligns graphical elements with textual elements matching the alignment of the one or more graphical elements and the one or more textual elements in the raw document; and wherein, when rendered by the web browser, the textual data file overlays the graphical data file such that alignment, content and appearance of one or more graphical elements and one or more textual elements of the composite document are the same as the alignment, content and appearance of the one or more graphical elements and the one or more textual elements of the raw document. | 1. A computerized method for generating an online collaborative editable document to be rendered by a web browser, comprising: receiving, at a server, a raw online collaborative editable document, having one or more data objects including one or more graphical elements and one or more textual elements, wherein the raw online collaborative editable document is configured to be rendered in a graphical format in a web browser and the raw document includes one or more presentation slides, one or more spreadsheets, or one or more word-processing document pages; identifying, at the server, the one or more graphical elements from the raw document, and generating a graphical data file including the one or more identified graphical elements; identifying, at the server, the one or more textual elements from the raw document, and generating a textual data file including the one or more identified textual elements, wherein the textual data file includes Hypertext Markup Language (HTML) data and Cascading Style Sheets (CSS) data, wherein generating the textual data file including the one or more textual elements includes identifying the one or more textual elements in the document and generating the textual data file having HTML data and CSS data representative of content and appearance of only the one or more identified textual elements; identifying, at the server, alignment of the one or more graphical elements and alignment of the one or more textual elements; adding, at the server, HTML and CSS data to the textual data file to include the graphical data file, thereby generating a composite document, wherein the CSS data aligns graphical elements with textual elements matching the alignment of the one or more graphical elements and the one or more textual elements in the raw document; and wherein, when rendered by the web browser, the textual data file overlays the graphical data file such that alignment, content and appearance of one or more graphical elements and one or more textual elements of the composite document are the same as the alignment, content and appearance of the one or more graphical elements and the one or more textual elements of the raw document. 2. The computerized method of claim 1 , further comprising sending the raw document from at least one of a stored remote database and the client computing device. | 0.706522 |
9,870,423 | 10 | 11 | 10. A system, comprising: one or more non-transitory computer readable media storing instructions; one or more processors operable to execute the instructions, wherein the instructions include instructions to: identify a particular entity, the particular entity being a particular person, place, or thing; identify a plurality of search queries that are each associated with the particular entity; determine a query score for each of the search queries, wherein the query score for a search query of the search queries is based on search result document quality for search result documents, for the search query, that are associated with the particular entity, wherein the search result document quality is based on a document centric signal of the search result documents that are associated with the particular entity; assign a particular search query of the search queries to the particular entity based on the determined query scores; receive input, the input being provided via a user interface input device of a client computing device; determine that the particular entity is associated with the input; provide, for presentation via a user interface output device of the client computing device, content that includes a name of the particular entity and one or more additional properties of the particular entity, wherein providing the content is in response to the input and is in response to determining that the particular entity is associated with the input; and submit, in response to selection of the content at the client computing device, the particular search query to a search engine based on the particular search query being assigned to the particular entity. | 10. A system, comprising: one or more non-transitory computer readable media storing instructions; one or more processors operable to execute the instructions, wherein the instructions include instructions to: identify a particular entity, the particular entity being a particular person, place, or thing; identify a plurality of search queries that are each associated with the particular entity; determine a query score for each of the search queries, wherein the query score for a search query of the search queries is based on search result document quality for search result documents, for the search query, that are associated with the particular entity, wherein the search result document quality is based on a document centric signal of the search result documents that are associated with the particular entity; assign a particular search query of the search queries to the particular entity based on the determined query scores; receive input, the input being provided via a user interface input device of a client computing device; determine that the particular entity is associated with the input; provide, for presentation via a user interface output device of the client computing device, content that includes a name of the particular entity and one or more additional properties of the particular entity, wherein providing the content is in response to the input and is in response to determining that the particular entity is associated with the input; and submit, in response to selection of the content at the client computing device, the particular search query to a search engine based on the particular search query being assigned to the particular entity. 11. The system of claim 10 , wherein the input is a partial search query and the content is a query suggestion for the partial search query. | 0.82716 |
9,917,904 | 1 | 6 | 1. A computer-implemented method comprising: receiving, at a computing device and from user interaction with service that is capable of providing search results in response to a search query, an input from a first user that comprises a reserved term; in response to receiving the input, identifying the reserved term as being associated communicating with one or more other users; generating an action that involves communicating between users to be performed by an application that is separate from the service, the generating based on the reserved term and on the input, including identifying at least one of a telephone number or a person from the input; and causing the computing device to initiate a communication session between the first user and the identified at least one of the telephone number or the person. | 1. A computer-implemented method comprising: receiving, at a computing device and from user interaction with service that is capable of providing search results in response to a search query, an input from a first user that comprises a reserved term; in response to receiving the input, identifying the reserved term as being associated communicating with one or more other users; generating an action that involves communicating between users to be performed by an application that is separate from the service, the generating based on the reserved term and on the input, including identifying at least one of a telephone number or a person from the input; and causing the computing device to initiate a communication session between the first user and the identified at least one of the telephone number or the person. 6. The method of claim 1 , wherein the communication session comprises a telephone call. | 0.881081 |
8,429,528 | 1 | 5 | 1. A label procurement and management system comprising: an internet based label database with network accessibility to a plurality of users from said users' computers, wherein said label database is configured for receiving, storing, and sending label data, with said label database configured for being populated with pre-existing graphic label files and wherein system software can be updated via the internet; an administrative function configured for defining authorized personnel and their privileges, for authorizing and controlling access to view and edit label data and system activity via password protection with at least one authorization group for individual users within the system; a user information page presented to a user upon login, with lists of pending user tasks assigned to a specific user, with authority to perform tasks as specified by the administrative function, the pending user tasks comprising at least one of edit requests pending, proofs pending, orders pending, and further comprising links to a work flow screen for each listed task; a label setup workbench configured to allow at least one user to upload a previously created label image as a graphic file and a label data file for editing in said label procurement and management system, wherein said label setup workbench is configured to allow at least one user to define at least one editable field or label data corresponding to the graphic file; a label search function configured to allow a user to select a label by searching said label database for archived label graphic files and label data files and to retrieve said archived label graphic files and label data files for which said user is authorized to search; an edit studio configured to create a copy of said selected label in said label search function, and to present a true and accurate visual representation of the selected label for inspection and precision text editing, wherein said edit studio is configured to allow said user to perform precision text edits to the selected label, wherein said edit studio is configured to display said precision text edits as the changes are made as a label preview in a graphic file format with the edits visibly marked, and wherein said edit studio is further configured to present a true and accurate graphic image of said label during editing with the edited label copy not overwriting the original selected label without multiple levels of approval; a proof caddy configured to display changes to a selected and edited label copy for review and approval or rejection by authorized personnel, wherein the visible marking applied to said edits is changed to a different marking to indicate approval of said edits; a schedule wizard for displaying a preview of a last run version of a label, setting order quantities, setting repeat orders, entering shipping information, and entering a purchase order number; and an order cart configured for providing label data downloading capability to a user and configured to allow a user to download at least one of a graphic file or a data file as the end product of the system; wherein said label procurement and management system is configured to create a label copy and provide a preview and approval step when transforming at least one existing graphic file depicting a consumer product label into a modified label design incorporating said changes. | 1. A label procurement and management system comprising: an internet based label database with network accessibility to a plurality of users from said users' computers, wherein said label database is configured for receiving, storing, and sending label data, with said label database configured for being populated with pre-existing graphic label files and wherein system software can be updated via the internet; an administrative function configured for defining authorized personnel and their privileges, for authorizing and controlling access to view and edit label data and system activity via password protection with at least one authorization group for individual users within the system; a user information page presented to a user upon login, with lists of pending user tasks assigned to a specific user, with authority to perform tasks as specified by the administrative function, the pending user tasks comprising at least one of edit requests pending, proofs pending, orders pending, and further comprising links to a work flow screen for each listed task; a label setup workbench configured to allow at least one user to upload a previously created label image as a graphic file and a label data file for editing in said label procurement and management system, wherein said label setup workbench is configured to allow at least one user to define at least one editable field or label data corresponding to the graphic file; a label search function configured to allow a user to select a label by searching said label database for archived label graphic files and label data files and to retrieve said archived label graphic files and label data files for which said user is authorized to search; an edit studio configured to create a copy of said selected label in said label search function, and to present a true and accurate visual representation of the selected label for inspection and precision text editing, wherein said edit studio is configured to allow said user to perform precision text edits to the selected label, wherein said edit studio is configured to display said precision text edits as the changes are made as a label preview in a graphic file format with the edits visibly marked, and wherein said edit studio is further configured to present a true and accurate graphic image of said label during editing with the edited label copy not overwriting the original selected label without multiple levels of approval; a proof caddy configured to display changes to a selected and edited label copy for review and approval or rejection by authorized personnel, wherein the visible marking applied to said edits is changed to a different marking to indicate approval of said edits; a schedule wizard for displaying a preview of a last run version of a label, setting order quantities, setting repeat orders, entering shipping information, and entering a purchase order number; and an order cart configured for providing label data downloading capability to a user and configured to allow a user to download at least one of a graphic file or a data file as the end product of the system; wherein said label procurement and management system is configured to create a label copy and provide a preview and approval step when transforming at least one existing graphic file depicting a consumer product label into a modified label design incorporating said changes. 5. The system of claim 1 , wherein said label setup workbench is configured for at least one user to define at least one editable zone of said label. | 0.706693 |
8,412,628 | 1 | 2 | 1. A method for receiving and processing a claim file and authoring and electronically filing a legal document for a legal action in a court, comprising the steps of: (A) electronically receiving the claim file in electronic form wherein the claim file includes a plurality of data fields in a native format; (B) mapping, using an electronic processor, one or more of the data fields from the native format to a desired format different from the native format to form a modified claim file; (C) selecting a court, using the processor, at least in part on data included in the modified claim file and predetermined court selection criteria; (D) generating, using the processor, a legal document in electronic form configured for electronic filing in the selected court and which is compliant with requirements of the selected court, using data in the modified claim file and predetermined filing requirements data associated with the selected court; and (E) electronically filing the generated legal document in the selected court. | 1. A method for receiving and processing a claim file and authoring and electronically filing a legal document for a legal action in a court, comprising the steps of: (A) electronically receiving the claim file in electronic form wherein the claim file includes a plurality of data fields in a native format; (B) mapping, using an electronic processor, one or more of the data fields from the native format to a desired format different from the native format to form a modified claim file; (C) selecting a court, using the processor, at least in part on data included in the modified claim file and predetermined court selection criteria; (D) generating, using the processor, a legal document in electronic form configured for electronic filing in the selected court and which is compliant with requirements of the selected court, using data in the modified claim file and predetermined filing requirements data associated with the selected court; and (E) electronically filing the generated legal document in the selected court. 2. The method of claim 1 wherein said step of receiving a claim file includes the sub-steps of: presenting a user interface configured to solicit claim data from a user; capturing the claim data through the user interface; and storing the claim data in the claim file. | 0.899701 |
7,765,225 | 8 | 9 | 8. The method as claimed in claim 1 further including the step of inputting a topic or class term into the search window together with a search term to identify documents including the search term and having document identifier labels related to the topic or class. | 8. The method as claimed in claim 1 further including the step of inputting a topic or class term into the search window together with a search term to identify documents including the search term and having document identifier labels related to the topic or class. 9. The method as claimed in claim 8 including the step of appending a symbol to the topic or class term to identify the topic of class term as a document identifier label search term. | 0.962438 |
8,620,022 | 9 | 10 | 9. A method for controlling an event structure system, the method comprising: recognizing multiple-person interaction primitives from an image, which is displayed on a display screen; composing an event by inference based on temporal relations using the multiple-person interaction primitive; and determining a final event by either eliminating an unnecessary event from the composed event, or adding a new event in the composed event, wherein the determining of the final event comprises: eliminating an unnecessary event by Multi-Thread Parsing (MTP); computing a start point distance and an end point distance between two events to thereby infer temporal relations; re-generating an event disregarded due to errors; and adding the re-generated event in the composed event. | 9. A method for controlling an event structure system, the method comprising: recognizing multiple-person interaction primitives from an image, which is displayed on a display screen; composing an event by inference based on temporal relations using the multiple-person interaction primitive; and determining a final event by either eliminating an unnecessary event from the composed event, or adding a new event in the composed event, wherein the determining of the final event comprises: eliminating an unnecessary event by Multi-Thread Parsing (MTP); computing a start point distance and an end point distance between two events to thereby infer temporal relations; re-generating an event disregarded due to errors; and adding the re-generated event in the composed event. 10. The method of claim 9 , wherein the eliminating of the unnecessary event further comprises determining whether the recognized two events are combined. | 0.891396 |
8,762,312 | 1 | 8 | 1. A computer implemented method for using sentiment-based analysis in content access, the method comprising the steps of: receiving a filtering policy by a computer, the received filtering policy specifying to filter a protected party's access to content based on fact-based categorization of content and subjective factors concerning content, wherein granularity of said filtering policy is variable by use of one or more of a plurality of combinations of fact-based categorization and subjective factors, wherein the protected party is being administered by a third party; detecting, by a computer, an attempt by the protected party to access specific content, the specific content being remotely located; categorizing, by a computer, the specific content based on occurrence of predefined words responsive to the access attempt; performing, by a computer, a sentiment-based analysis of the specific content responsive to the access attempt; responsive to results of the categorization in light of the sentiment-based analysis of the specific content, determining, by a computer, whether the filtering policy permits the protected party to access the specific content; responsive to results of the determining step, managing, by a computer, the attempted access of the specific content by the protected party. | 1. A computer implemented method for using sentiment-based analysis in content access, the method comprising the steps of: receiving a filtering policy by a computer, the received filtering policy specifying to filter a protected party's access to content based on fact-based categorization of content and subjective factors concerning content, wherein granularity of said filtering policy is variable by use of one or more of a plurality of combinations of fact-based categorization and subjective factors, wherein the protected party is being administered by a third party; detecting, by a computer, an attempt by the protected party to access specific content, the specific content being remotely located; categorizing, by a computer, the specific content based on occurrence of predefined words responsive to the access attempt; performing, by a computer, a sentiment-based analysis of the specific content responsive to the access attempt; responsive to results of the categorization in light of the sentiment-based analysis of the specific content, determining, by a computer, whether the filtering policy permits the protected party to access the specific content; responsive to results of the determining step, managing, by a computer, the attempted access of the specific content by the protected party. 8. The method of claim 1 wherein categorizing, by a computer, the specific content based on occurrence of predefined words further comprises: categorizing, by a computer, the specific content based on occurrence of predefined words in real-time in conjunction with an attempt by the protected party to download the specific content. | 0.730519 |
9,799,335 | 1 | 4 | 1. A method for speech recognition implemented by a speech recognition device comprising: receiving a first speech signal issued by multiple users; performing analog to digital conversion on the first speech signal to generate a first digital signal after the analog to digital conversion; extracting a first speech parameter from the first digital signal, the first speech parameter describing a speech feature of the first speech signal; if the first speech parameter coincides with a first prestored speech parameter in a sample library, executing control signaling instructed by the first digital signal, the sample library prestoring prestored speech parameters of N users, N≧1; wherein extracting the first speech parameter from the first digital signal comprises: performing signal filtering on the first digital signal so as to obtain at least a first sub signal corresponding to a first user and a second sub signal corresponding to a second user from the filtered first digital signal; extracting, from the first sub signal, a second speech parameter that describes a speech feature of the first sub signal, and extracting, from the second sub signal, a third speech parameter that describes a speech feature of the second sub signal; wherein the first speech parameter comprises the second speech parameter and the third speech parameter. | 1. A method for speech recognition implemented by a speech recognition device comprising: receiving a first speech signal issued by multiple users; performing analog to digital conversion on the first speech signal to generate a first digital signal after the analog to digital conversion; extracting a first speech parameter from the first digital signal, the first speech parameter describing a speech feature of the first speech signal; if the first speech parameter coincides with a first prestored speech parameter in a sample library, executing control signaling instructed by the first digital signal, the sample library prestoring prestored speech parameters of N users, N≧1; wherein extracting the first speech parameter from the first digital signal comprises: performing signal filtering on the first digital signal so as to obtain at least a first sub signal corresponding to a first user and a second sub signal corresponding to a second user from the filtered first digital signal; extracting, from the first sub signal, a second speech parameter that describes a speech feature of the first sub signal, and extracting, from the second sub signal, a third speech parameter that describes a speech feature of the second sub signal; wherein the first speech parameter comprises the second speech parameter and the third speech parameter. 4. The method according to claim 1 , wherein if the first speech parameter coincides with the first prestored speech parameter in the sample library, executing control signalling instructed by the first digital signal comprises: determining whether the sample library comprises a second prestored speech parameter that coincides with the second speech parameter, and/or a third prestored speech parameter that coincides with the third speech parameter; if the sample library comprises a second prestored speech parameter that coincides with the second speech parameter, executing control signalling instructed by the first sub signal; and/or, if the sample library comprises a third prestored speech parameter that coincides with the third speech parameter, executing control signalling instructed by the second sub signal. | 0.545806 |
8,676,802 | 1 | 5 | 1. A non-transitory computer readable medium having instructions stored thereon that cause a processor to retrieve documents in response to at least one search term from a user, the retrieving the documents comprising: receiving the search term for searching a plurality of text documents, wherein each text document is associated with one or more salient terms extracted from the document and each text document is associated with one or more properties that represent the one or more extracted salient terms; retrieving a first set of retrieved documents from a query of the plurality of text documents, wherein each of the retrieved documents comprises the search term; retrieving the associated salient terms for each of the retrieved documents and the associated properties; grouping based on a distance metric the retrieved salient terms into one or more clusters of salient terms and providing the clusters of salient terms to the user, wherein each of the cluster of salient terms corresponds to one of the properties associated with the retrieved documents and each cluster displays the associated salient terms; receiving a selection of a first cluster of the clusters of salient terms from the user, wherein the first cluster comprises first salient terms; selecting a second set of retrieved documents from the first set of retrieved documents, wherein each second set document of the second set includes at least one of the first salient terms of the first cluster of salient terms; retrieving associated second salient terms for each of the second set documents; and grouping the second salient terms into one or more second clusters of salient terms and providing the second clusters of salient terms to the user. | 1. A non-transitory computer readable medium having instructions stored thereon that cause a processor to retrieve documents in response to at least one search term from a user, the retrieving the documents comprising: receiving the search term for searching a plurality of text documents, wherein each text document is associated with one or more salient terms extracted from the document and each text document is associated with one or more properties that represent the one or more extracted salient terms; retrieving a first set of retrieved documents from a query of the plurality of text documents, wherein each of the retrieved documents comprises the search term; retrieving the associated salient terms for each of the retrieved documents and the associated properties; grouping based on a distance metric the retrieved salient terms into one or more clusters of salient terms and providing the clusters of salient terms to the user, wherein each of the cluster of salient terms corresponds to one of the properties associated with the retrieved documents and each cluster displays the associated salient terms; receiving a selection of a first cluster of the clusters of salient terms from the user, wherein the first cluster comprises first salient terms; selecting a second set of retrieved documents from the first set of retrieved documents, wherein each second set document of the second set includes at least one of the first salient terms of the first cluster of salient terms; retrieving associated second salient terms for each of the second set documents; and grouping the second salient terms into one or more second clusters of salient terms and providing the second clusters of salient terms to the user. 5. The non-transitory computer readable medium of claim 1 , the retrieving the documents further comprising, after selecting the second set of retrieved documents, iteratively repeating the retrieving the associated salient terms, grouping the retrieved salient terms into one or more clusters of salient terms, receiving the selection of a first cluster, and selecting a second set of retrieved documents in response to additional selections of a cluster by the user. | 0.590909 |
8,442,496 | 15 | 20 | 15. A non-transitory computer-readable storage medium comprising instructions that, when executed by a processor, cause the processor to perform operations comprising: receiving a call for a called party at the voicemail system, the voicemail system comprising a stored language preference for the called party; prompting a calling party to leave a message; creating the message; providing a plurality of calling-party-selected language preferences; prompting the calling party to select, from the plurality of calling-party-selected language preferences, a calling-party-selected language preference for the message; in response to prompting the calling party to select, from the plurality of calling-party-selected language preferences, the calling-party-selected language preference for the message, receiving the calling-party-selected language preference for the message; overriding the stored language preference for the called party with the calling-party-selected language preference; determining whether the message is in the calling-party-selected language preference; and in response to overriding the stored language preference with the calling-party-selected language preference, and if the message is not in the calling-party-selected preferred language identified by the language preference, translating the message into a preferred language of the calling-party-selected preferred language preference, thereby creating a translated message. | 15. A non-transitory computer-readable storage medium comprising instructions that, when executed by a processor, cause the processor to perform operations comprising: receiving a call for a called party at the voicemail system, the voicemail system comprising a stored language preference for the called party; prompting a calling party to leave a message; creating the message; providing a plurality of calling-party-selected language preferences; prompting the calling party to select, from the plurality of calling-party-selected language preferences, a calling-party-selected language preference for the message; in response to prompting the calling party to select, from the plurality of calling-party-selected language preferences, the calling-party-selected language preference for the message, receiving the calling-party-selected language preference for the message; overriding the stored language preference for the called party with the calling-party-selected language preference; determining whether the message is in the calling-party-selected language preference; and in response to overriding the stored language preference with the calling-party-selected language preference, and if the message is not in the calling-party-selected preferred language identified by the language preference, translating the message into a preferred language of the calling-party-selected preferred language preference, thereby creating a translated message. 20. The non-transitory computer-readable storage medium claim 15 , wherein the instructions for overriding the stored language preference for the called party with the calling-party-selected language preference comprise instructions for overriding the stored language preference for the called party with the calling-party-selected language preference in response to a trigger initiated by the called party to perform the override. | 0.526374 |
9,342,557 | 23 | 24 | 23. A method of executing a query in a HADOOP™ distributed computing cluster having multiple data nodes forming a peer-to-peer network for the query, each data node functioning as a peer in the peer-to-peer network and being capable of interacting with components of HADOOP™ cluster, each peer having an instance of a query engine running in memory, each instance of the query engine is configured to perform; the method comprising: receiving, by a one data node in the distributed computing cluster, a query; designating the one data node that receives the query as a coordinating data node; obtaining, by the coordinating data node and through a state store and a name node, (1) membership information regarding all query engine instances that are running in the cluster, and (2) location information regarding where data blocks relevant to the query are distributed among the plurality of data nodes, wherein the state store is separate from the data nodes; parsing the query to create fragments of the query based on data obtained from the state store and the name node; constructing a query plan based on the data obtained from the state store; distributing, by the coordinating data node and according to the query plan, the fragments of the query to data nodes in the distributed computing cluster that have data relevant to the query; receiving, from the data nodes having data relevant to the query, intermediate results corresponding to execution of the fragments of the query; and generating a final result based on the intermediate results for a client. | 23. A method of executing a query in a HADOOP™ distributed computing cluster having multiple data nodes forming a peer-to-peer network for the query, each data node functioning as a peer in the peer-to-peer network and being capable of interacting with components of HADOOP™ cluster, each peer having an instance of a query engine running in memory, each instance of the query engine is configured to perform; the method comprising: receiving, by a one data node in the distributed computing cluster, a query; designating the one data node that receives the query as a coordinating data node; obtaining, by the coordinating data node and through a state store and a name node, (1) membership information regarding all query engine instances that are running in the cluster, and (2) location information regarding where data blocks relevant to the query are distributed among the plurality of data nodes, wherein the state store is separate from the data nodes; parsing the query to create fragments of the query based on data obtained from the state store and the name node; constructing a query plan based on the data obtained from the state store; distributing, by the coordinating data node and according to the query plan, the fragments of the query to data nodes in the distributed computing cluster that have data relevant to the query; receiving, from the data nodes having data relevant to the query, intermediate results corresponding to execution of the fragments of the query; and generating a final result based on the intermediate results for a client. 24. The method of claim 23 , wherein the data nodes execute the fragments of the query on a distributed file system or a data store of the distributed computing cluster. | 0.783887 |
8,726,169 | 1 | 31 | 1. A method for enabling structured communication among a social network including a computer, the method comprising: receiving, by the computer, input pertaining to a question; formulating by the computer the question based upon the input; generating by the computer an answer pattern including potential responses to the question based upon a form of the question; translating and transmitting by the computer a message including the question and the answer pattern having the potential responses to the question to a plurality of users over a corresponding plurality of preferred messaging platforms from among a plurality of different messaging platforms for eliciting responses to the question from two or more of the users using the answer pattern; collecting and aggregating by the computer the responses to the question from a corresponding two or more of the plurality of preferred messaging platforms; and presenting by the computer the responses in a summary format, wherein the plurality of preferred messaging platforms comprises, for each user of the plurality of users, a corresponding preferred messaging platform for that user from among the plurality of preferred messaging platforms. | 1. A method for enabling structured communication among a social network including a computer, the method comprising: receiving, by the computer, input pertaining to a question; formulating by the computer the question based upon the input; generating by the computer an answer pattern including potential responses to the question based upon a form of the question; translating and transmitting by the computer a message including the question and the answer pattern having the potential responses to the question to a plurality of users over a corresponding plurality of preferred messaging platforms from among a plurality of different messaging platforms for eliciting responses to the question from two or more of the users using the answer pattern; collecting and aggregating by the computer the responses to the question from a corresponding two or more of the plurality of preferred messaging platforms; and presenting by the computer the responses in a summary format, wherein the plurality of preferred messaging platforms comprises, for each user of the plurality of users, a corresponding preferred messaging platform for that user from among the plurality of preferred messaging platforms. 31. The method of claim 1 , further comprising suggesting one or more follow up questions based upon a response to a prior question. | 0.930672 |
9,350,753 | 24 | 25 | 24. A computer vulnerability discovery system comprising: interfaces to a plurality of researcher computers; control logic logically interposed between a researcher computer of the plurality of researcher computers and one or more target systems, wherein the researcher computer is a computer operated by, or to be operated by, an invited researcher, wherein an invited researcher is a person or organization selected to participate in one or more computer vulnerability research projects directed to researching and/or identifying computer vulnerabilities of the one or more target systems comprising one or more network component and/or one or more computer component; storage for access credentials for a management computer associated with the control logic to allow access to the control logic by particular ones of the plurality of researcher computers; storage for data about an assignment of a particular computer vulnerability research project of the one or more computer vulnerability research projects to the researcher computer or to the invited researcher, wherein the particular computer vulnerability research project relates to a particular target system; an interface for a communications path between the control logic and the particular target system; a monitor, coupled to the control logic, for monitoring networked data communications between the researcher computer and the particular target system, wherein the networked data communications include communications that are usable to identify a candidate vulnerability of the particular target system; storage for data about a candidate vulnerability of the particular target system based on a report received from the invited researcher resulting from the invited researcher's use of the researcher computer to interact with the particular target system via the control logic; storage for validation data about the report of the candidate vulnerability of the particular target system, including data about attempted duplication of the candidate vulnerability after receiving the report; and an output for providing a message triggering one or more remediation operations on the particular target system based at least in part upon the report. | 24. A computer vulnerability discovery system comprising: interfaces to a plurality of researcher computers; control logic logically interposed between a researcher computer of the plurality of researcher computers and one or more target systems, wherein the researcher computer is a computer operated by, or to be operated by, an invited researcher, wherein an invited researcher is a person or organization selected to participate in one or more computer vulnerability research projects directed to researching and/or identifying computer vulnerabilities of the one or more target systems comprising one or more network component and/or one or more computer component; storage for access credentials for a management computer associated with the control logic to allow access to the control logic by particular ones of the plurality of researcher computers; storage for data about an assignment of a particular computer vulnerability research project of the one or more computer vulnerability research projects to the researcher computer or to the invited researcher, wherein the particular computer vulnerability research project relates to a particular target system; an interface for a communications path between the control logic and the particular target system; a monitor, coupled to the control logic, for monitoring networked data communications between the researcher computer and the particular target system, wherein the networked data communications include communications that are usable to identify a candidate vulnerability of the particular target system; storage for data about a candidate vulnerability of the particular target system based on a report received from the invited researcher resulting from the invited researcher's use of the researcher computer to interact with the particular target system via the control logic; storage for validation data about the report of the candidate vulnerability of the particular target system, including data about attempted duplication of the candidate vulnerability after receiving the report; and an output for providing a message triggering one or more remediation operations on the particular target system based at least in part upon the report. 25. The computer vulnerability discovery system of claim 24 , further comprising: a leaderboard data structure that includes records of researchers, researcher identifiers, awards the researchers have earned or obtained; and a display presentation for viewing by researchers wherein the display presentation illustrates relative awards over multiple unrelated or distributed researchers so as to encourage competition to find vulnerabilities. | 0.7724 |
6,085,196 | 6 | 8 | 6. A system according to claim 1, wherein the means for interactively creating comprises: a map creator object. | 6. A system according to claim 1, wherein the means for interactively creating comprises: a map creator object. 8. A system according to claim 6, wherein the map creator object comprises: a reference to a software object for an element for transformation of the first structured information format; a reference to a software object for an element of the second structured information format, for transformation of the element of the first structured information format; a reference to a software object for a property of the element of the second structured information format, for transformation of the element of the first structured information format; a reference to a software object for an attribute value of the element of the second structured information format, for transformation of the element of the first structured information format; an object method for obtaining the element for transformation of the first structured information format, which has been interactively selected by the user, using the software object for the element for transformation of the first structured information format; an object method for obtaining the element of the second structured information format which corresponds to the element of the first structured information format, which has been interactively selected by the user, using the software object for the element of the second structured information format; an object method for determining a property of the element of the second structured information format which has been selected by the user, using the software object for a property of the element of the second structured information format; an object method for obtaining a second structured information format attribute value which has been interactively input by a user, using the software object for the attribute value of the element of the second structured information format; and an object method for assigning the attribute value which has been interactively input by a user to the second structured information format attribute value. | 0.569118 |
7,698,328 | 15 | 16 | 15. A system, comprising: one or more computers configured to perform operations including: receiving a first search query including one or more search terms; providing a first set of documents responsive to the first query; determining one or more collocations from the first set of documents that include at least one of the search terms, each collocation including at least one other term that is semantically related to the at least one search term; scoring the collocations from the first set of documents, including determining a mutual information score for each collocation using a mutual information test; multiplying at least some collocation scores by frequency counts, a frequency count for a given collocation representing a number of times the collocation occurs in a document of the first set of documents; determining a subset of the first set of documents to present to a user based on the scored collocations; providing one or more user interface elements to be used by a user to include and exclude documents from the first set of documents that contain at least one specified collocation of the collocations; receiving user input specifying inclusion or exclusion of documents from the first set of documents that contain at least one of the collocations; refining the first search query to produce a second query based on the user input; and providing a second set of documents responsive to the second query, where the second set of documents includes or excludes documents containing the specified collocation. | 15. A system, comprising: one or more computers configured to perform operations including: receiving a first search query including one or more search terms; providing a first set of documents responsive to the first query; determining one or more collocations from the first set of documents that include at least one of the search terms, each collocation including at least one other term that is semantically related to the at least one search term; scoring the collocations from the first set of documents, including determining a mutual information score for each collocation using a mutual information test; multiplying at least some collocation scores by frequency counts, a frequency count for a given collocation representing a number of times the collocation occurs in a document of the first set of documents; determining a subset of the first set of documents to present to a user based on the scored collocations; providing one or more user interface elements to be used by a user to include and exclude documents from the first set of documents that contain at least one specified collocation of the collocations; receiving user input specifying inclusion or exclusion of documents from the first set of documents that contain at least one of the collocations; refining the first search query to produce a second query based on the user input; and providing a second set of documents responsive to the second query, where the second set of documents includes or excludes documents containing the specified collocation. 16. The system of claim 15 , where the one or more collocations are retrieved from a collocation index. | 0.840557 |
8,856,142 | 10 | 11 | 10. A computer-implemented method for an interactive graphical search interface, the method comprising: generating, using a search engine database, a plurality of related search parameters based on one or more of initial search parameters; generating, by a processor, a multi-dimensional search space having a plurality of vertices, based on the initial and related search parameters, wherein each vertex is populated with and represents one of the initial or related search parameters; transmitting a graphical interface projecting the multi-dimensional search space, along with one or more elements by which adjustments to a weighting of one or more of the one or more initial search parameters and the plurality of related search parameters; and transmitting a plurality of updated search results based on the adjusted weights of the initial and related search parameters, wherein each of the one or more elements is movable toward or away from a center of the multi-dimensional search space to change the weighting of one or more of the one or more initial search parameters and the plurality of related search parameters. | 10. A computer-implemented method for an interactive graphical search interface, the method comprising: generating, using a search engine database, a plurality of related search parameters based on one or more of initial search parameters; generating, by a processor, a multi-dimensional search space having a plurality of vertices, based on the initial and related search parameters, wherein each vertex is populated with and represents one of the initial or related search parameters; transmitting a graphical interface projecting the multi-dimensional search space, along with one or more elements by which adjustments to a weighting of one or more of the one or more initial search parameters and the plurality of related search parameters; and transmitting a plurality of updated search results based on the adjusted weights of the initial and related search parameters, wherein each of the one or more elements is movable toward or away from a center of the multi-dimensional search space to change the weighting of one or more of the one or more initial search parameters and the plurality of related search parameters. 11. The method of claim 10 , further comprising: generating, by a processor, a matrix of hyperlinks within the multi-dimensional search space, each hyperlink having coordinates within the search space defining a relevance of the hyperlink to each of the one or more initial search parameters and the plurality of related search parameters. | 0.704188 |
9,396,178 | 7 | 8 | 7. A computer implemented method for automated dictionary population, comprising: providing a processor executing instructions for: receiving a message containing words; parsing the words of the message; comparing each word to entries of at least one dictionary to identify new words that are not in said at least one dictionary; and storing said new words in a supplementary word list; and further comprising processing profanities, wherein the processing profanities comprises: identifying profanities within the parsed words by comparing the parsed words to a profanity word list; modifying the profanities by replacing at least some of the profanity with a symbol. | 7. A computer implemented method for automated dictionary population, comprising: providing a processor executing instructions for: receiving a message containing words; parsing the words of the message; comparing each word to entries of at least one dictionary to identify new words that are not in said at least one dictionary; and storing said new words in a supplementary word list; and further comprising processing profanities, wherein the processing profanities comprises: identifying profanities within the parsed words by comparing the parsed words to a profanity word list; modifying the profanities by replacing at least some of the profanity with a symbol. 8. The method of claim 7 , further comprising: displaying the modified profanity to a user in a candidate list; requesting feedback from the user; receiving user feedback, wherein the feedback includes selection and de-selection of the profanities, wherein de-selection of the profanity may be at least one of explicit and implicit; if the feedback includes selection of the profanities: then, displaying the profanity to the user; and storing the profanities; else, if the feedback includes de-selection of the profanities: then, removing the profanities from the candidate list. | 0.500861 |
5,386,494 | 34 | 35 | 34. The apparatus of claim 32, wherein the data processing system is for displaying on the display a list of alternative commands for the spoken command and the cursor control device is for selecting either the spoken command or one of the commands in the list of alternative commands. | 34. The apparatus of claim 32, wherein the data processing system is for displaying on the display a list of alternative commands for the spoken command and the cursor control device is for selecting either the spoken command or one of the commands in the list of alternative commands. 35. The apparatus of claim 34, wherein the data processing system is for displaying the list of alternative commands as a menu and for displaying a synonym menu for one of the alternative commands in response to user-manipulation of the cursor control device. | 0.895649 |
8,849,031 | 6 | 10 | 6. A non-transitory computer-readable medium that stores computer-readable instructions that, when executed by a computer, cause the computer to perform a computer-implemented method comprising: capturing a source image using a first machine; segmenting said source image into first planes using said first machine; structurally analyzing said first planes to identify different regions using said first machine each of said regions sharing similar text attributes comprising at least one of a specific size and shape; creating second planes from said first planes such that a separate second plane is created for each of said regions using said first machine; associating tags with said second planes using said first machine, said tags comprising spatial location of said regions within said first planes; combining said second planes and associated tags into a mixed raster content document using said first machine; and performing a separate recognition process on each of said second planes using a second machine, wherein each of said first planes comprises a mask plane and foreground plane combination. | 6. A non-transitory computer-readable medium that stores computer-readable instructions that, when executed by a computer, cause the computer to perform a computer-implemented method comprising: capturing a source image using a first machine; segmenting said source image into first planes using said first machine; structurally analyzing said first planes to identify different regions using said first machine each of said regions sharing similar text attributes comprising at least one of a specific size and shape; creating second planes from said first planes such that a separate second plane is created for each of said regions using said first machine; associating tags with said second planes using said first machine, said tags comprising spatial location of said regions within said first planes; combining said second planes and associated tags into a mixed raster content document using said first machine; and performing a separate recognition process on each of said second planes using a second machine, wherein each of said first planes comprises a mask plane and foreground plane combination. 10. The computer-readable medium according to claim 6 , wherein said structurally analyzing of said first planes comprises using a document model. | 0.592179 |
9,424,836 | 1 | 4 | 1. A computer-implemented method comprising acts of: receiving, via at least one network, adaptation data generated at least in part by performing statistical processing on audio data comprising at least one user utterance; and using the adaptation data to update at least one acoustic model for use in speech recognition processing, wherein the adaptation data is in a format that prevents reconstruction of the audio data. | 1. A computer-implemented method comprising acts of: receiving, via at least one network, adaptation data generated at least in part by performing statistical processing on audio data comprising at least one user utterance; and using the adaptation data to update at least one acoustic model for use in speech recognition processing, wherein the adaptation data is in a format that prevents reconstruction of the audio data. 4. The computer-implemented method of claim 1 , wherein: the adaptation data comprises first adaptation data and second adaptation data; the first adaptation data is generated at least in part by performing statistical processing on first audio data comprising at least one first utterance spoken by a first user; the second adaptation data is generated at least in part by performing statistical processing on second audio data comprising at least one second utterance spoken by a second user different from the first user; and the act of using the adaptation data comprises aggregating the first adaptation data and the second adaptation data. | 0.618343 |
8,131,552 | 4 | 5 | 4. The method of claim 3 , further comprising: identifying at least one target speaker using the audio components and the visual components. | 4. The method of claim 3 , further comprising: identifying at least one target speaker using the audio components and the visual components. 5. The method of claim 4 , further comprising: generating a summary of multimedia content based on the audio components, the visual components, the text components, the semantically coherent text blocks, and the identified target speaker. | 0.913455 |
7,904,477 | 1 | 2 | 1. A method for handling a plurality of information units in an information processing system through verification process for said plurality of information units, comprising the following steps of: a) converting each information unit in said plurality of information units into verified object by augmenting a first meaning in said information unit with a second meaning, b) expressing the verified objects, converted from said plurality of information units, by object representation for each verified object, c) constructing a processing structure that is capable of applying a plurality of relationships among said verified objects, d) applying said processing structure to said verified objects to handle said plurality of information units according to the relationships, e) handling rules that exist in a distributed network, wherein the rules are used to construct the processing structure that applies the relationship, defined in the rules, among the verified objects, and whereby the rules can be referenced by the information processing system remotely, and f) using a semantic tree as a basis for defining the relationship in the rules, wherein the information units are based on data or event in the information processing system, and wherein the verified objects are semantically augmented information units. | 1. A method for handling a plurality of information units in an information processing system through verification process for said plurality of information units, comprising the following steps of: a) converting each information unit in said plurality of information units into verified object by augmenting a first meaning in said information unit with a second meaning, b) expressing the verified objects, converted from said plurality of information units, by object representation for each verified object, c) constructing a processing structure that is capable of applying a plurality of relationships among said verified objects, d) applying said processing structure to said verified objects to handle said plurality of information units according to the relationships, e) handling rules that exist in a distributed network, wherein the rules are used to construct the processing structure that applies the relationship, defined in the rules, among the verified objects, and whereby the rules can be referenced by the information processing system remotely, and f) using a semantic tree as a basis for defining the relationship in the rules, wherein the information units are based on data or event in the information processing system, and wherein the verified objects are semantically augmented information units. 2. The method according to claim 1 , wherein the method further comprises a step of converting each information unit of the plurality of information units based on data or event in the information processing system into verified object by augmenting the first meaning in said information unit with a second meaning. | 0.703947 |
9,460,199 | 8 | 10 | 8. A computer program product for generating a provenance for a physical object, the computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media, the program instructions comprising: program instructions to identify a first source of information that includes unstructured text and one or more keywords associated with an object; program instructions to retrieve the unstructured text included in the first source; program instructions to identify provenance information of the object that is included in one or more segments of the unstructured text, wherein the identified provenance information is verified; program instructions to add the identified provenance information of the object to a timeline; program instructions to receive a purported provenance information; program instruction to determine a degree of accuracy of the purported provenance information using a statistical analysis based, at least in part, on a number of occurrences of the purported provenance information in the identified provenance information and a source of the purported provenance information, wherein the source of the purported provenance information comprises a historical context and one or more characteristics of a seller of the physical object; and in response to determining the degree of accuracy, program instructions to generate a report, wherein the report compares the purported provenance information to the identified provenance information, and wherein the report comprises (i) the degree of accuracy of the purported provenance information and (ii) an overlap between the purported provenance information and the identified provenance information. | 8. A computer program product for generating a provenance for a physical object, the computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media, the program instructions comprising: program instructions to identify a first source of information that includes unstructured text and one or more keywords associated with an object; program instructions to retrieve the unstructured text included in the first source; program instructions to identify provenance information of the object that is included in one or more segments of the unstructured text, wherein the identified provenance information is verified; program instructions to add the identified provenance information of the object to a timeline; program instructions to receive a purported provenance information; program instruction to determine a degree of accuracy of the purported provenance information using a statistical analysis based, at least in part, on a number of occurrences of the purported provenance information in the identified provenance information and a source of the purported provenance information, wherein the source of the purported provenance information comprises a historical context and one or more characteristics of a seller of the physical object; and in response to determining the degree of accuracy, program instructions to generate a report, wherein the report compares the purported provenance information to the identified provenance information, and wherein the report comprises (i) the degree of accuracy of the purported provenance information and (ii) an overlap between the purported provenance information and the identified provenance information. 10. The computer program product of claim 8 , wherein program instructions to identify provenance information of the object that is included in one or more segments of the unstructured text includes: program instructions to perform text analytics on the unstructured text using a dictionary and a set of rules, wherein the set of rules includes rules to retrieve unstructured text, parse the retrieved text, and extract provenance information from the parsed text, and wherein the dictionary includes a set of keywords that indicate a relationship of an object to a location, and a set of words that indicates the relationship of an object to a time. | 0.636058 |
4,858,170 | 7 | 10 | 7. A method for rapidly recording vocalized speech comprising spoken words and transcribing said spoken words into commonly readable, text comprising the steps of: assigned an alphabetic shorthand code to said spoken words, said code being derived by a. omitting all silent letters appearing in each said spoken word of said vocalized speech; b. omitting a consonant where two of the same said consonants appear consecutively in the same said spoken word; c. omitting a vowel where two of the same said vowels appear consecutively in the same said spoken word; d. omitting all unaccented vowels from each said spoken word; e. omitting the letter combinations "la" and "ta" in each said spoken word where said spoken word has more than one syllable; f. omitting the letter "d" in each said spoken word where said letter "d" appears after the letter "n" and occurs in the same syllable; g. writing the letter "y" in each said spoken word wherever the "y" sound is heard; h. omitting the letters "t" in each said spoken word where said letter "t" occurs after the letter "s"; i. omitting the letter "t" in each said spoken word where said letter "t" occurs after the letter "x"; j. replacing the letter combination "ct" with the letter "k" in each said spoken word where said letter combination "ct" occurs; and entering into an appropriately programmed data processing system said alphabetic shorthand code to produced said spoken words in typed or printed form. | 7. A method for rapidly recording vocalized speech comprising spoken words and transcribing said spoken words into commonly readable, text comprising the steps of: assigned an alphabetic shorthand code to said spoken words, said code being derived by a. omitting all silent letters appearing in each said spoken word of said vocalized speech; b. omitting a consonant where two of the same said consonants appear consecutively in the same said spoken word; c. omitting a vowel where two of the same said vowels appear consecutively in the same said spoken word; d. omitting all unaccented vowels from each said spoken word; e. omitting the letter combinations "la" and "ta" in each said spoken word where said spoken word has more than one syllable; f. omitting the letter "d" in each said spoken word where said letter "d" appears after the letter "n" and occurs in the same syllable; g. writing the letter "y" in each said spoken word wherever the "y" sound is heard; h. omitting the letters "t" in each said spoken word where said letter "t" occurs after the letter "s"; i. omitting the letter "t" in each said spoken word where said letter "t" occurs after the letter "x"; j. replacing the letter combination "ct" with the letter "k" in each said spoken word where said letter combination "ct" occurs; and entering into an appropriately programmed data processing system said alphabetic shorthand code to produced said spoken words in typed or printed form. 10. The method for recording and transcribing of claim 7 wherein commonly repeated prefixes and suffixes of said vocalized speech are replaced with alphabetic shorthand codes. | 0.949451 |
8,707,185 | 4 | 9 | 4. The system of claim 2 , further comprising: a web widget comprising device-executable code stored at a non-transitory data storage medium and configured, when executed, as a viewer-perceivable GUI within, overlying, or proximate viewer-perceivable content presented to the viewer at the viewer device, and further configured with a remote-user identification portion, a remote-user interaction portion, and a shared window GUI accessing means. | 4. The system of claim 2 , further comprising: a web widget comprising device-executable code stored at a non-transitory data storage medium and configured, when executed, as a viewer-perceivable GUI within, overlying, or proximate viewer-perceivable content presented to the viewer at the viewer device, and further configured with a remote-user identification portion, a remote-user interaction portion, and a shared window GUI accessing means. 9. The system of claim 4 , wherein all of or any portion of the device-executable code is executed by a service-provider device coupled in communication with each of the viewer device and the remote user device via the data transfer network, and wherein the result of such execution is presented to either or both of the viewer and the remote user at their respective devices. | 0.940638 |
8,286,150 | 6 | 7 | 6. The module generating method according to claim 5 , wherein the commonizing further involves junction-node-restructuring that is based on the block structure information and the appendant information and involves focusing on one block defined as a subroutine, extracting a node directly related to the block of focus by tracing back a processing sequence to a node that is in an ancestor block upstream in the processing sequence from the block of focus and from which the block of focus is reached as a result of sequential processing, and by tracing the processing sequence to a node that is in a descendant block downstream in the processing sequence from the block of focus and that is processed after the block of focus. | 6. The module generating method according to claim 5 , wherein the commonizing further involves junction-node-restructuring that is based on the block structure information and the appendant information and involves focusing on one block defined as a subroutine, extracting a node directly related to the block of focus by tracing back a processing sequence to a node that is in an ancestor block upstream in the processing sequence from the block of focus and from which the block of focus is reached as a result of sequential processing, and by tracing the processing sequence to a node that is in a descendant block downstream in the processing sequence from the block of focus and that is processed after the block of focus. 7. The module generating method according to claim 6 , wherein the commonizing further involves identical-portion-merging that, with respect to a plurality of portions that use the block of focus extracted from the program at the junction-node-restructuring, involves comparing nodes in ancestor blocks of the block of focus, merging the ancestor blocks, comparing nodes in descendant blocks of the block of focus, merging the descendant blocks, and obtaining merged-block information as a result of the merging of the ancestor blocks and of the descendant blocks. | 0.867668 |
9,607,058 | 11 | 12 | 11. A method of managing documents associated with one or more patent applications, the method comprising: associating a first database record and a second database record with a patent family identifier, wherein the first database record corresponds to a first patent application and the second database record corresponds to a second patent application; retrieving a reference from a patent data resource using a crawler service based on one or more of the patent family identifier, the first patent application, and the second patent application; based on a determination that automatic text extraction is applicable to the reference, generating an optical character recognition (OCR) version of the reference, wherein generating the OCR version of the reference comprises converting the reference from a native file format to a format that facilitates automatic data extraction; based on a determination that the OCR version of the reference meets or exceeds a confidence level threshold, matching the OCR version of the reference to at least one of a plurality of reference templates, wherein matching the OCR version of the reference to at least one of the plurality of reference templates comprises comparing at least a portion of the extractable data in the OCR version of the reference to one or more of the plurality of reference templates to identify a match; extracting a select data from the OCR version of the reference based on the at least one of the plurality of reference templates; validating the extracted data, wherein the validating the extracted data comprises determining that the extracted data is not already associated with one or more of the first database record and the second database record; populating a plurality of input fields of an information disclosure statement (IDS) form using at least the validated extracted data, wherein at least one of the plurality of input fields includes descriptive data corresponding to the reference; presenting an IDS review interface to a reviewing user, the IDS review interface comprising a representation of a review version of the populated IDS form and a representation of the reference indicating a new reference; and presenting a set of selectable new reference options to the reviewing user, wherein the set of selectable new reference options comprise: a self-citation option; an include option; a don't include option; and a do not file option. | 11. A method of managing documents associated with one or more patent applications, the method comprising: associating a first database record and a second database record with a patent family identifier, wherein the first database record corresponds to a first patent application and the second database record corresponds to a second patent application; retrieving a reference from a patent data resource using a crawler service based on one or more of the patent family identifier, the first patent application, and the second patent application; based on a determination that automatic text extraction is applicable to the reference, generating an optical character recognition (OCR) version of the reference, wherein generating the OCR version of the reference comprises converting the reference from a native file format to a format that facilitates automatic data extraction; based on a determination that the OCR version of the reference meets or exceeds a confidence level threshold, matching the OCR version of the reference to at least one of a plurality of reference templates, wherein matching the OCR version of the reference to at least one of the plurality of reference templates comprises comparing at least a portion of the extractable data in the OCR version of the reference to one or more of the plurality of reference templates to identify a match; extracting a select data from the OCR version of the reference based on the at least one of the plurality of reference templates; validating the extracted data, wherein the validating the extracted data comprises determining that the extracted data is not already associated with one or more of the first database record and the second database record; populating a plurality of input fields of an information disclosure statement (IDS) form using at least the validated extracted data, wherein at least one of the plurality of input fields includes descriptive data corresponding to the reference; presenting an IDS review interface to a reviewing user, the IDS review interface comprising a representation of a review version of the populated IDS form and a representation of the reference indicating a new reference; and presenting a set of selectable new reference options to the reviewing user, wherein the set of selectable new reference options comprise: a self-citation option; an include option; a don't include option; and a do not file option. 12. The method of claim 11 , wherein the associating a first database record and a second database record with a patent family identifier comprises a linkage type of: a parent linkage; a child linkage; or a foreign priority linkage. | 0.878023 |
8,086,442 | 10 | 11 | 10. A method of dividing natural language text into segments, the method comprising: using a processor to perform acts comprising: representing one or more sentence breaking rules in a first regular expression, wherein any sentence breaking rule that has both before and after patterns is included in said first regular expression as a positive lookbehind for the before pattern followed by a non-capture group for the after pattern, wherein any sentence break rule that has only a before pattern is included in said first regular expression as a positive lookbehind for the before pattern, and wherein any sentence breaking rule that has only an after pattern is included in said first regular expression as a positive lookahead for the after pattern; combining a plurality of exceptions to said one or more sentence breaking rules disjunctively into a second regular expression, said second regular expression being distinct from said first regular expression, wherein any exception that has both before and after patterns is included in said second regular expression as the before pattern followed by a non-capture group for the after pattern, and wherein any exception that has only an after pattern or a before pattern but not both is included in said second regular expression as the before or after pattern; finding first strings in said natural language text that match said second regular expression; replacing said first strings with placeholders to create a second string, wherein said second string comprises said natural language text but with said placeholders in place of said first strings; subsequent to said finding and said replacing, using said first regular expression to detect sentence break points in said second string; and subsequent to detecting said sentence break points, replacing said placeholders in said second string with said first strings. | 10. A method of dividing natural language text into segments, the method comprising: using a processor to perform acts comprising: representing one or more sentence breaking rules in a first regular expression, wherein any sentence breaking rule that has both before and after patterns is included in said first regular expression as a positive lookbehind for the before pattern followed by a non-capture group for the after pattern, wherein any sentence break rule that has only a before pattern is included in said first regular expression as a positive lookbehind for the before pattern, and wherein any sentence breaking rule that has only an after pattern is included in said first regular expression as a positive lookahead for the after pattern; combining a plurality of exceptions to said one or more sentence breaking rules disjunctively into a second regular expression, said second regular expression being distinct from said first regular expression, wherein any exception that has both before and after patterns is included in said second regular expression as the before pattern followed by a non-capture group for the after pattern, and wherein any exception that has only an after pattern or a before pattern but not both is included in said second regular expression as the before or after pattern; finding first strings in said natural language text that match said second regular expression; replacing said first strings with placeholders to create a second string, wherein said second string comprises said natural language text but with said placeholders in place of said first strings; subsequent to said finding and said replacing, using said first regular expression to detect sentence break points in said second string; and subsequent to detecting said sentence break points, replacing said placeholders in said second string with said first strings. 11. The method of claim 10 , wherein said acts further comprise: choosing said placeholders to be strings that do not occur in said natural language. | 0.732975 |
8,606,560 | 8 | 10 | 8. The system according to claim 1 , wherein the acquisition device is an audio acquisition device ( 4 , 6 ) and the recognition device is a speech recognition device ( 30 ) which produce the source sentence from a sentence spoken in the source language acquired by the audio acquisition device. | 8. The system according to claim 1 , wherein the acquisition device is an audio acquisition device ( 4 , 6 ) and the recognition device is a speech recognition device ( 30 ) which produce the source sentence from a sentence spoken in the source language acquired by the audio acquisition device. 10. The system according to claim 8 , wherein the interpretation system facilitates bidirectional interpretation, the interpretation system producing, according to a first channel of interpretation, an interpretation, into a second target language, of speech in a first source language and producing, according to a second channel of interpretation, an interpretation, into a first target language, of speech in a second source language, the first source language and the second target language and the second source language and the first target language is identical, the interpretation system including a first audio acquisition device ( 4 ) and a first audio restoration device ( 3 ) and a second audio acquisition device ( 6 ) and a second audio restoration device ( 5 ). | 0.876904 |
9,201,965 | 7 | 8 | 7. Logic encoded in one or more non-transitory media that includes code for execution and when executed by a processor is operable to perform operations comprising: receiving data propagating in a network environment; ignoring Joint Photographic Experts Group (JPEG) documents in the data; identifying an audio and video media file in the data, wherein the audio and video media file is associated with a plurality of individuals; generating a text file based on the audio and video media file; comparing the text file to a plurality of blacklisted words; dropping the text file if a blacklisted word is found in the text file; identifying selected words within the text file based on a whitelist to create a first word list, wherein the first word list includes fewer words than the text file; comparing the selected words in the first word list to a personal vocabulary database associated with an individual from the plurality of individuals, wherein the personal vocabulary database associated with the individual includes one or more words that the individual added to the personal vocabulary database, and wherein words in the personal vocabulary database associated with the individual may be marked as private; and removing from the first word list, one or more of the selected words to create a second word list based on the selected words not being found in the personal vocabulary database associated with the individual, wherein the second word list includes fewer words then the first word list, wherein at least one of the selected words that is removed is associated with a false positive from two words that phonetically sound similar. | 7. Logic encoded in one or more non-transitory media that includes code for execution and when executed by a processor is operable to perform operations comprising: receiving data propagating in a network environment; ignoring Joint Photographic Experts Group (JPEG) documents in the data; identifying an audio and video media file in the data, wherein the audio and video media file is associated with a plurality of individuals; generating a text file based on the audio and video media file; comparing the text file to a plurality of blacklisted words; dropping the text file if a blacklisted word is found in the text file; identifying selected words within the text file based on a whitelist to create a first word list, wherein the first word list includes fewer words than the text file; comparing the selected words in the first word list to a personal vocabulary database associated with an individual from the plurality of individuals, wherein the personal vocabulary database associated with the individual includes one or more words that the individual added to the personal vocabulary database, and wherein words in the personal vocabulary database associated with the individual may be marked as private; and removing from the first word list, one or more of the selected words to create a second word list based on the selected words not being found in the personal vocabulary database associated with the individual, wherein the second word list includes fewer words then the first word list, wherein at least one of the selected words that is removed is associated with a false positive from two words that phonetically sound similar. 8. The logic of claim 7 , the processor being further operable to perform operations comprising: generating a resultant after removing one or more of the selected words, wherein the resultant is separated into fields that identify a title and an author associated with the resultant. | 0.520339 |
9,905,222 | 8 | 9 | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: mapping call-types between a first spoken dialog system and a second spoken dialog system using a set of labeled data, to yield mapped call-types; training a model using information based on the mapped call-types; and routing incoming calls based on the model. | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: mapping call-types between a first spoken dialog system and a second spoken dialog system using a set of labeled data, to yield mapped call-types; training a model using information based on the mapped call-types; and routing incoming calls based on the model. 9. The system of claim 8 , wherein the mapping of the call-types comprises performing one of splitting the call-types, merging the call-types, and renaming the call-types. | 0.705172 |
7,680,335 | 1 | 11 | 1. A method for identifying a structure of interest within image data, comprising: receiving image data; receiving an initial point within the received image data; transforming the received image data into a scale-space; performing geometric fitting using prior-constrained mean shift on the scale-space image data to identify a structure candidate in a vicinity of the initial point; using the identified structure candidate to set up a prior constraint for subsequent iterations; presenting the identified structure candidate to a user and querying the user to determine whether the identified structure candidate is a structure of interest; and when the identified structure candidate is determined to not be a structure of interest, repeating the steps of performing geometric fitting using prior-constrained mean shift and presenting an identified structure candidate until it is determined that an identified structure candidate is a structure of interest, wherein the above steps are performed by a computer system. | 1. A method for identifying a structure of interest within image data, comprising: receiving image data; receiving an initial point within the received image data; transforming the received image data into a scale-space; performing geometric fitting using prior-constrained mean shift on the scale-space image data to identify a structure candidate in a vicinity of the initial point; using the identified structure candidate to set up a prior constraint for subsequent iterations; presenting the identified structure candidate to a user and querying the user to determine whether the identified structure candidate is a structure of interest; and when the identified structure candidate is determined to not be a structure of interest, repeating the steps of performing geometric fitting using prior-constrained mean shift and presenting an identified structure candidate until it is determined that an identified structure candidate is a structure of interest, wherein the above steps are performed by a computer system. 11. The method of claim 1 , wherein the image data comprises three-dimensional computed tomography (CT) data and the identified structure candidate is indicative of a lung nodule. | 0.833952 |
8,078,965 | 5 | 6 | 5. The method of claim 1 , wherein receiving an indication of a selection of a font scheme for applying to the text selection, further comprises providing a menu of font schemes for applying to the text selection. | 5. The method of claim 1 , wherein receiving an indication of a selection of a font scheme for applying to the text selection, further comprises providing a menu of font schemes for applying to the text selection. 6. The method of claim 5 , further comprising providing the menu of font schemes for applying to the text selection based on a keyboard language identification applicable to the menu of font schemes wherein the menu of font schemes includes font schemes applicable to text runs associated with the keyboard language identification. | 0.944925 |
8,909,591 | 9 | 12 | 9. A processing system for identifying business listings, the processing system comprising: one or more computing devices, each of the one or more computing devices having one or more processors; and a memory, coupled to the one or more processors, for storing business listings; wherein the one or more computing devices is configured to: determine a first frequency value of a business listing characteristic within a first plurality of business listings received from a first source, the first plurality of business listings being associated with a particular business listing context; determine a second frequency value of the business listing characteristic within a second plurality of business listings received from a second source, the second plurality of business listings being associated with the particular business listing context; determine a frequency differential between the first frequency value and the second frequency value; in response to the frequency differential exceeding a threshold differential, identify the business listing characteristic as a differential characteristic; and identify a particular business listing of the plurality of business listings as a spam listing using the differential characteristic. | 9. A processing system for identifying business listings, the processing system comprising: one or more computing devices, each of the one or more computing devices having one or more processors; and a memory, coupled to the one or more processors, for storing business listings; wherein the one or more computing devices is configured to: determine a first frequency value of a business listing characteristic within a first plurality of business listings received from a first source, the first plurality of business listings being associated with a particular business listing context; determine a second frequency value of the business listing characteristic within a second plurality of business listings received from a second source, the second plurality of business listings being associated with the particular business listing context; determine a frequency differential between the first frequency value and the second frequency value; in response to the frequency differential exceeding a threshold differential, identify the business listing characteristic as a differential characteristic; and identify a particular business listing of the plurality of business listings as a spam listing using the differential characteristic. 12. The processing system of claim 9 , wherein the business listing characteristic is at least one of a title length, a text term, a phone number, and an address. | 0.75 |
9,946,790 | 11 | 12 | 11. The system of claim 7 , wherein, when executed, the item categorizing service further causes the at least one computing device to at least determine a number of the plurality of user-created item lists having a respective title term that matches the particular predefined keyword. | 11. The system of claim 7 , wherein, when executed, the item categorizing service further causes the at least one computing device to at least determine a number of the plurality of user-created item lists having a respective title term that matches the particular predefined keyword. 12. The system of claim 11 , wherein the item category is populated with the particular item when a ratio of the number of keyword tags to the number of the plurality of user-created item lists reaches a predefined percentage value. | 0.940391 |
7,842,873 | 7 | 9 | 7. A method for processing an audio file having at least vocal components, the method comprising: detecting a refrain of the audio file by identifying repeated vocal segments in a phonetic transcription of at least a portion of the audio file; generating either or both a phonetic or acoustic representation of the refrain; and storing the generated phonetic or acoustic representation together with the audio file in memory. | 7. A method for processing an audio file having at least vocal components, the method comprising: detecting a refrain of the audio file by identifying repeated vocal segments in a phonetic transcription of at least a portion of the audio file; generating either or both a phonetic or acoustic representation of the refrain; and storing the generated phonetic or acoustic representation together with the audio file in memory. 9. The method of claim 7 , where detecting the refrain includes generating a phonetic transcription of a majority of the audio file and identifying repeating similar segments within the phonetic transcription of the audio file. | 0.502193 |
7,974,912 | 48 | 60 | 48. A computer system that manages pay-per-click advertising, by determining an amount to be charged in response to a click of a hyperlink associated with a target keyword, comprising a memory, and processing hardware configured to: access from memory a particular amount a first advertiser is willing to be charged in response to a click of a hyperlink associated with said first advertiser, access from memory first and second different statistics related to one or more of a rate of use by users, number of times a hyperlink was viewed, data that relates to an increase or decrease in the use of a keyword by users, demographics of users associated with a keyword or demographics of advertisers associated with a keyword, and without human intervention, determine an amount, to be charged to a second advertiser in response to a click of a hyperlink associated with said target keyword and said second advertiser, wherein said amount to be charged to said second advertiser is determined using said particular amount, and is also determined using said first and second statistics. | 48. A computer system that manages pay-per-click advertising, by determining an amount to be charged in response to a click of a hyperlink associated with a target keyword, comprising a memory, and processing hardware configured to: access from memory a particular amount a first advertiser is willing to be charged in response to a click of a hyperlink associated with said first advertiser, access from memory first and second different statistics related to one or more of a rate of use by users, number of times a hyperlink was viewed, data that relates to an increase or decrease in the use of a keyword by users, demographics of users associated with a keyword or demographics of advertisers associated with a keyword, and without human intervention, determine an amount, to be charged to a second advertiser in response to a click of a hyperlink associated with said target keyword and said second advertiser, wherein said amount to be charged to said second advertiser is determined using said particular amount, and is also determined using said first and second statistics. 60. The computer system of claim 48 wherein the determination of the amount includes the use of a minimum currency amount. | 0.870488 |
9,117,447 | 11 | 15 | 11. The system of claim 10 , wherein the event alert is issued by a calendar application, and the context data is a text string associated with a previously created calendar event stored by the calendar application. | 11. The system of claim 10 , wherein the event alert is issued by a calendar application, and the context data is a text string associated with a previously created calendar event stored by the calendar application. 15. The system of claim 11 , wherein the context data includes a location associated with the calendar event. | 0.936183 |
8,244,721 | 8 | 9 | 8. The system of claim 1 , the shared web task engine implements a group query expansion that expands the portion of the text query based on evaluating a text query from the group, the expansion of the text query is dependent upon having a relationship there between in which the relationship includes at least one of a semantic content, a time span of entry, or a manual inference. | 8. The system of claim 1 , the shared web task engine implements a group query expansion that expands the portion of the text query based on evaluating a text query from the group, the expansion of the text query is dependent upon having a relationship there between in which the relationship includes at least one of a semantic content, a time span of entry, or a manual inference. 9. The system of claim 8 , the text query from the group is identified from a task session manually defined in at least one of the shared web task engine or the collaborative web search. | 0.935729 |
8,140,321 | 15 | 18 | 15. A device comprising: a memory to store instructions; a coherence processor to execute one or more of the instructions to calculate a coherence of multiple terms in a sequence of terms, where the coherence processor calculates the coherence of the multiple terms in the sequence relative to a first collection of documents in which the sequence occurs; a variation processor to execute one or more of the instructions to calculate a variation of context terms in a second collection of documents that differs from the first collection of documents, where the variation processor calculates the variation of the context terms based on entropy of the context terms within the second collection of documents; a heuristics processor to execute one or more of the instructions to apply one or more predefined rules to the sequence, where the one or more predefined rules relate to defining sequence of characters as semantic units, and a decision processor to execute one or more of the instructions to determine that the sequence constitutes a semantic unit based on the coherence of the multiple terms in the sequence, the variation of the context terms, and further based, at least in part, on application of the one or more predefined rules to the sequence. | 15. A device comprising: a memory to store instructions; a coherence processor to execute one or more of the instructions to calculate a coherence of multiple terms in a sequence of terms, where the coherence processor calculates the coherence of the multiple terms in the sequence relative to a first collection of documents in which the sequence occurs; a variation processor to execute one or more of the instructions to calculate a variation of context terms in a second collection of documents that differs from the first collection of documents, where the variation processor calculates the variation of the context terms based on entropy of the context terms within the second collection of documents; a heuristics processor to execute one or more of the instructions to apply one or more predefined rules to the sequence, where the one or more predefined rules relate to defining sequence of characters as semantic units, and a decision processor to execute one or more of the instructions to determine that the sequence constitutes a semantic unit based on the coherence of the multiple terms in the sequence, the variation of the context terms, and further based, at least in part, on application of the one or more predefined rules to the sequence. 18. The device of claim 15 , where the entropy, H(S), is calculated as
H ( S )=MIN( HL ( S ), HR ( S )), where HL ( S ) = - ∑ w f ( wS ) f ( S ) · log ( f ( wS ) f ( S ) ) , and HR ( S ) = - ∑ w f ( Sw ) f ( S ) · log ( f ( Sw ) f ( S ) ) , and where MIN defines a minimum operation, S represents the sequence, HL(S) is entropy left of the sequence, HR(S) is entropy right of the sequence, f(wS) defines a number of times that a particular term, w, appears in the second collection of documents followed by the sequence, f(Sw) refers to a number of times that the sequence is followed by w in the second collection of documents, and f(S) refers to a number of times that the sequence S is present in the second collection of documents. | 0.500649 |
7,485,788 | 4 | 6 | 4. The combination chimes and message bars of claim 1 , wherein said plurality of chimes are suspended by chime lines in a circular pattern from said main support member with said a single striker suspended vertically by a striker line from said main support member within an inner boundary of said chimes. | 4. The combination chimes and message bars of claim 1 , wherein said plurality of chimes are suspended by chime lines in a circular pattern from said main support member with said a single striker suspended vertically by a striker line from said main support member within an inner boundary of said chimes. 6. The combination chimes and message bars of claim 4 , wherein said plurality of message bars are suspended by message lines so that said message bars are spaced apart in a circular pattern to the interior of said circular arrangement of said chimes. | 0.865919 |
8,060,359 | 1 | 13 | 1. A machine translation apparatus comprising: a central processing unit; an identification information detection unit that detects, from a designated physical object or an attachment thereto, identification information of the designated object; a receiving unit that receives a source language sentence; a word dividing unit that divides the source language sentence into a plurality of first words by morphological analysis; a deixis detection unit that detects, from the first words, a deixis indicating the designated object; a correspondence setting unit that sets a correspondence between the identification information of the designated object and the deixis; a semantic class determining unit executing on the central processing unit that determines a semantic class indicating a semantic attribute of the designated object previously associated with the identification information of the designated object; and a translation unit that translates the source language sentence according to the determined semantic class of the designated object corresponding to the deixis. | 1. A machine translation apparatus comprising: a central processing unit; an identification information detection unit that detects, from a designated physical object or an attachment thereto, identification information of the designated object; a receiving unit that receives a source language sentence; a word dividing unit that divides the source language sentence into a plurality of first words by morphological analysis; a deixis detection unit that detects, from the first words, a deixis indicating the designated object; a correspondence setting unit that sets a correspondence between the identification information of the designated object and the deixis; a semantic class determining unit executing on the central processing unit that determines a semantic class indicating a semantic attribute of the designated object previously associated with the identification information of the designated object; and a translation unit that translates the source language sentence according to the determined semantic class of the designated object corresponding to the deixis. 13. The machine translation apparatus according to claim 1 , wherein the identification information detection unit includes an image pickup unit that picks-up an image of the designated object; and an image recognition unit that analyzes the image picked up and acquiring the identification information including the semantic class of the designated object. | 0.79388 |
9,460,195 | 1 | 2 | 1. A computer-implemented method for determining term importance in a text content for information discovery and presentation, comprising: receiving a text content; tokenizing the text content into a plurality of terms, each term comprising one or more words or phrases; identifying a first term in the text content, wherein the first term is or is contained in a grammatical subject of a sentence; identifying a second term in the text content, wherein the second term is or is contained in a non-subject portion of a sentence; using, by a computer, a pre-defined criterion for determining whether the first term is of greater importance than the second term, or whether the second term is of greater importance than the first term; associating a first importance measure to the first term based on the pre-defined criterion; associating a second importance measure to the second term based on the pre-defined criterion; further determining the first importance measure based on a comparison between a frequency of the first term inside the text content and a frequency of the first term obtained from a document external to the text content, or further determining the second importance measure based on a comparison between a frequency of the second term inside the text content and a frequency of the second term obtained from a document external to the text content; selecting the first term in preference over the second term if the first importance measure is greater than the second importance measure, or selecting the second term in preference over the first term if the second importance measure is greater than the first importance measure; performing an action associated with the selected term, wherein the action comprises at least outputting an element associated with the selected term, displaying an element associated with the selected term, or using an element associated with the selected term for a computer-assisted operation associated with the text content including ranking a search result, wherein the element is selected from the group consisting of at least the selected term, the first importance measure or the second importance measure, and a sentence or paragraph containing the selected term. | 1. A computer-implemented method for determining term importance in a text content for information discovery and presentation, comprising: receiving a text content; tokenizing the text content into a plurality of terms, each term comprising one or more words or phrases; identifying a first term in the text content, wherein the first term is or is contained in a grammatical subject of a sentence; identifying a second term in the text content, wherein the second term is or is contained in a non-subject portion of a sentence; using, by a computer, a pre-defined criterion for determining whether the first term is of greater importance than the second term, or whether the second term is of greater importance than the first term; associating a first importance measure to the first term based on the pre-defined criterion; associating a second importance measure to the second term based on the pre-defined criterion; further determining the first importance measure based on a comparison between a frequency of the first term inside the text content and a frequency of the first term obtained from a document external to the text content, or further determining the second importance measure based on a comparison between a frequency of the second term inside the text content and a frequency of the second term obtained from a document external to the text content; selecting the first term in preference over the second term if the first importance measure is greater than the second importance measure, or selecting the second term in preference over the first term if the second importance measure is greater than the first importance measure; performing an action associated with the selected term, wherein the action comprises at least outputting an element associated with the selected term, displaying an element associated with the selected term, or using an element associated with the selected term for a computer-assisted operation associated with the text content including ranking a search result, wherein the element is selected from the group consisting of at least the selected term, the first importance measure or the second importance measure, and a sentence or paragraph containing the selected term. 2. The method of claim 1 , wherein the first term is determined to be of greater importance than the second term, and the first importance measure is greater than the second importance measure. | 0.847551 |
8,473,295 | 1 | 2 | 1. A method comprising: receiving a command to correct a displayed word in a displayed text; highlighting the displayed word to be corrected in the displayed text; displaying a first list of alternatives for the displayed word while continuing to highlight the displayed word to be corrected in the displayed text, each alternative having an associated number; receiving a speech signal consisting of a pronunciation of a word that is not in the first list of alternatives and is not a number while displaying the first list of alternatives for the displayed word; decoding the speech signal received while displaying the first list of alternatives for the displayed word to produce a decoded word and a second list of alternative words while displaying the first list of alternatives for the displayed word; a processor determines that the decoded word is not a number; because the decoded word is not a number, displaying the decoded word and the second list of alternative words to the user while continuing to highlight the displayed word to be corrected in the displayed text, the decoded word and each word in the second list of alternative words each displayed word having an associated number; receiving a second speech signal; decoding the second speech signal to identify a second decoded word and a third list of alternative words; the processor determines that the second decoded word is a number associated with a word in the second list of alternative words, where the word associated with the number was not present in the first list of alternative words; and replacing the highlighted word to be corrected in the displayed text with the word associated with the number indicated by the second decoded word. | 1. A method comprising: receiving a command to correct a displayed word in a displayed text; highlighting the displayed word to be corrected in the displayed text; displaying a first list of alternatives for the displayed word while continuing to highlight the displayed word to be corrected in the displayed text, each alternative having an associated number; receiving a speech signal consisting of a pronunciation of a word that is not in the first list of alternatives and is not a number while displaying the first list of alternatives for the displayed word; decoding the speech signal received while displaying the first list of alternatives for the displayed word to produce a decoded word and a second list of alternative words while displaying the first list of alternatives for the displayed word; a processor determines that the decoded word is not a number; because the decoded word is not a number, displaying the decoded word and the second list of alternative words to the user while continuing to highlight the displayed word to be corrected in the displayed text, the decoded word and each word in the second list of alternative words each displayed word having an associated number; receiving a second speech signal; decoding the second speech signal to identify a second decoded word and a third list of alternative words; the processor determines that the second decoded word is a number associated with a word in the second list of alternative words, where the word associated with the number was not present in the first list of alternative words; and replacing the highlighted word to be corrected in the displayed text with the word associated with the number indicated by the second decoded word. 2. The method of claim 1 further comprising: before receiving the command to correct a word, decoding an initial speech signal to identify the word and at least one word in the list of alternatives. | 0.850679 |
9,495,331 | 8 | 19 | 8. A method for conducting a dialog with a user of at least one computerized enterprise system, the method comprising: using at least one ontological entity to define user dialog topics including items; conducting a dialog with a user of at least one computerized enterprise system about an individual topic from among said user dialog topics, including generating a directed graph based on item references, from links between said items, by applying closure-based variable scoping in conjunction with backward-chaining-based logic to said directed graph; and identifying and scoring potential discussion forks based on said directed graph. | 8. A method for conducting a dialog with a user of at least one computerized enterprise system, the method comprising: using at least one ontological entity to define user dialog topics including items; conducting a dialog with a user of at least one computerized enterprise system about an individual topic from among said user dialog topics, including generating a directed graph based on item references, from links between said items, by applying closure-based variable scoping in conjunction with backward-chaining-based logic to said directed graph; and identifying and scoring potential discussion forks based on said directed graph. 19. A method according to claim 8 wherein at least one parameter comprises at least one ItemReference including a reference to at least one other item (referenced item) to be used as an input for a block. | 0.854494 |
7,613,693 | 6 | 8 | 6. A computer-implemented system, comprising: an indexing engine that creates an index of source code files, the index incorporating one or more tags and, for each tag, a name of a respective source code file in which the tag is defined, a path to the respective source code file relative to a root directory, and a representation of an include-tree of the respective source code file, where the include-tree is a sequence of files that are included by or imported by the respective source code file; an interface to receive a search query and a current context, where the current context is a file being edited, the current context is in a directory in a path relative to the root directory, and the current context has an associated include-tree; and a ranking engine that ranks a plurality of source code files that each define a tag that satisfies the search query, where the plurality of source code files includes a plurality of source code files that are in the include-tree of the current context and at least one file that is not in the include-tree of the current context, where the ranking includes applying multiple levels of sorting, including a first level of sorting where all source code files that are in the include-tree of the current context are ranked higher than all source code files that are not in the include-tree of the current context, and a second level of sorting where all source code files in the include-tree of the current context are ranked by the relative directory distance from the current context to each source code file. | 6. A computer-implemented system, comprising: an indexing engine that creates an index of source code files, the index incorporating one or more tags and, for each tag, a name of a respective source code file in which the tag is defined, a path to the respective source code file relative to a root directory, and a representation of an include-tree of the respective source code file, where the include-tree is a sequence of files that are included by or imported by the respective source code file; an interface to receive a search query and a current context, where the current context is a file being edited, the current context is in a directory in a path relative to the root directory, and the current context has an associated include-tree; and a ranking engine that ranks a plurality of source code files that each define a tag that satisfies the search query, where the plurality of source code files includes a plurality of source code files that are in the include-tree of the current context and at least one file that is not in the include-tree of the current context, where the ranking includes applying multiple levels of sorting, including a first level of sorting where all source code files that are in the include-tree of the current context are ranked higher than all source code files that are not in the include-tree of the current context, and a second level of sorting where all source code files in the include-tree of the current context are ranked by the relative directory distance from the current context to each source code file. 8. The system of claim 6 , wherein the indexing engine creates the index of source code files by performing operations further comprising: receiving one or more s-expression formatted TAGS file, each TAGS file corresponding to one or more source code files and containing, for each source code file, a name of the source code file, a path to the source code file, a language of the source code file, one or more tags defined in the source code file, a location of each tag defined within the source code file, and an item descriptor of each tag defined within the source code file; storing the one or more TAGS files in a data store; and using the one or more TAGS files to create the index of source code files. | 0.707718 |
8,311,330 | 12 | 19 | 12. An apparatus for determining segments in a document, comprising: a parser operative to create a document model based on the document when the document is in a common representation format that supports discovery of internal structure of the document; and a structure analyzer, in communication with the parser, operative to determine a plurality of segments based on at least one structure-dependent function applied to the document model. | 12. An apparatus for determining segments in a document, comprising: a parser operative to create a document model based on the document when the document is in a common representation format that supports discovery of internal structure of the document; and a structure analyzer, in communication with the parser, operative to determine a plurality of segments based on at least one structure-dependent function applied to the document model. 19. The apparatus of claim 12 , the analyzer further comprising: a cluster identification component operative to identify a plurality of document clusters based on properties of a plurality of additional documents within a document repository in which the document is stored; a cluster comparator component, in communication with the cluster identification component, operative to identify a best-match document cluster of the plurality of document clusters for the document; a segment size threshold determination component, in communication with the cluster comparator component, for determining a segment size threshold for previously identified segments in those additional documents in the best-match document cluster; and a segment extraction component, in communication with the segment size threshold determination component, operative to identify the plurality of segments based on the average segment size threshold. | 0.605286 |
8,527,269 | 3 | 9 | 3. A computer implemented method for analyzing conversational data, the method comprising: receiving first conversational data that is produced by an entity; identifying a first set of lexical features from the first conversational data; reducing, by a computer, the first set of lexical features to generate a first language map; and storing the first language map into a corpus of language maps in association with the entity, the corpus comprising a plurality of language maps that are associated with different entities. | 3. A computer implemented method for analyzing conversational data, the method comprising: receiving first conversational data that is produced by an entity; identifying a first set of lexical features from the first conversational data; reducing, by a computer, the first set of lexical features to generate a first language map; and storing the first language map into a corpus of language maps in association with the entity, the corpus comprising a plurality of language maps that are associated with different entities. 9. The method of claim 3 , wherein reducing the first set of lexical features to generate a first language map comprises reducing the first set of lexical features based on overlaps between lexical features in the first set and lexical features in the corpus. | 0.883228 |
8,250,001 | 1 | 9 | 1. A method of dynamically adapting a sensitivity of at least one user interface component on an electronic device, comprising: identifying a device context corresponding to the electronic device; processing the device context in real time to identify a potential user intent and to determine a probability that the potential user intent corresponds to an actual user intent; selecting a user input sensitivity parameter based on the potential user intent and the determined probability; and adapting the sensitivity of the at least one user interface component to correspond to the user input sensitivity parameter. | 1. A method of dynamically adapting a sensitivity of at least one user interface component on an electronic device, comprising: identifying a device context corresponding to the electronic device; processing the device context in real time to identify a potential user intent and to determine a probability that the potential user intent corresponds to an actual user intent; selecting a user input sensitivity parameter based on the potential user intent and the determined probability; and adapting the sensitivity of the at least one user interface component to correspond to the user input sensitivity parameter. 9. The method of claim 1 , further comprising: selecting a haptic response parameter based on the potential user intent and the determined probability; and communicating the haptic response parameter to the user interface to indicate to the user interface to generate a haptic response via the at least one user interface component. | 0.732689 |
9,699,472 | 16 | 17 | 16. The device of claim 14 , wherein the one or more processors are configured to determine that the PU is restricted to uni-directional inter prediction if a height or a width of a video block associated with the PU is below a threshold. | 16. The device of claim 14 , wherein the one or more processors are configured to determine that the PU is restricted to uni-directional inter prediction if a height or a width of a video block associated with the PU is below a threshold. 17. The device of claim 16 , wherein the threshold is 8. | 0.975799 |
8,352,333 | 5 | 6 | 5. The method of claim 1 , further comprising notifying a user that an update has taken place of the self-updating naturally-reading narrative product summary. | 5. The method of claim 1 , further comprising notifying a user that an update has taken place of the self-updating naturally-reading narrative product summary. 6. The method of claim 5 , wherein the user is notified by email or RSS feed that an update has taken place of the self-updating naturally-reading narrative product summary. | 0.947923 |
9,741,347 | 17 | 19 | 17. A non-transitory computer-readable storage medium storing executable computer program code for processing an interaction, the interaction including an utterance requiring recognition before being usable for further computer-implemented processing, the computer program code comprising instructions for: receiving data representing an utterance from a device of a customer over a computer network; identifying a grammar to which the utterance is expected to conform; determining a time length of the utterance; dynamically selecting, based at least in part on the identified grammar and the time length of the utterance, one or more recognizers from a set of recognizers including: an automated speech recognizer (ASR), and a second type of recognizer, different from the automated speech recognizer, and communicating over a computer network with devices located at locations remote from the computer system; and providing a recognition result responsive to results of processing by the one or more recognizers. | 17. A non-transitory computer-readable storage medium storing executable computer program code for processing an interaction, the interaction including an utterance requiring recognition before being usable for further computer-implemented processing, the computer program code comprising instructions for: receiving data representing an utterance from a device of a customer over a computer network; identifying a grammar to which the utterance is expected to conform; determining a time length of the utterance; dynamically selecting, based at least in part on the identified grammar and the time length of the utterance, one or more recognizers from a set of recognizers including: an automated speech recognizer (ASR), and a second type of recognizer, different from the automated speech recognizer, and communicating over a computer network with devices located at locations remote from the computer system; and providing a recognition result responsive to results of processing by the one or more recognizers. 19. The non-transitory computer-readable storage medium of claim 17 , wherein said dynamically selecting is responsive to a confidence metric. | 0.864245 |
4,783,811 | 12 | 13 | 12. The method of claim 7 and further comprising: representing said bytes using predetermined symbols; storing a set of special symbols each representing more than one of the symbols used in representing said bytes; and transforming said ones of said segments in accordance with said stored set of rules and said set of special symbols. | 12. The method of claim 7 and further comprising: representing said bytes using predetermined symbols; storing a set of special symbols each representing more than one of the symbols used in representing said bytes; and transforming said ones of said segments in accordance with said stored set of rules and said set of special symbols. 13. The method of claim 12 wherein at least one of said special symbols points to a list of selected ones of said predetermined symbols, such that a byte matching any of the selected ones of said predetermined symbols will match said at least one special symbol. | 0.911066 |
7,630,552 | 1 | 32 | 1. A method of assessing a document using a computer system, comprising: providing a document to the computer system, wherein the document comprises at least one information field; and for at least one non-signature information field of the document, comparing, using the computer system, handwriting in the non-signature information field to at least two handwriting profile representations from at least one non-signature information field of at least one other document, wherein writing in at least one of the information fields of the document comprises at least two examples of a type of handwritten information, and further comprising comparing at least two of the examples to assess whether two or more of the examples approximately match. | 1. A method of assessing a document using a computer system, comprising: providing a document to the computer system, wherein the document comprises at least one information field; and for at least one non-signature information field of the document, comparing, using the computer system, handwriting in the non-signature information field to at least two handwriting profile representations from at least one non-signature information field of at least one other document, wherein writing in at least one of the information fields of the document comprises at least two examples of a type of handwritten information, and further comprising comparing at least two of the examples to assess whether two or more of the examples approximately match. 32. The method of claim 1 , wherein at least one handwriting profile representation comprises at least one local characteristic of the writing. | 0.893284 |
7,801,887 | 33 | 34 | 33. A computer-readable medium according to claim 31 further comprising a ninth data field for adding vocabulary words to the vocabulary based upon occurrences of words in at least some of the retrieved documents. | 33. A computer-readable medium according to claim 31 further comprising a ninth data field for adding vocabulary words to the vocabulary based upon occurrences of words in at least some of the retrieved documents. 34. A computer-readable medium according to claim 33 further comprising a tenth data field for determining a quality of the vocabulary based upon how many vocabulary words are added thereto. | 0.934074 |
9,928,836 | 12 | 13 | 12. A system comprising: a speech-to-text engine implemented at least partially in hardware of a computing device to receive a natural language input indicative of an operation to be performed and to convert the natural language input into text; and a natural language processing module implemented at least partially in hardware of the computing device to: parse the text into at least one part-of-speech; locate at least one grammar template of a plurality of grammar templates that correspond to the at least one part-of-speech by matching the part-of-speech against a sentence expression defined by each of the plurality of grammar templates, the at least one grammar template selected based on a scoring mechanism; detect an arbitrary term in the at least one part-of-speech based on the located grammar template; identify a known operational term in the at least one part-of-speech, the known operational term corresponding to the operation to be performed; determine a term that is related to the arbitrary term based on matching the sentence expression of the at least one grammar template against the known operational term, the term describing a modification for the operation to be performed and selected from a set of base terms corresponding to the known operational term; and initiate performance of the operation as including the modification described by the term. | 12. A system comprising: a speech-to-text engine implemented at least partially in hardware of a computing device to receive a natural language input indicative of an operation to be performed and to convert the natural language input into text; and a natural language processing module implemented at least partially in hardware of the computing device to: parse the text into at least one part-of-speech; locate at least one grammar template of a plurality of grammar templates that correspond to the at least one part-of-speech by matching the part-of-speech against a sentence expression defined by each of the plurality of grammar templates, the at least one grammar template selected based on a scoring mechanism; detect an arbitrary term in the at least one part-of-speech based on the located grammar template; identify a known operational term in the at least one part-of-speech, the known operational term corresponding to the operation to be performed; determine a term that is related to the arbitrary term based on matching the sentence expression of the at least one grammar template against the known operational term, the term describing a modification for the operation to be performed and selected from a set of base terms corresponding to the known operational term; and initiate performance of the operation as including the modification described by the term. 13. The system as described in claim 12 , wherein the determination of the term includes producing a measure of closeness using a term distance formula between the arbitrary term and a respective base terms from the set of base terms. | 0.502128 |
7,840,549 | 13 | 18 | 13. A system, comprising: hardware logic performing operations, the operations comprising: receiving a search request including one or more search terms; capturing each of the one or more search terms; providing a list of topics to a user as search results; receiving user selection of a topic in the list of topics, wherein the user adds one or more folksonomy tags to the topic after reviewing the topic; capturing the one or more folksonomy tags added by the user to the topic; and mapping each of the one or more search terms and each of the one or more folksonomy tags to the topic; for each of the search terms: counting a first number of times the search term has been used for both searching and adding folksonomy tags to the topic; and based on the first number of times, adding the search term to retrievability aids by adding the search term to metadata for the topic, to an index, to a controlled vocabulary, and to a taxonomy , and wherein the adding is based on a search term threshold; and for each of the one or more folksonomy tags: counting a second number of times the folksonomy tag has been added to the topic; and based on the second number of times, adding the folksonomy tag to retrievability aids by adding the folksonomy tag to the metadata for the topic, to the index, to the controlled vocabulary, and to the taxonomy , and wherein the adding is based on a folksonomy tag threshold. | 13. A system, comprising: hardware logic performing operations, the operations comprising: receiving a search request including one or more search terms; capturing each of the one or more search terms; providing a list of topics to a user as search results; receiving user selection of a topic in the list of topics, wherein the user adds one or more folksonomy tags to the topic after reviewing the topic; capturing the one or more folksonomy tags added by the user to the topic; and mapping each of the one or more search terms and each of the one or more folksonomy tags to the topic; for each of the search terms: counting a first number of times the search term has been used for both searching and adding folksonomy tags to the topic; and based on the first number of times, adding the search term to retrievability aids by adding the search term to metadata for the topic, to an index, to a controlled vocabulary, and to a taxonomy , and wherein the adding is based on a search term threshold; and for each of the one or more folksonomy tags: counting a second number of times the folksonomy tag has been added to the topic; and based on the second number of times, adding the folksonomy tag to retrievability aids by adding the folksonomy tag to the metadata for the topic, to the index, to the controlled vocabulary, and to the taxonomy , and wherein the adding is based on a folksonomy tag threshold. 18. The system of claim 13 , wherein mapping comprises associating each of the one or more search terms and the one or more folksonomy tags with the topic that was selected. | 0.85339 |
9,978,365 | 5 | 8 | 5. The method of claim 1 , wherein the first analysis includes natural language processing of the voice input. | 5. The method of claim 1 , wherein the first analysis includes natural language processing of the voice input. 8. The method of claim 5 , wherein the natural language processing includes resolving a meaning of ambiguous words in the voice input by determining which of a plurality of meanings is more likely based on usage statistics associated with a user of the user terminal that receives the voice input. | 0.888346 |
8,819,021 | 4 | 7 | 4. A method comprising: inputting a user specified criterion which correlates to high relevance; preparing a data set for processing; de-duplicating the data set; extracting the data set; determining, prior to indexing the data set, where to prioritize the data set in a processing queue by evaluating how well the data set matches the user specified criterion relative to other data sets that have been processed based on inputs received from users relating to their review of the already processed other electronic data sets; having a user do a complete or sample assessment of initially processed data sets that outranks the initial user specified criterion in the event of conflict; permitting a user to override prioritization of specific data sets or its schemes for determining prioritization; indexing the data set; and iteratively repeating the process based on user feedback and the desired quality and quantity of relevant data until all data sets have been exhausted. | 4. A method comprising: inputting a user specified criterion which correlates to high relevance; preparing a data set for processing; de-duplicating the data set; extracting the data set; determining, prior to indexing the data set, where to prioritize the data set in a processing queue by evaluating how well the data set matches the user specified criterion relative to other data sets that have been processed based on inputs received from users relating to their review of the already processed other electronic data sets; having a user do a complete or sample assessment of initially processed data sets that outranks the initial user specified criterion in the event of conflict; permitting a user to override prioritization of specific data sets or its schemes for determining prioritization; indexing the data set; and iteratively repeating the process based on user feedback and the desired quality and quantity of relevant data until all data sets have been exhausted. 7. The method of claim 4 , wherein having a user do a complete or sample assessment of initially processed data sets that outranks the initial user specified criterion in the event of conflict is generalized into a model, further wherein the model is selected from a group consisting of: multidimensional modeling, closed item set-based calculations, clustering, support vector analysis, and other kinds of statistical analysis. | 0.586074 |
7,558,408 | 27 | 34 | 27. One or more processor-readable digital data storage media having programming instructions embedded therein for programming a processor to classify images including face regions that are acquired with an image acquisition device, the programming instructions comprising: a workflow module providing for the automatic or semiautomatic processing of identified face regions within digital images from which normalized face classifier parameter values are extracted and collectively referred to as a faceprint, the processing comprising: comparing said extracted faceprint to a database of archived faceprints previously determined to correspond to one or more known identities, determining based on the comparing whether a new faceprint corresponds to any of the one or more known identities, and associating the new faceprint and a normalized face region from which said faceprint is derived with a new or known identity within a database comprising other data corresponding to the archived faceprints and associated parent images for performing further comparisons with further faceprints, to permit data corresponding to the new faceprint and its associated parent image to be archived according to the associating by the workflow module within one or more digital data storage media; and a set of user interface modules for obtaining user input in the classifying of faceprints and their associated normalized face regions and parent images; and wherein one or more archived faceprints have been previously determined to correspond to the one or more known identities, and the comparing by the workflow module comprises determining proximities of the values of the face classifier parameters of the new face print image with values corresponding to the one or more archived faceprints, and wherein the determining by the workflow module comprises a further confirmation to determine whether the new faceprint corresponds to a known identity when comparisons of the face classifier parameter values of a first faceprint with multiple archived faceprints corresponding to a same known identity result in at least one determination of an identity match and at least one determination that the identities do not match. | 27. One or more processor-readable digital data storage media having programming instructions embedded therein for programming a processor to classify images including face regions that are acquired with an image acquisition device, the programming instructions comprising: a workflow module providing for the automatic or semiautomatic processing of identified face regions within digital images from which normalized face classifier parameter values are extracted and collectively referred to as a faceprint, the processing comprising: comparing said extracted faceprint to a database of archived faceprints previously determined to correspond to one or more known identities, determining based on the comparing whether a new faceprint corresponds to any of the one or more known identities, and associating the new faceprint and a normalized face region from which said faceprint is derived with a new or known identity within a database comprising other data corresponding to the archived faceprints and associated parent images for performing further comparisons with further faceprints, to permit data corresponding to the new faceprint and its associated parent image to be archived according to the associating by the workflow module within one or more digital data storage media; and a set of user interface modules for obtaining user input in the classifying of faceprints and their associated normalized face regions and parent images; and wherein one or more archived faceprints have been previously determined to correspond to the one or more known identities, and the comparing by the workflow module comprises determining proximities of the values of the face classifier parameters of the new face print image with values corresponding to the one or more archived faceprints, and wherein the determining by the workflow module comprises a further confirmation to determine whether the new faceprint corresponds to a known identity when comparisons of the face classifier parameter values of a first faceprint with multiple archived faceprints corresponding to a same known identity result in at least one determination of an identity match and at least one determination that the identities do not match. 34. The system of claim 27 , wherein the programming instructions comprise instructions for receiving data management editing from the user regarding statistical thresholds utilized in the comparing. | 0.888453 |
5,481,703 | 9 | 13 | 9. A relational database restructuring system, having at least one relation, each said relation having a plurality of tuples, a set of attributes, a set of candidate keys and a set of non-key attributes, wherein each said tuple is managed as a two-dimensional relation for each said attribute and wherein each said relation has a candidate key serving as a set of attributes which can uniquely identify one of said tuples, comprising: first determination means for checking, with reference to values of tuples which are present in said relations, whether a first set of attributes is functionally dependent on a second set of attributes; division means for dividing a first relation into a second and a third relation by a projecting operation for a designated attribute set; second determination means for determining, from attribute sets A and B which are included in a relation and are mutually primary, whether said attribute sets A and B satisfy at least one of a first condition and a second condition, said first condition being that said attribute set A is a proper subset of said set of candidate keys and said attribute set B is a subset of a non-key attribute set serving as a subset of said set of candidate keys said second condition being that both the attribute sets A and B are proper subsets of said non-key attribute set; and means for checking whether said attribute set B is functionally dependent on said attribute set A once said second determination means has determined that said attribute sets A and B satisfy at least one of said first condition and said second condition, and dividing said relation including said attribute sets A and B, when said attribute set A is functionally dependent on attribute set B, into a relation formed by a projection to a subset of the attribute set B and, a relation formed by a projection to a union between said attribute sets A and B. | 9. A relational database restructuring system, having at least one relation, each said relation having a plurality of tuples, a set of attributes, a set of candidate keys and a set of non-key attributes, wherein each said tuple is managed as a two-dimensional relation for each said attribute and wherein each said relation has a candidate key serving as a set of attributes which can uniquely identify one of said tuples, comprising: first determination means for checking, with reference to values of tuples which are present in said relations, whether a first set of attributes is functionally dependent on a second set of attributes; division means for dividing a first relation into a second and a third relation by a projecting operation for a designated attribute set; second determination means for determining, from attribute sets A and B which are included in a relation and are mutually primary, whether said attribute sets A and B satisfy at least one of a first condition and a second condition, said first condition being that said attribute set A is a proper subset of said set of candidate keys and said attribute set B is a subset of a non-key attribute set serving as a subset of said set of candidate keys said second condition being that both the attribute sets A and B are proper subsets of said non-key attribute set; and means for checking whether said attribute set B is functionally dependent on said attribute set A once said second determination means has determined that said attribute sets A and B satisfy at least one of said first condition and said second condition, and dividing said relation including said attribute sets A and B, when said attribute set A is functionally dependent on attribute set B, into a relation formed by a projection to a subset of the attribute set B and, a relation formed by a projection to a union between said attribute sets A and B. 13. A system according to claim 9, wherein said division means has means for informing an operator of a result determined by said first determination means, inputting an enable/disable a division instruction from said operator, and controlling division processing in accordance with said instruction. | 0.745331 |
5,426,653 | 7 | 10 | 7. A radio communication device for receiving a radiofrequency (RF) signal comprising at least first, second, and third words of at least first, second, and third duplicate messages, respectively, wherein each word including message information and error correction information, and wherein the second and third words are redundant words associated with the first word, the radio communication device comprising: comparing means for comparing each corresponding bit of the first, second and third words to determine, for each corresponding bit, which of first and second bit values is a majority bit value; generating means coupled to the comparing means for generating a fourth word which includes a bit for each corresponding bit included in the first, second, and third words, wherein each bit of the fourth word has a value equivalent to the majority bit value corresponding thereto; error correction circuitry coupled to the generating means for performing error correction on each of the first, second, third, and fourth words utilizing the error correction information: determining mean for determining a number of corrected words include in the first, second, third, and fourth words; and choosing means for selecting message information included in one of the first, second, third and fourth words, said choosing means selecting, if said determining means determines that one word has been corrected by the correcting means, the message information contained in said one corrected word. | 7. A radio communication device for receiving a radiofrequency (RF) signal comprising at least first, second, and third words of at least first, second, and third duplicate messages, respectively, wherein each word including message information and error correction information, and wherein the second and third words are redundant words associated with the first word, the radio communication device comprising: comparing means for comparing each corresponding bit of the first, second and third words to determine, for each corresponding bit, which of first and second bit values is a majority bit value; generating means coupled to the comparing means for generating a fourth word which includes a bit for each corresponding bit included in the first, second, and third words, wherein each bit of the fourth word has a value equivalent to the majority bit value corresponding thereto; error correction circuitry coupled to the generating means for performing error correction on each of the first, second, third, and fourth words utilizing the error correction information: determining mean for determining a number of corrected words include in the first, second, third, and fourth words; and choosing means for selecting message information included in one of the first, second, third and fourth words, said choosing means selecting, if said determining means determines that one word has been corrected by the correcting means, the message information contained in said one corrected word. 10. The radio communication device according to claim 7, further comprising: an alert mechanism for generating an alert; and a controller coupled to the alert mechanism and the selection means for activating the alert mechanism in response to the selection means selecting the message information included in the one of the first, second, third, and fourth words. | 0.865754 |
7,966,327 | 2 | 8 | 2. A method of searching a plurality of stored objects according to claim 1 , wherein said step of finding objects comprises the steps of: defining a similarity distance between said objects using a weighted distance function based upon said collection of sketches; and finding objects closest to a query object based upon said weighted distance function. | 2. A method of searching a plurality of stored objects according to claim 1 , wherein said step of finding objects comprises the steps of: defining a similarity distance between said objects using a weighted distance function based upon said collection of sketches; and finding objects closest to a query object based upon said weighted distance function. 8. A method of searching a plurality of stored objects in accordance with claim 2 , wherein the step of generating a collection of multi-dimensional vectors comprises the steps of: segmenting each object into a plurality of segments; and performing feature extraction on said plurality of segments corresponding to each object to produce said collection of multi-dimensional vectors. | 0.810584 |
8,103,506 | 1 | 4 | 1. A non-transitory computer-readable medium comprising computer-readable instructions for correlating a free text expression of an identity to at least one known identity having a plurality of expressions in a database, said computer-readable instructions comprising instructions that: allow an input of a plurality of expressions associated with an input identity; electronically convert the plurality of expressions to phonetic equivalent codes; compare the phonetic equivalent codes to determine correlations between the codes; correlate at least one of the plurality of expressions with the known identity based on the phonetic equivalent code associated with the at least one expression having a threshold correlation to a phonetic equivalent code associated with the known identity; electronically provide the known identity using the at least one expression having a threshold correlation to a phonetic equivalent code associated with the known identity; allow an input of a verification that the electronically-provided known identity matches a desired identity intended at a time of the input of the plurality of expressions associated with the input identity; and eliminate from the database another of the plurality of expressions having a threshold correlation to the phonetic equivalent code for the known identity. | 1. A non-transitory computer-readable medium comprising computer-readable instructions for correlating a free text expression of an identity to at least one known identity having a plurality of expressions in a database, said computer-readable instructions comprising instructions that: allow an input of a plurality of expressions associated with an input identity; electronically convert the plurality of expressions to phonetic equivalent codes; compare the phonetic equivalent codes to determine correlations between the codes; correlate at least one of the plurality of expressions with the known identity based on the phonetic equivalent code associated with the at least one expression having a threshold correlation to a phonetic equivalent code associated with the known identity; electronically provide the known identity using the at least one expression having a threshold correlation to a phonetic equivalent code associated with the known identity; allow an input of a verification that the electronically-provided known identity matches a desired identity intended at a time of the input of the plurality of expressions associated with the input identity; and eliminate from the database another of the plurality of expressions having a threshold correlation to the phonetic equivalent code for the known identity. 4. The non-transitory computer-readable medium of claim 1 , further comprising instructions that: obtain a plurality of known identities; and convert the known identities to a plurality of phonetic equivalent codes; wherein the instructions that electronically provide the known identity comprises instructions that provide at least one known identity using a threshold correlation between a phonetic equivalent code associated with the input identity and a phonetic equivalent code associated with the known identity. | 0.528233 |
8,200,657 | 9 | 10 | 9. A computer readable medium including program instructions implemented by a computer, the program instructions for searching for data in a database, the program instructions implementing steps comprising: receiving a query that is a request for data in the database, wherein the query includes at least one uneven non-Boolean term condition including an OR condition that spans at least two tables of the database, wherein the OR condition includes two predicates; splitting the at least one uneven non-Boolean term condition into a plurality of separate query portions that each provide a Boolean term satisfied by accessing a different particular one of the at least two tables, wherein each predicate is provided to a different one of the separate query portions; executing the separate query portions independently of each other to find at least one data result in each of the at least two tables that satisfies the Boolean term of each separate query portion; identifying at least one bridge table, wherein the at least one bridge table does not satisfy the at least one uneven non-Boolean term condition and has at least one column from each of the at least two tables; and combining the data results from each separate query portion into a final result that satisfies the query, wherein the at least one bridge table is used to join each of the at least two tables to combine the data results. | 9. A computer readable medium including program instructions implemented by a computer, the program instructions for searching for data in a database, the program instructions implementing steps comprising: receiving a query that is a request for data in the database, wherein the query includes at least one uneven non-Boolean term condition including an OR condition that spans at least two tables of the database, wherein the OR condition includes two predicates; splitting the at least one uneven non-Boolean term condition into a plurality of separate query portions that each provide a Boolean term satisfied by accessing a different particular one of the at least two tables, wherein each predicate is provided to a different one of the separate query portions; executing the separate query portions independently of each other to find at least one data result in each of the at least two tables that satisfies the Boolean term of each separate query portion; identifying at least one bridge table, wherein the at least one bridge table does not satisfy the at least one uneven non-Boolean term condition and has at least one column from each of the at least two tables; and combining the data results from each separate query portion into a final result that satisfies the query, wherein the at least one bridge table is used to join each of the at least two tables to combine the data results. 10. The computer readable medium of claim 9 wherein the data results include rows in a table found from the execution of the separate query portions, and wherein rows duplicated between the data results from the separate query portions are removed from one of the data results. | 0.66866 |
8,332,434 | 1 | 7 | 1. A computer-implemented method to map a set of words to a set of ontology terms, the method comprising: determining a starting point for each of a plurality of ontology contexts, each of the starting points including terms matching a set of words, the set of words including a plurality of words; determining a term set corresponding to the set of words in the ontology context of each of the starting points; ranking the starting points and selectively using a predetermined number of the ranked starting points; ranking the term sets determined for all of the starting points; and providing an output of the term sets in a ranked order. | 1. A computer-implemented method to map a set of words to a set of ontology terms, the method comprising: determining a starting point for each of a plurality of ontology contexts, each of the starting points including terms matching a set of words, the set of words including a plurality of words; determining a term set corresponding to the set of words in the ontology context of each of the starting points; ranking the starting points and selectively using a predetermined number of the ranked starting points; ranking the term sets determined for all of the starting points; and providing an output of the term sets in a ranked order. 7. The computer-implemented method of claim 1 , wherein terms of the determined term set corresponding to the set of words in the ontology context of each of the starting points are determined based on a combination of the terms' similarity to the set of words, a strength of the terms' ontology to the starting point; and a global popularity of the terms. | 0.701843 |
7,783,644 | 22 | 24 | 22. A computer-implemented method of determining an importance score for an entity mentioned in a book, comprising: identifying library classification data indicating a classification of the book; determining whether the library classification data mention entities from the book; assigning query-independent importance scores to the entities of an entity type mentioned in the book, wherein the importance scores of entities mentioned in the library classification data are elevated relative to importance scores of entities not mentioned in the library classification data; selecting a subset of the plurality of entities responsive to the entities' importance scores and entity type; and presenting the selected subset of entities to a user. | 22. A computer-implemented method of determining an importance score for an entity mentioned in a book, comprising: identifying library classification data indicating a classification of the book; determining whether the library classification data mention entities from the book; assigning query-independent importance scores to the entities of an entity type mentioned in the book, wherein the importance scores of entities mentioned in the library classification data are elevated relative to importance scores of entities not mentioned in the library classification data; selecting a subset of the plurality of entities responsive to the entities' importance scores and entity type; and presenting the selected subset of entities to a user. 24. The method of claim 22 , wherein assigning query-independent importance scores comprises: determining an optical character recognition (OCR) confidence score for book text related to an entity; and calculating the importance score for the entity responsive at least in part to the OCR confidence score. | 0.922296 |
9,405,375 | 28 | 29 | 28. A non-transitory processor-readable medium comprising processor-readable instructions configured to cause a processor to: record a gesture object in a plurality of data objects over time; determine at least one set of gesture angles using the plurality of recorded data objects, wherein each of the gesture angles in the at least one set of gesture angles comprises an angle measurement between two positions of the gesture object, the two positions recorded in successive data objects of the plurality of recorded data objects, wherein the at least one set of gesture angles further comprises a first subset of gesture angles and a second subset of gesture angles; determine a first histogram representing a frequency of angles based on the first subset of gesture angles and a second histogram representing a frequency of angles based on the second subset of gesture angles; recognize a gesture based on comparing the first histogram and the second histogram to a respective first model histogram and second model histogram, each model histogram representing a frequency of angles of a subdivision of gestures of a gesture model; and modify a behavior of the device in response to the recognizing the gesture. | 28. A non-transitory processor-readable medium comprising processor-readable instructions configured to cause a processor to: record a gesture object in a plurality of data objects over time; determine at least one set of gesture angles using the plurality of recorded data objects, wherein each of the gesture angles in the at least one set of gesture angles comprises an angle measurement between two positions of the gesture object, the two positions recorded in successive data objects of the plurality of recorded data objects, wherein the at least one set of gesture angles further comprises a first subset of gesture angles and a second subset of gesture angles; determine a first histogram representing a frequency of angles based on the first subset of gesture angles and a second histogram representing a frequency of angles based on the second subset of gesture angles; recognize a gesture based on comparing the first histogram and the second histogram to a respective first model histogram and second model histogram, each model histogram representing a frequency of angles of a subdivision of gestures of a gesture model; and modify a behavior of the device in response to the recognizing the gesture. 29. The non-transitory processor-readable medium of claim 28 , wherein the first subset of gesture angles and the second subset of gesture angles are time-ordered; and the instructions are further configured to cause the processor to recognize the gesture including individually comparing the first subset of gesture angles and the second subset of gesture angles to a respective subdivision of the gesture model. | 0.501208 |
7,954,107 | 19 | 21 | 19. A method of integrating an existing web-based application into a service, comprising steps of: providing a meta-model in a computer; conducting service model definition for the existing web-based application according to the meta-model; transforming service model into service packing codes and a model definition document of the service; and deploying the service packing codes to generate a service proxy interface in a runtime environment; a service definition that acts as a root node of the meta-model, has a service name, an input message link name and an output message link name, and contains a number of pages and link elements; a page definition for describing an input message, an out put message, a URL for accessing it and a security and session setting, which contained in the page; an input message definition for defining data structure of the input data, so as to represent the input data of the existing web-based application as the input parameter of the service to be transformed; at least one output message definition for defining data structure of output data; and a page link definition for determining a flow of page transferring, including source page name, destination page name, output message name of the source page and and input message name of the destination, page, so as to enable the execution engine to proceed along the page link, wherein the input message definition and the output message definition further comprises a simple variable type definition and a complex variable type definition, wherein the complex variable type contains the simple variable type or is embedded in another complex variable type. | 19. A method of integrating an existing web-based application into a service, comprising steps of: providing a meta-model in a computer; conducting service model definition for the existing web-based application according to the meta-model; transforming service model into service packing codes and a model definition document of the service; and deploying the service packing codes to generate a service proxy interface in a runtime environment; a service definition that acts as a root node of the meta-model, has a service name, an input message link name and an output message link name, and contains a number of pages and link elements; a page definition for describing an input message, an out put message, a URL for accessing it and a security and session setting, which contained in the page; an input message definition for defining data structure of the input data, so as to represent the input data of the existing web-based application as the input parameter of the service to be transformed; at least one output message definition for defining data structure of output data; and a page link definition for determining a flow of page transferring, including source page name, destination page name, output message name of the source page and and input message name of the destination, page, so as to enable the execution engine to proceed along the page link, wherein the input message definition and the output message definition further comprises a simple variable type definition and a complex variable type definition, wherein the complex variable type contains the simple variable type or is embedded in another complex variable type. 21. The method according to claim 19 , further comprising providing an execution engine for executing the service requested by a user through the service proxy interface according to the service model definition document loaded in runtime. | 0.874343 |
7,497,778 | 1 | 27 | 1. A method of conducting a word based lottery game having a plurality of players, comprising the steps of: for each game, the players wagering on an entry defined by a set of words; in a random draw process, randomly generating an outcome that is a concatenation of characters, the draw being such that each outcome can be assigned a probability of occurrence; defining a rule that confers the words in the player entry a win status based on the outcome of the draw producing characters that are used to form the respective words in the player entry; selecting winning entries based on the words in an entry that are conferred a win status; and assigning a prize for each winning entry as a function of a value assigned to each of the words in the player entry formed by the randomly drawn characters, the value based on the commonality of the characters that form the words in the player entry. | 1. A method of conducting a word based lottery game having a plurality of players, comprising the steps of: for each game, the players wagering on an entry defined by a set of words; in a random draw process, randomly generating an outcome that is a concatenation of characters, the draw being such that each outcome can be assigned a probability of occurrence; defining a rule that confers the words in the player entry a win status based on the outcome of the draw producing characters that are used to form the respective words in the player entry; selecting winning entries based on the words in an entry that are conferred a win status; and assigning a prize for each winning entry as a function of a value assigned to each of the words in the player entry formed by the randomly drawn characters, the value based on the commonality of the characters that form the words in the player entry. 27. The method of claim 1 , further comprising the steps of: entering the outcome of a draw into a database; and correlating entries into the game to determine the prize amounts each entry is entitled to. | 0.554585 |
9,471,064 | 10 | 11 | 10. A non-transitory article of manufacture tangibly embodying computer readable instructions, which when implemented, cause a computer to perform the steps of a method for controlling one or more drones to respond to a request for information, comprising; receiving a natural language request for information about a spatial location; parsing the natural language request into a plurality of data requests; searching for existing sources for the plurality of data requests: determining that there are one or more existing sources for one or more of the plurality of data requests; analyzing the existing sources to obtain first data responsive to the plurality of data requests; determining that there are no existing sources for two or more of the plurality of data requests and identifying the data requests with no existing source as missing data requests; configuring a flight plan for one or more drones over the spatial location based on the plurality of data requests and based on the missing data requests; controlling one or more drones to fly over the spatial location according to the configured flight plan to obtain a plurality of data types from the spatial location based on the plurality of data requests and based on the missing data requests; extracting a plurality of data points responsive to the plurality of data requests from the plurality of data types obtained by the one or more drones; obtaining labels from a user for one or more of the plurality of data points; determining whether there are unlabeled data points; predicting labels for the unlabeled data points from a learning algorithm using the labels obtained from the user; determining the predicted labels are true labels for the unlabeled data points; analyzing the responsive data to provide an answer to the natural language request for information, the analyzing including combining the first data, the user labeled data points and the true labeled data points to provide an answer to the first natural language request for information. | 10. A non-transitory article of manufacture tangibly embodying computer readable instructions, which when implemented, cause a computer to perform the steps of a method for controlling one or more drones to respond to a request for information, comprising; receiving a natural language request for information about a spatial location; parsing the natural language request into a plurality of data requests; searching for existing sources for the plurality of data requests: determining that there are one or more existing sources for one or more of the plurality of data requests; analyzing the existing sources to obtain first data responsive to the plurality of data requests; determining that there are no existing sources for two or more of the plurality of data requests and identifying the data requests with no existing source as missing data requests; configuring a flight plan for one or more drones over the spatial location based on the plurality of data requests and based on the missing data requests; controlling one or more drones to fly over the spatial location according to the configured flight plan to obtain a plurality of data types from the spatial location based on the plurality of data requests and based on the missing data requests; extracting a plurality of data points responsive to the plurality of data requests from the plurality of data types obtained by the one or more drones; obtaining labels from a user for one or more of the plurality of data points; determining whether there are unlabeled data points; predicting labels for the unlabeled data points from a learning algorithm using the labels obtained from the user; determining the predicted labels are true labels for the unlabeled data points; analyzing the responsive data to provide an answer to the natural language request for information, the analyzing including combining the first data, the user labeled data points and the true labeled data points to provide an answer to the first natural language request for information. 11. The non-transitory article of manufacture of claim 10 , wherein controlling the one or more drones comprises one or more of uploading flight plans to the one or more drones, receiving real-time telemetry from the drone and performing analytics on the real-time telemetry to determine real-time flight conditions. | 0.907818 |
8,244,038 | 1 | 4 | 1. A method of detecting dominant points on text characters in a scanned document, comprising: executing an optical character recognition (OCR) algorithm that recognizes a text character in the scanned document; performing a table lookup that identifies one or more dominant point detection rules for detecting the dominant points; applying the one or more identified dominant point detection rules to the text character to detect dominant points on the text character; fitting one or more curves to each text character outline between neighboring dominant points to convert the text character from a bitmap to a vector representation using the detected dominant points; and storing the vectorized text character to memory for use in a vector representation of the scanned document. | 1. A method of detecting dominant points on text characters in a scanned document, comprising: executing an optical character recognition (OCR) algorithm that recognizes a text character in the scanned document; performing a table lookup that identifies one or more dominant point detection rules for detecting the dominant points; applying the one or more identified dominant point detection rules to the text character to detect dominant points on the text character; fitting one or more curves to each text character outline between neighboring dominant points to convert the text character from a bitmap to a vector representation using the detected dominant points; and storing the vectorized text character to memory for use in a vector representation of the scanned document. 4. The method of claim 1 , wherein the dominant point is a maximum or minimum of the text character in a pre-specified direction. | 0.831152 |
10,083,169 | 1 | 4 | 1. A method comprising: receiving a first sequence of words arranged according to a first order, wherein the first sequence of words comprises a plurality of sentences of words, the plurality of sentences being in an input order; for each word in the first sequence of words, beginning with a first word in the first order: determining a topic vector that is associated with the word, generating a combined input from the word and the topic vector, and processing the combined input through one or more sequence modeling layers to generate a respective sequence modeling output for the word; and processing one or more of the respective sequence modeling outputs through an output layer to generate a neural network output for the first sequence of words, wherein, for each word in each sentence after a first sentence in the input order, determining the topic vector that is associated with the word is based, at least in part, on a sequence modeling output for a last word in a sentence immediately before the sentence in the input order. | 1. A method comprising: receiving a first sequence of words arranged according to a first order, wherein the first sequence of words comprises a plurality of sentences of words, the plurality of sentences being in an input order; for each word in the first sequence of words, beginning with a first word in the first order: determining a topic vector that is associated with the word, generating a combined input from the word and the topic vector, and processing the combined input through one or more sequence modeling layers to generate a respective sequence modeling output for the word; and processing one or more of the respective sequence modeling outputs through an output layer to generate a neural network output for the first sequence of words, wherein, for each word in each sentence after a first sentence in the input order, determining the topic vector that is associated with the word is based, at least in part, on a sequence modeling output for a last word in a sentence immediately before the sentence in the input order. 4. The method of claim 1 , wherein processing one or more of the respective sequence modeling outputs comprises: processing the respective sequence modeling output for a last word in the first sequence of words through the output layer, wherein the output layer is configured to receive the respective sequence modeling output for the last word in the first sequence of words and generate a respective next word score for each word in a vocabulary of words, and wherein the respective next word score for each vocabulary word represents a likelihood that the vocabulary word is a word that immediately follows the last word in the first sequence of words in a source text. | 0.672195 |
8,495,591 | 13 | 14 | 13. A computer-readable storage memory storing computer-executable instructions which when executed cause a computing environment to: receiving an input from a caller, the input comprising the preprocessor conditional directive statement; in order to have information available in each parsing path induced by mutually exclusive branches returned to the caller, serializing the input into a stream of tokens produced by following each parsing path induced by mutually exclusive branches of the preprocessor conditional directive statement interrupting a declaration by: labeling tokens belonging to a first parsing path with a first parsing path indicator; labeling tokens belonging to a second parsing path with a second parsing path indicator; fetching the tokens that belong to the first parsing path in a first pass and returning the tokens that belong to the first parsing path to the caller; and fetching the tokens that belong to the second parsing path in a second pass and returning the tokens that belong to the second parsing path to the caller, wherein parsing paths induced by mutually exclusive branches of the preprocessor conditional directive statement are detected by matching preprocessor conditional directives of the preprocessor conditional directive statement. | 13. A computer-readable storage memory storing computer-executable instructions which when executed cause a computing environment to: receiving an input from a caller, the input comprising the preprocessor conditional directive statement; in order to have information available in each parsing path induced by mutually exclusive branches returned to the caller, serializing the input into a stream of tokens produced by following each parsing path induced by mutually exclusive branches of the preprocessor conditional directive statement interrupting a declaration by: labeling tokens belonging to a first parsing path with a first parsing path indicator; labeling tokens belonging to a second parsing path with a second parsing path indicator; fetching the tokens that belong to the first parsing path in a first pass and returning the tokens that belong to the first parsing path to the caller; and fetching the tokens that belong to the second parsing path in a second pass and returning the tokens that belong to the second parsing path to the caller, wherein parsing paths induced by mutually exclusive branches of the preprocessor conditional directive statement are detected by matching preprocessor conditional directives of the preprocessor conditional directive statement. 14. The computer-readable storage memory of claim 13 , wherein the caller comprises a compiler, a program development tool, a lexer, a syntax analyzer, a preprocessor or a preprocessor/lexer. | 0.795503 |
8,108,371 | 16 | 17 | 16. Computer-storage media having computer-executable instructions embodied thereon that, when executed by a computing device, facilitate a method for presenting a search result received in response to a search-engine query, the method comprising: submitting by the computing device the search-engine query, which was inputted into a web browser; receiving by the computing device a hyperlink of a web page deemed to satisfy the search-engine query, wherein the hyperlink is received by the web browser running a control; after receiving the hyperlink, using the control to automatically generate by the computing device a web-browser instance that is executed on a background thread of the web browser and that retrieves from a web server the web page identified by the hyperlink, wherein the web-browser instance operates in safe mode that does not allow controls to be executed; storing a snapshot of the web page retrieved in real time by the web-browser instance, wherein the snapshot is used to create a thumbnail of the web page; and presenting the thumbnail together with the hyperlink as part of a search-results webpage. | 16. Computer-storage media having computer-executable instructions embodied thereon that, when executed by a computing device, facilitate a method for presenting a search result received in response to a search-engine query, the method comprising: submitting by the computing device the search-engine query, which was inputted into a web browser; receiving by the computing device a hyperlink of a web page deemed to satisfy the search-engine query, wherein the hyperlink is received by the web browser running a control; after receiving the hyperlink, using the control to automatically generate by the computing device a web-browser instance that is executed on a background thread of the web browser and that retrieves from a web server the web page identified by the hyperlink, wherein the web-browser instance operates in safe mode that does not allow controls to be executed; storing a snapshot of the web page retrieved in real time by the web-browser instance, wherein the snapshot is used to create a thumbnail of the web page; and presenting the thumbnail together with the hyperlink as part of a search-results webpage. 17. The one or more computer-readable media of claim 16 , wherein the thumbnail includes at least one of a graphics interchange format (GIF), tagged image file format (TIFF), portable document format (PDF), or joint photographic experts group (JPEG) file format. | 0.768959 |
8,473,555 | 8 | 11 | 8. The method of claim 1 , wherein the session is a group chat session, and further comprising: storing, by the processor, a language parameter set for each participant participating in the group chat session, wherein the language parameter set comprises the language and the desired display language. | 8. The method of claim 1 , wherein the session is a group chat session, and further comprising: storing, by the processor, a language parameter set for each participant participating in the group chat session, wherein the language parameter set comprises the language and the desired display language. 11. The method of claim 8 , wherein the incoming electronic communication is a text-based file. | 0.979348 |
9,292,594 | 1 | 4 | 1. In a computing system environment, a method of finding relevancy data available on one or more computing devices, comprising: monitoring computing events on the one or more computing devices relative to current data; triggering an evaluation of the current data against original data earlier grouped together on the one or more computing devices according to relatedness of the original data based on the monitored events, the evaluation processing ordered symbol frequency vectors and ordered bit vectors for the current data and the original data to determine relatedness, and at least one vector contains one coordinate position for a set of symbols defined in a symbol dictionary for the original data, and wherein each symbol frequency vector includes a count for a number of times each particular symbol occurs within a given file's symbol dictionary, and wherein each bit vector includes a single bit representing each unique symbol within a given file's symbol dictionary, and wherein triggering further includes determining a common file of members grouped together in response to the evaluation; adding semantic meaning and metadata to the grouped to tether data by harvesting unions of the members that share the common file; and suggesting offerings that some other body of data exists that may be of interest to the current data based on the added semantic meaning and the metadata, and presenting the suggested offerings in a separate user interface for a user to explore when the user choses to do so. | 1. In a computing system environment, a method of finding relevancy data available on one or more computing devices, comprising: monitoring computing events on the one or more computing devices relative to current data; triggering an evaluation of the current data against original data earlier grouped together on the one or more computing devices according to relatedness of the original data based on the monitored events, the evaluation processing ordered symbol frequency vectors and ordered bit vectors for the current data and the original data to determine relatedness, and at least one vector contains one coordinate position for a set of symbols defined in a symbol dictionary for the original data, and wherein each symbol frequency vector includes a count for a number of times each particular symbol occurs within a given file's symbol dictionary, and wherein each bit vector includes a single bit representing each unique symbol within a given file's symbol dictionary, and wherein triggering further includes determining a common file of members grouped together in response to the evaluation; adding semantic meaning and metadata to the grouped to tether data by harvesting unions of the members that share the common file; and suggesting offerings that some other body of data exists that may be of interest to the current data based on the added semantic meaning and the metadata, and presenting the suggested offerings in a separate user interface for a user to explore when the user choses to do so. 4. The method of claim 1 , further including presenting to the user of the one or more computing devices a suggestion of the original data most related to the current data. | 0.832685 |
4,611,995 | 1 | 2 | 1. An electronic language learning machine, comprising: means to translate a language, memory means for storing words of a language to be learned and associated marks, each mark representative of additional information relating to a different one of the words; display means for visualizing words and marks; selecting means for selecting any one of the words stored in said memory means to be displayed for study by a user of said language learning machine; applying means for applying a selected word to said display means; and manually actuatable means for causing said applying means to apply to said display means the mark associated with the selected word and stored in said memory means, after the beginning of the display of the selected word, where in response to actuation of said manually actuatable means said language learning machine accesses memory to provide location of where said mark should appear in relation to said selected word, as opposed to an operator inputting the location. | 1. An electronic language learning machine, comprising: means to translate a language, memory means for storing words of a language to be learned and associated marks, each mark representative of additional information relating to a different one of the words; display means for visualizing words and marks; selecting means for selecting any one of the words stored in said memory means to be displayed for study by a user of said language learning machine; applying means for applying a selected word to said display means; and manually actuatable means for causing said applying means to apply to said display means the mark associated with the selected word and stored in said memory means, after the beginning of the display of the selected word, where in response to actuation of said manually actuatable means said language learning machine accesses memory to provide location of where said mark should appear in relation to said selected word, as opposed to an operator inputting the location. 2. An electronic language learning machine according to claim 1, wherein said memory means stores each word and its associated mark in the same memory address. | 0.879728 |
9,594,831 | 1 | 5 | 1. A method implemented by one or more computer processing devices, the method comprising: receiving and storing a list of multiple different named entities, the multiple different named entities homogenously pertaining to a particular subject matter domain; determining and storing a set of candidate mentions of the multiple different named entities, each candidate mention being an occurrence of a corresponding named entity in the list of multiple different named entities, the set of candidate mentions including true mentions and false mentions occurring in a collection of documents; identifying particular candidate mentions as the true mentions within the set of candidate mentions by leveraging homogeneity in the list of multiple different named entities, each true mention corresponding to a valid occurrence of an individual named entity in the collection of documents, the identifying including assigning scores to individual candidate mentions of the set of candidate mentions and identifying the particular candidate mentions as the true mentions using the scores; and outputting the true mentions. | 1. A method implemented by one or more computer processing devices, the method comprising: receiving and storing a list of multiple different named entities, the multiple different named entities homogenously pertaining to a particular subject matter domain; determining and storing a set of candidate mentions of the multiple different named entities, each candidate mention being an occurrence of a corresponding named entity in the list of multiple different named entities, the set of candidate mentions including true mentions and false mentions occurring in a collection of documents; identifying particular candidate mentions as the true mentions within the set of candidate mentions by leveraging homogeneity in the list of multiple different named entities, each true mention corresponding to a valid occurrence of an individual named entity in the collection of documents, the identifying including assigning scores to individual candidate mentions of the set of candidate mentions and identifying the particular candidate mentions as the true mentions using the scores; and outputting the true mentions. 5. The method of claim 1 , wherein the scores include co-occurrence scores, and said identifying comprises: identifying strings associated with plural respective named entities in the list of multiple different named entities that appear as the individual candidate mentions in a particular document; assigning the co-occurrence scores to the individual candidate mentions based on an extent to which the particular document includes two or more of the strings; and identifying the particular candidate mentions associated with the two or more of the strings as some of the true mentions based on the co-occurrence scores. | 0.688064 |
8,423,526 | 1 | 5 | 1. A system for comparing two or more phrases to determine a most common one of the two or more phrases, comprising: a linguistic interface for simultaneously submitting each of the two or more phrases as a search string to a search engine; and a linguistic analysis tool for receiving search results from the search engine for each of the two or more phrases, the linguistic analysis tool comparing the search results to determine the most common one of the two or more phrases; wherein the linguistic interface communicates with the linguistic analysis tool and displays the most common one of the two or more phrases to a user; and wherein the search results comprise a hit value that specifies the number of hits found by the search engine for the search string; wherein the linguistic interface and the linguistic analysis tool operate on a computer device. | 1. A system for comparing two or more phrases to determine a most common one of the two or more phrases, comprising: a linguistic interface for simultaneously submitting each of the two or more phrases as a search string to a search engine; and a linguistic analysis tool for receiving search results from the search engine for each of the two or more phrases, the linguistic analysis tool comparing the search results to determine the most common one of the two or more phrases; wherein the linguistic interface communicates with the linguistic analysis tool and displays the most common one of the two or more phrases to a user; and wherein the search results comprise a hit value that specifies the number of hits found by the search engine for the search string; wherein the linguistic interface and the linguistic analysis tool operate on a computer device. 5. The system of claim 1 , the linguistic interface operating within a personal computer. | 0.770619 |
8,375,308 | 1 | 20 | 1. A method of changing a conversation topic between a plurality of users via a user-interface, the method comprising a computer performing the steps of: concurrently displaying a user interface to each of a plurality of users engaging in a conversation over computer-based terminals, wherein the user interface includes input fields to enable any one of the plurality of users to request a change of a current conversation topic and request a new conversation topic and provide the user request to all other users engaging in the conversation; obtaining from at least a first one of the plurality of users, via the user-interface, a request to change the conversation topic; notifying the plurality of users, via the user-interface, of the request to change the current conversation topic by presenting an indicator to the plurality of users obtaining from at least a second one of the plurality of users, via the user-interface, at least one indication of support for the request to change the conversation topic; and changing the conversation topic between the users in response to the request and the at least one indication of support for the request, wherein the user-interface is configured to operate in a first mode and a second mode, wherein in the first mode, the users request to change the conversation topic by activating a switch on the user-interface, further wherein in the second mode, the users request to change the conversation topic by inputting one or more new conversation topics, wherein the user-interface is configured to automatically switch between the first mode and the second mode when more than a threshold percentage of the users request to change the conversation topic. | 1. A method of changing a conversation topic between a plurality of users via a user-interface, the method comprising a computer performing the steps of: concurrently displaying a user interface to each of a plurality of users engaging in a conversation over computer-based terminals, wherein the user interface includes input fields to enable any one of the plurality of users to request a change of a current conversation topic and request a new conversation topic and provide the user request to all other users engaging in the conversation; obtaining from at least a first one of the plurality of users, via the user-interface, a request to change the conversation topic; notifying the plurality of users, via the user-interface, of the request to change the current conversation topic by presenting an indicator to the plurality of users obtaining from at least a second one of the plurality of users, via the user-interface, at least one indication of support for the request to change the conversation topic; and changing the conversation topic between the users in response to the request and the at least one indication of support for the request, wherein the user-interface is configured to operate in a first mode and a second mode, wherein in the first mode, the users request to change the conversation topic by activating a switch on the user-interface, further wherein in the second mode, the users request to change the conversation topic by inputting one or more new conversation topics, wherein the user-interface is configured to automatically switch between the first mode and the second mode when more than a threshold percentage of the users request to change the conversation topic. 20. The method of claim 1 , wherein the request to change the conversation topic specifies one or more new conversation topics. | 0.86518 |
4,493,655 | 11 | 12 | 11. A radio-controlled teaching device comprising in combination: a teacher transmitter unit containing tone generation means, timing means associated with and controlling the duration of tones generated by said tone generation means, manual switching means operatively connected to said timing means for actuating said timing means and said tone generation means at selected points during oral reading of textual or test material, counting and readout means operatively associated with said timing means for counting and displaying the number of times said tone generation means are actuated, manual reset means operatively connected to said counting and readout means for selectively resetting said readout means to zero, a radio transmitter operatively coupled to the output of said tone generation means for transmitting tones generated by said tone generation means, an audio input jack for connecting said teacher transmitter unit to one audio output channel of a plural channel tape player, and a toner decoder operatively connected between said audio input jack and said timing means for automatically actuating said timing means and tone generation means in response to discrete tones recorded at selected points on one channel of a plural tape record; and a plurality of portable student receiver units containing a battery power supply, a radio receiver tuned to the carrier frequency of said transmitter, a tone decoder operatively connected to the output of said radio receiver, a first timing means operatively connected to and actuated by the output of said tone decoder for providing a short time period during which a student is expected to respond at said selected points during oral reading of textual or test material or during recorded presentation of programmed instructional material, a response switch which is momentarily closed by the student at said selected points during oral reading of textual or test material or during recorded presentation of programmed instructional material, a second timing means operatively connected to and actuated by said response switch for providing a brief time period when said response switch is momentarily closed, a first logic gate and a second logic gate operatively connected to said first and second timing means wherein a "right" pulse is conducted by said first logic gate when said response switch is momentarily closed during said short time period of said first timing means and, wherein a "wrong" pulse is conducted by said second logic gate when said response switch is momentarily closed when said short time period of said first timing means is not occuring, a third timing means operatively connected to the outputs of said first logic gate and second logic gate and actuated by said "right" pulse or "wrong" pulse for momentarily disabling said second timing means and said first logic gate and second logic gate when said response switch is momentarily closed, a first counter operatively connected to the output of said first logic gate, whereby a said "right" pulse advances said first counter one count when said "right" pulse occurs, a second counter operatively connected to said second logic gate, whereby said "wrong" pulse advances said second counter one count when said "wrong" pulse occurs, first decoder/drivers and liquid crystal readouts operatively connected to the outputs of said first counter for displaying the current count of said first counter, and second decoder/drivers and liquid crystal readouts operatively connected to the outputs of said second counter for displaying the current count of said second counter. | 11. A radio-controlled teaching device comprising in combination: a teacher transmitter unit containing tone generation means, timing means associated with and controlling the duration of tones generated by said tone generation means, manual switching means operatively connected to said timing means for actuating said timing means and said tone generation means at selected points during oral reading of textual or test material, counting and readout means operatively associated with said timing means for counting and displaying the number of times said tone generation means are actuated, manual reset means operatively connected to said counting and readout means for selectively resetting said readout means to zero, a radio transmitter operatively coupled to the output of said tone generation means for transmitting tones generated by said tone generation means, an audio input jack for connecting said teacher transmitter unit to one audio output channel of a plural channel tape player, and a toner decoder operatively connected between said audio input jack and said timing means for automatically actuating said timing means and tone generation means in response to discrete tones recorded at selected points on one channel of a plural tape record; and a plurality of portable student receiver units containing a battery power supply, a radio receiver tuned to the carrier frequency of said transmitter, a tone decoder operatively connected to the output of said radio receiver, a first timing means operatively connected to and actuated by the output of said tone decoder for providing a short time period during which a student is expected to respond at said selected points during oral reading of textual or test material or during recorded presentation of programmed instructional material, a response switch which is momentarily closed by the student at said selected points during oral reading of textual or test material or during recorded presentation of programmed instructional material, a second timing means operatively connected to and actuated by said response switch for providing a brief time period when said response switch is momentarily closed, a first logic gate and a second logic gate operatively connected to said first and second timing means wherein a "right" pulse is conducted by said first logic gate when said response switch is momentarily closed during said short time period of said first timing means and, wherein a "wrong" pulse is conducted by said second logic gate when said response switch is momentarily closed when said short time period of said first timing means is not occuring, a third timing means operatively connected to the outputs of said first logic gate and second logic gate and actuated by said "right" pulse or "wrong" pulse for momentarily disabling said second timing means and said first logic gate and second logic gate when said response switch is momentarily closed, a first counter operatively connected to the output of said first logic gate, whereby a said "right" pulse advances said first counter one count when said "right" pulse occurs, a second counter operatively connected to said second logic gate, whereby said "wrong" pulse advances said second counter one count when said "wrong" pulse occurs, first decoder/drivers and liquid crystal readouts operatively connected to the outputs of said first counter for displaying the current count of said first counter, and second decoder/drivers and liquid crystal readouts operatively connected to the outputs of said second counter for displaying the current count of said second counter. 12. A radio-controlled teaching device according to claim 11, wherein said recorded presentation of programmed instructional material further includes a plural channel tape player, speaker, and instructional tape, a first audio output carrying recorded tone signals of said player being connected to said audio input jack of said teacher transmitter unit, a second audio output carrying recorded instructional material of said player being connected to said speaker for said recorded presentation of programmed instructional material to one or more students of a classroom, said students responding at selected points of said programmed instructional material by momentarily closing respective response switches of said student receiver units. | 0.500672 |
7,996,210 | 1 | 3 | 1. A computer readable medium embodying instructions executable by a processor to perform a method for determining a sentiment lexicon associated with an entity, the method steps comprising: inputting a plurality of texts associated with the entity; labeling seed words in the plurality of texts as positive or negative; determining a score estimate for the plurality of words based on the labeling; re-enumerating paths of the plurality of words and determining a number of sentiment alternations; determining a final score for the plurality of words using only paths whose number of alternations is within a threshold; converting the final scores to corresponding s-scores for each of the plurality of words; and outputting the sentiment lexicon associated with the entity. | 1. A computer readable medium embodying instructions executable by a processor to perform a method for determining a sentiment lexicon associated with an entity, the method steps comprising: inputting a plurality of texts associated with the entity; labeling seed words in the plurality of texts as positive or negative; determining a score estimate for the plurality of words based on the labeling; re-enumerating paths of the plurality of words and determining a number of sentiment alternations; determining a final score for the plurality of words using only paths whose number of alternations is within a threshold; converting the final scores to corresponding s-scores for each of the plurality of words; and outputting the sentiment lexicon associated with the entity. 3. The method of claim 1 , further comprising discarding ambiguous words of the plurality of words. | 0.853982 |
9,398,032 | 12 | 13 | 12. The apparatus of claim 8 , further comprising: wherein said computer-readable code of the local engine is configured to receive script analysis results via the network from the script analyzer; and said computer-readable code of the local engine is configured to perform a security action if the results indicate presence of malicious code in the unique script. | 12. The apparatus of claim 8 , further comprising: wherein said computer-readable code of the local engine is configured to receive script analysis results via the network from the script analyzer; and said computer-readable code of the local engine is configured to perform a security action if the results indicate presence of malicious code in the unique script. 13. The apparatus of claim 12 , wherein the security action comprises blocking execution of the unique script with the malicious code. | 0.935078 |
9,953,171 | 1 | 5 | 1. A system for tokenization of data comprising: a receiver configured to receive a request for tokenization, wherein the request comprises input data to be tokenized; a parser configured to parse the input data into a plurality of input data parts and determine respective datatypes corresponding to the input data parts; a trained artificial neural network comprising a plurality of artificial neurons comprising respective inputs, weight coefficients, and activation functions, the plurality of artificial neurons forming an input layer, an output layer, and one or more hidden layers, wherein the input layer receives the plurality of input data parts and the respective datatypes, the one or more hidden layers apply a transformation to the plurality of input data parts to generate tokens via a plurality of different tokenization techniques corresponding to the respective datatypes of the plurality of input data parts, and the output layer provides at least one output token corresponding to a given input data part out of the plurality of input data parts. | 1. A system for tokenization of data comprising: a receiver configured to receive a request for tokenization, wherein the request comprises input data to be tokenized; a parser configured to parse the input data into a plurality of input data parts and determine respective datatypes corresponding to the input data parts; a trained artificial neural network comprising a plurality of artificial neurons comprising respective inputs, weight coefficients, and activation functions, the plurality of artificial neurons forming an input layer, an output layer, and one or more hidden layers, wherein the input layer receives the plurality of input data parts and the respective datatypes, the one or more hidden layers apply a transformation to the plurality of input data parts to generate tokens via a plurality of different tokenization techniques corresponding to the respective datatypes of the plurality of input data parts, and the output layer provides at least one output token corresponding to a given input data part out of the plurality of input data parts. 5. The system of claim 1 , wherein the secure tokenization technique comprises at least one selected from the group consisting of: hashing, encrypting, random numbers, and combinations of hashing, encrypting, or random numbers. | 0.821541 |
9,715,874 | 1 | 6 | 1. A method of updating an automatic speech recognition (ASR) system, the method comprising: compiling a first finite-state transducer (FST) from a set of one or more ASR models, the first FST comprising a first set of paths defining a first set of speech sequences for the ASR system to recognize based on the set of ASR models; initializing the ASR system to use the first FST in recognizing speech, by causing the first FST to be stored at the ASR system; in response to an update to the set of ASR models, compiling a second FST from the updated set of ASR models, the second FST comprising a second set of paths defining a second set of speech sequences for the ASR system to recognize based on the updated set of ASR models, the second set of speech sequences being different from the first set of speech sequences by at least one speech sequence; by analyzing the second FST together with the first FST via execution of stored instructions by at least one processor, extracting a patch representing the difference between the first FST and the second FST, the patch being configured to be applied non-destructively to the first FST at the ASR system to cause the ASR system to use the second set of paths from the second FST in recognizing speech, wherein extracting the patch comprises generating a third FST by adding to the first FST paths that are in the second FST and not in the first FST and removing from the first FST paths that are in the first FST and not in the second FST, resulting in the third FST encoding the second set of paths of the second FST in a different graph structure than the second FST, and forming the patch of states in the third FST that are modified and/or added with respect to the first FST; and providing the extracted patch to the ASR system as an update. | 1. A method of updating an automatic speech recognition (ASR) system, the method comprising: compiling a first finite-state transducer (FST) from a set of one or more ASR models, the first FST comprising a first set of paths defining a first set of speech sequences for the ASR system to recognize based on the set of ASR models; initializing the ASR system to use the first FST in recognizing speech, by causing the first FST to be stored at the ASR system; in response to an update to the set of ASR models, compiling a second FST from the updated set of ASR models, the second FST comprising a second set of paths defining a second set of speech sequences for the ASR system to recognize based on the updated set of ASR models, the second set of speech sequences being different from the first set of speech sequences by at least one speech sequence; by analyzing the second FST together with the first FST via execution of stored instructions by at least one processor, extracting a patch representing the difference between the first FST and the second FST, the patch being configured to be applied non-destructively to the first FST at the ASR system to cause the ASR system to use the second set of paths from the second FST in recognizing speech, wherein extracting the patch comprises generating a third FST by adding to the first FST paths that are in the second FST and not in the first FST and removing from the first FST paths that are in the first FST and not in the second FST, resulting in the third FST encoding the second set of paths of the second FST in a different graph structure than the second FST, and forming the patch of states in the third FST that are modified and/or added with respect to the first FST; and providing the extracted patch to the ASR system as an update. 6. The method of claim 1 , wherein using the second set of paths from the second FST in recognizing speech comprises disallowing at least one path included in the first FST. | 0.879694 |
8,631,002 | 1 | 5 | 1. A computer-implemented method of determining a query classification using a computing system having processor, memory, and data storage subsystems, the computer-implemented method comprising: selecting a knowledge domain comprising a plurality of seed-web domains which are classified to belong to the knowledge domain; for each seed-web domain, performing a filtered web search of a given query utilizing a filter associated with a particular seed-web domain to identify a total number of filtered documents associated with the seed-web domain that are relevant to the given query thereby resulting in each seed-web domain within the knowledge domain having a corresponding total number of filtered documents; for each seed-web domain, referencing a total number of documents corresponding with the seed-web domain thereby resulting in each seed-web domain within the knowledge domain having a corresponding total number of documents; calculating, via the processor, a coverage for each seed-web domain using the total number of filtered documents associated with the seed-web domain and the total number of documents corresponding with the seed-web domain thereby resulting in each seed-web domain within the knowledge domain having a corresponding coverage, wherein the coverage for each seed-web domain is calculated by dividing the total number of filtered documents pages for the corresponding seed-web domain by the total number of documents for the seed-web domain; and computing an amount of coverage for the knowledge domain using the calculated coverage for each seed-web domain. | 1. A computer-implemented method of determining a query classification using a computing system having processor, memory, and data storage subsystems, the computer-implemented method comprising: selecting a knowledge domain comprising a plurality of seed-web domains which are classified to belong to the knowledge domain; for each seed-web domain, performing a filtered web search of a given query utilizing a filter associated with a particular seed-web domain to identify a total number of filtered documents associated with the seed-web domain that are relevant to the given query thereby resulting in each seed-web domain within the knowledge domain having a corresponding total number of filtered documents; for each seed-web domain, referencing a total number of documents corresponding with the seed-web domain thereby resulting in each seed-web domain within the knowledge domain having a corresponding total number of documents; calculating, via the processor, a coverage for each seed-web domain using the total number of filtered documents associated with the seed-web domain and the total number of documents corresponding with the seed-web domain thereby resulting in each seed-web domain within the knowledge domain having a corresponding coverage, wherein the coverage for each seed-web domain is calculated by dividing the total number of filtered documents pages for the corresponding seed-web domain by the total number of documents for the seed-web domain; and computing an amount of coverage for the knowledge domain using the calculated coverage for each seed-web domain. 5. The computer-implemented method of claim 1 , wherein a significant average percentage of coverage exceeds a minimum average percentage of coverage. | 0.738676 |
8,060,507 | 23 | 29 | 23. A system for use in personalizing advertising for a user, the system comprising: one or more processing devices; and one or more storage devices storing instructions which, when executed, cause the one or more processing devices to implement: a content server configured to present documents, from a set of documents, to a user such that the user can select documents for viewing; at least one positive word vector formed using words contained in at least a segment of the documents in the set of documents that are selected by the user for viewing; at least one negative word vector formed using words contained in at least a segment of the documents in the set of documents that are not selected by the user for viewing; one or more document word vectors for at least some of the documents that were selected by the user for viewing; a ranking engine configured to: perform a vector space relationship analysis of the positive word vector, the negative word vector, and the document word vectors; establish a document rank order of the documents selected by the user for viewing based on the performed vector space relationship analysis; classify the documents selected by the user for viewing in predetermined categories; and rank the predetermined categories based on the document rank order; and an ad server, operatively coupled with the ranking engine, for presenting, to the user in a selected context, advertisements associated with the ranked categories. | 23. A system for use in personalizing advertising for a user, the system comprising: one or more processing devices; and one or more storage devices storing instructions which, when executed, cause the one or more processing devices to implement: a content server configured to present documents, from a set of documents, to a user such that the user can select documents for viewing; at least one positive word vector formed using words contained in at least a segment of the documents in the set of documents that are selected by the user for viewing; at least one negative word vector formed using words contained in at least a segment of the documents in the set of documents that are not selected by the user for viewing; one or more document word vectors for at least some of the documents that were selected by the user for viewing; a ranking engine configured to: perform a vector space relationship analysis of the positive word vector, the negative word vector, and the document word vectors; establish a document rank order of the documents selected by the user for viewing based on the performed vector space relationship analysis; classify the documents selected by the user for viewing in predetermined categories; and rank the predetermined categories based on the document rank order; and an ad server, operatively coupled with the ranking engine, for presenting, to the user in a selected context, advertisements associated with the ranked categories. 29. The system of claim 23 , wherein the ranking engine is configured to perform the vector space relationship analysis by applying Rocchio's method to the positive word vector, the negative word vector, and the document word vectors. | 0.840599 |
8,051,071 | 19 | 21 | 19. A system, comprising: a memory device to store computer-executable instructions; and one or more processors, to execute the computer-executable instructions, to: determine an amount or rate that a document moves positions in search result rankings over time; generate a score for the document based on the amount or rate that the document moves in the search result rankings over time; and rank the document with regard to at least one other document based on the score. | 19. A system, comprising: a memory device to store computer-executable instructions; and one or more processors, to execute the computer-executable instructions, to: determine an amount or rate that a document moves positions in search result rankings over time; generate a score for the document based on the amount or rate that the document moves in the search result rankings over time; and rank the document with regard to at least one other document based on the score. 21. The system of claim 19 , where when determining the amount or rate that the document moves in search result rankings, the one or more processors are to: determine a rate at which the document moves positions in the search result rankings. | 0.845663 |
8,010,527 | 1 | 21 | 1. A method implemented within a computer system comprising a central processing unit (CPU) and a random access memory (RAM), the method comprising: a. utilizing the CPU and RAM to obtain a history of online activities of a user; b. utilizing the CPU and RAM to receive user preference information from the user; c. utilizing the CPU and RAM to identify a plurality of online information resources linking to online resources viewed by the user, wherein each of the plurality of online information resources is associated with an online information source; d. utilizing the CPU and RAM to generate a plurality of relevance scores for each of the identified online information resource; and e. using the generated plurality of relevance scores to generate a ranked list of recommended online information sources, wherein a rank of each online information source is determined by aggregating at least some of the plurality of relevance scores of the identified online information resources according to the received user preference information, wherein: the ranked list comprises links to online sources that are not in the history of the online activities of the user, the online information resource is a blog post, the online resource viewed by the user is a visited web page, the online information source is a source blog web page, and the online source is a related web feed. | 1. A method implemented within a computer system comprising a central processing unit (CPU) and a random access memory (RAM), the method comprising: a. utilizing the CPU and RAM to obtain a history of online activities of a user; b. utilizing the CPU and RAM to receive user preference information from the user; c. utilizing the CPU and RAM to identify a plurality of online information resources linking to online resources viewed by the user, wherein each of the plurality of online information resources is associated with an online information source; d. utilizing the CPU and RAM to generate a plurality of relevance scores for each of the identified online information resource; and e. using the generated plurality of relevance scores to generate a ranked list of recommended online information sources, wherein a rank of each online information source is determined by aggregating at least some of the plurality of relevance scores of the identified online information resources according to the received user preference information, wherein: the ranked list comprises links to online sources that are not in the history of the online activities of the user, the online information resource is a blog post, the online resource viewed by the user is a visited web page, the online information source is a source blog web page, and the online source is a related web feed. 21. The method of claim 1 , wherein the user preference information comprises ranking criteria. | 0.863506 |
8,495,483 | 2 | 3 | 2. The method of claim 1 , where, for each document, of the plurality of documents, the selected text includes text beginning after the hyperlink and continuing to an end of the paragraph that includes the hyperlink. | 2. The method of claim 1 , where, for each document, of the plurality of documents, the selected text includes text beginning after the hyperlink and continuing to an end of the paragraph that includes the hyperlink. 3. The method of claim 2 , further comprising: selecting text from each document, of the plurality of documents, only when the paragraph that includes the hyperlink is structured as a paragraph that begins with the hyperlink, is followed by the text, and includes no additional hyperlinks. | 0.959983 |
9,892,112 | 13 | 17 | 13. A method employing a knowledge engine for processing natural language input, comprising: parsing a phrase into subcomponents using the knowledge engine; identifying a category for each parsed subcomponent and a syntactic structure of the phrase; generating a list of definitions for each parsed subcomponent, the list corresponding to the identified category; ranking the definitions in the list according to relevance; identifying an outcome base on ranked relevancy, the outcome being a definition with the highest relevance in the list; searching a corpus for evidence of a pattern associated with the list; scoring each definition in the list according to a weighted calculation based on congruence of corpus evidence with the pattern; and generating an outcome, wherein the outcome is a definition with a strongest congruence to the pattern. | 13. A method employing a knowledge engine for processing natural language input, comprising: parsing a phrase into subcomponents using the knowledge engine; identifying a category for each parsed subcomponent and a syntactic structure of the phrase; generating a list of definitions for each parsed subcomponent, the list corresponding to the identified category; ranking the definitions in the list according to relevance; identifying an outcome base on ranked relevancy, the outcome being a definition with the highest relevance in the list; searching a corpus for evidence of a pattern associated with the list; scoring each definition in the list according to a weighted calculation based on congruence of corpus evidence with the pattern; and generating an outcome, wherein the outcome is a definition with a strongest congruence to the pattern. 17. The method of claim 13 , wherein the ranking according relevance includes filtering the definitions based on similar adjectives. | 0.825397 |
8,117,225 | 15 | 41 | 15. A computer program product embodied on a non-transitory computer-readable medium, comprising: code for registering a global unique user login information capable of being used to access a plurality of different online applications associated with an online application system including a first online application that provides access to a first one or more files associated with the first online application, a second online application that provides access to a second one or more files associated with the second online application, a third online application that provides access to a third one or more files associated with the third online application, and a fourth online application that provides access to a fourth one or more files associated with the fourth online application; code for receiving the global unique user login information in connection with a login; code for receiving an indication to add access to the first online application, utilizing at least one first online application identifier associated with the first online application; code for receiving an indication to add access to the second online application, utilizing at least one second online application identifier associated with the second online application; code for receiving an indication to add access to the third online application, utilizing at least one third online application identifier associated with the third online application; code for receiving an indication to add access to the fourth online application, utilizing at least one fourth online application identifier associated with the fourth online application; code for allowing registration of the first online application; code for allowing registration of the second online application; code for allowing registration of the third online application; code for allowing registration of the fourth online application; code for displaying the at least one first online application identifier associated with the first online application for access purposes; code for displaying the at least one second online application identifier associated with the second online application for access purposes; code for displaying the at least one third online application identifier associated with the third online application for access purposes; code for displaying the at least one fourth online application identifier associated with the fourth online application for access purposes; code for receiving a selection of the at least one first online application identifier associated with the first online application for access purposes; code for receiving a selection of the at least one second online application identifier associated with the second online application for access purposes; code for receiving a selection of the at least one third online application identifier associated with the third online application for access purposes; code for receiving a selection of the at least one fourth online application identifier associated with the fourth online application for access purposes; code for, in response to the selection of the at least one first online application identifier associated with the first online application for access purposes, allowing access to the first online application; code for, in response to the selection of the at least one second online application identifier associated with the second online application for access purposes, allowing access to the second online application; code for, in response to the selection of the at least one third online application identifier associated with the third online application for access purposes, allowing access to the third online application; code for, in response to the selection of the at least one fourth online application identifier associated with the fourth online application for access purposes, allowing access to the fourth online application; code for identifying at least one profile, the at least one profile including: at least one user profile of an accessing user, the at least one user profile including: registration information determined when the accessing user registered, and automatically determined information that is determined automatically based on user selections of the accessing user; and at least one group profile; code for displaying a search interface in connection with the online application system, the search interface being displayed simultaneously with an advertisement that is selected based on the registration information and the automatically determined information of the at least one user profile, and the at least one group profile; code for performing a search in connection with the online application system utilizing the search interface; and code for displaying search results of the search, where the search results involve a plurality of the different online applications associated with the online application system. | 15. A computer program product embodied on a non-transitory computer-readable medium, comprising: code for registering a global unique user login information capable of being used to access a plurality of different online applications associated with an online application system including a first online application that provides access to a first one or more files associated with the first online application, a second online application that provides access to a second one or more files associated with the second online application, a third online application that provides access to a third one or more files associated with the third online application, and a fourth online application that provides access to a fourth one or more files associated with the fourth online application; code for receiving the global unique user login information in connection with a login; code for receiving an indication to add access to the first online application, utilizing at least one first online application identifier associated with the first online application; code for receiving an indication to add access to the second online application, utilizing at least one second online application identifier associated with the second online application; code for receiving an indication to add access to the third online application, utilizing at least one third online application identifier associated with the third online application; code for receiving an indication to add access to the fourth online application, utilizing at least one fourth online application identifier associated with the fourth online application; code for allowing registration of the first online application; code for allowing registration of the second online application; code for allowing registration of the third online application; code for allowing registration of the fourth online application; code for displaying the at least one first online application identifier associated with the first online application for access purposes; code for displaying the at least one second online application identifier associated with the second online application for access purposes; code for displaying the at least one third online application identifier associated with the third online application for access purposes; code for displaying the at least one fourth online application identifier associated with the fourth online application for access purposes; code for receiving a selection of the at least one first online application identifier associated with the first online application for access purposes; code for receiving a selection of the at least one second online application identifier associated with the second online application for access purposes; code for receiving a selection of the at least one third online application identifier associated with the third online application for access purposes; code for receiving a selection of the at least one fourth online application identifier associated with the fourth online application for access purposes; code for, in response to the selection of the at least one first online application identifier associated with the first online application for access purposes, allowing access to the first online application; code for, in response to the selection of the at least one second online application identifier associated with the second online application for access purposes, allowing access to the second online application; code for, in response to the selection of the at least one third online application identifier associated with the third online application for access purposes, allowing access to the third online application; code for, in response to the selection of the at least one fourth online application identifier associated with the fourth online application for access purposes, allowing access to the fourth online application; code for identifying at least one profile, the at least one profile including: at least one user profile of an accessing user, the at least one user profile including: registration information determined when the accessing user registered, and automatically determined information that is determined automatically based on user selections of the accessing user; and at least one group profile; code for displaying a search interface in connection with the online application system, the search interface being displayed simultaneously with an advertisement that is selected based on the registration information and the automatically determined information of the at least one user profile, and the at least one group profile; code for performing a search in connection with the online application system utilizing the search interface; and code for displaying search results of the search, where the search results involve a plurality of the different online applications associated with the online application system. 41. The computer program product of claim 15 , wherein the computer program product is operable such that the first online application identifier, the second online application identifier, the third online application identifier, and the fourth online application identifier are organized in horizontally oriented tabs. | 0.790957 |
9,436,951 | 22 | 35 | 22. A non-transitory computer-readable medium whose contents configure one or more computing systems to perform a method of presenting additional content for a term presented by a first mobile communication device, the method comprising: receiving, by the first mobile communication device, a first utterance; transmitting a first identifier of the first mobile communication device and the first utterance from the first mobile communication device to a computing device; receiving, by the first mobile communication device from the computing device, text representing a transcription of the first utterance; receiving, by the first mobile communication device from the computing device, an indicator that first additional content is available for a term identified within the text by the indicator, wherein the term is associated at the computing device with the first identifier of the first mobile communication device and a second identifier of a second mobile communication device, and wherein the first additional content for the term is associated with the first identifier and the second identifier; presenting, on the first mobile communications device, the text with an emphasis on the term identified by the indicator; after presenting the text on the first mobile communication device, receiving, by the first mobile communication device, a second utterance that includes the term; transmitting, by the first mobile communication device, the first identifier and the second utterance to the computing device; receiving, by the first mobile communication device from the computing device, in response to transmitting the second utterance and the first identifier, the first additional content; presenting, on the first mobile communication device, the first additional content for the term; transmitting, by the first mobile communication device, the second identifier to the computing device, the computing device configured to send the text as well as the indicator that first additional content is available for the term to the second mobile communication device using the second identifier; and receiving, by the first mobile communication device from the computing device, a message including a transcribed third utterance received by the second communication device in response to the text. | 22. A non-transitory computer-readable medium whose contents configure one or more computing systems to perform a method of presenting additional content for a term presented by a first mobile communication device, the method comprising: receiving, by the first mobile communication device, a first utterance; transmitting a first identifier of the first mobile communication device and the first utterance from the first mobile communication device to a computing device; receiving, by the first mobile communication device from the computing device, text representing a transcription of the first utterance; receiving, by the first mobile communication device from the computing device, an indicator that first additional content is available for a term identified within the text by the indicator, wherein the term is associated at the computing device with the first identifier of the first mobile communication device and a second identifier of a second mobile communication device, and wherein the first additional content for the term is associated with the first identifier and the second identifier; presenting, on the first mobile communications device, the text with an emphasis on the term identified by the indicator; after presenting the text on the first mobile communication device, receiving, by the first mobile communication device, a second utterance that includes the term; transmitting, by the first mobile communication device, the first identifier and the second utterance to the computing device; receiving, by the first mobile communication device from the computing device, in response to transmitting the second utterance and the first identifier, the first additional content; presenting, on the first mobile communication device, the first additional content for the term; transmitting, by the first mobile communication device, the second identifier to the computing device, the computing device configured to send the text as well as the indicator that first additional content is available for the term to the second mobile communication device using the second identifier; and receiving, by the first mobile communication device from the computing device, a message including a transcribed third utterance received by the second communication device in response to the text. 35. The non-transitory computer-readable medium of claim 22 , wherein receiving the text from the first computing device includes receiving a plurality of terms that have been selected by the first computing device from the transcription and associated with the identifier of the first mobile communication device. | 0.682186 |
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