Patents by Inventor Christopher J. C. Burges
Christopher J. C. Burges has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 9031885Abstract: Aspects of the subject matter described herein relate to predicting and using search engine switching behavior. In aspects, switching components receive a representation of user interactions with at least one browser. The switching components derive information from the representation that is useful in predicting whether a user will switch search engines. The derived information and information about a user's current interaction with a browser is then used by a switch predictor to predict whether the user will switch search engines. This prediction may be used in a variety of ways examples of which are given herein.Type: GrantFiled: May 7, 2012Date of Patent: May 12, 2015Assignee: Microsoft Technology Licensing, LLCInventors: Allison P. Heath, Ryen William White, Christopher J. C. Burges, Eric David Brill, Robert L. Rounthwaite
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Patent number: 9020806Abstract: The subject disclosure is directed towards automated processes for generating sentence completion questions based at least in part on a language model. Using the language model, a sentence is located, and alternates for a focus word (or words) in the sentence are automatically provided. Also described is automated filtering candidate sentences to locate the sentence, filtering the alternates based upon elimination criteria, scoring sentences with the correct word and as modified the alternates, and ranking the alternates. Manual selection may be used along with the automated processes.Type: GrantFiled: November 30, 2012Date of Patent: April 28, 2015Assignee: Microsoft Technology Licensing, LLCInventors: Geoffrey G. Zweig, Christopher J. C. Burges
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Patent number: 8935258Abstract: Described is a technology for identifying sample data items (e.g., documents corresponding to query-URL pairs) having the greatest likelihood of being mislabeled when previously judged, and selecting those data items for re-judging. In one aspect, lambda gradient scores (information associated with ranked sample data items that indicates a relative direction and how “strongly” to move each data item for lowering a ranking cost) are summed for pairs of sample data items to compute re-judgment scores for each of those sample data items. The re-judgment scores indicate a relative likelihood of mislabeling. Once the selected sample data items are re-judged, a new training set is available, whereby a new ranker may be trained.Type: GrantFiled: June 15, 2009Date of Patent: January 13, 2015Assignee: Microsoft CorporationInventors: Krysta M. Svore, Elbio Renato Torres Abib, Christopher J. C. Burges, Bhuvan Middha
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Publication number: 20140156260Abstract: The subject disclosure is directed towards automated processes for generating sentence completion questions based at least in part on a language model. Using the language model, a sentence is located, and alternates for a focus word (or words) in the sentence are automatically provided. Also described is automated filtering candidate sentences to locate the sentence, filtering the alternates based upon elimination criteria, scoring sentences with the correct word and as modified the alternates, and ranking the alternates. Manual selection may be used along with the automated processes.Type: ApplicationFiled: November 30, 2012Publication date: June 5, 2014Applicant: MICROSOFT CORPORATIONInventors: Geoffrey G. Zweig, Christopher J.C. Burges
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Publication number: 20130282632Abstract: A spam detection system is disclosed. The system includes a classifier training component that receives a first set of training pages labeled as normal pages and a second set of training pages labeled as spam pages. The training component trains a web page classifier based on both the first set of training pages and the second set of training pages. A spam detector then receives unlabeled web pages uses the web page classifier to classify the unlabeled web pages as spam pages or normal pages.Type: ApplicationFiled: June 19, 2013Publication date: October 24, 2013Inventors: Dengyong Zhou, Christopher J.C. Burges, Tao Tao
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Patent number: 8494998Abstract: A spam detection system is disclosed. The system includes a classifier training component that receives a first set of training pages labeled as normal pages and a second set of training pages labeled as spam pages. The training component trains a web page classifier based on both the first set of training pages and the second set of training pages. A spam detector then receives unlabeled web pages uses the web page classifier to classify the unlabeled web pages as spam pages or normal pages.Type: GrantFiled: April 1, 2011Date of Patent: July 23, 2013Assignee: Microsoft CorporationInventors: Dengyong Zhou, Christopher J. C. Burges, Tao Tao
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Patent number: 8392410Abstract: Described herein is a system that includes a receiver component that receives first scores for training points and second scores for the training points, wherein the first scores are individually assigned to the training points by a first ranker component and the second scores are individually assigned to the training points by a second ranker component. The apparatus further includes a determiner component in communication with the receiver component that automatically outputs a value for a parameter ? based at least in part upon the first scores and the second scores, wherein ? is used to linearly combine the first ranker component and the second ranker component.Type: GrantFiled: July 15, 2010Date of Patent: March 5, 2013Assignee: Microsoft CorporationInventor: Christopher J. C. Burges
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Patent number: 8332411Abstract: A system described herein includes a trainer component that receives an estimated gradient of cost that corresponds to a first ranker component with respect to at least one training point and at least one query. The trainer component builds a second ranker component based at least in part upon the received estimated gradient. The system further includes a combiner component that linearly combines the first ranker component and the second ranker component.Type: GrantFiled: February 18, 2008Date of Patent: December 11, 2012Assignee: Microsoft CorporationInventors: Christopher J. C. Burges, Qiang Wu
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Publication number: 20120271811Abstract: Aspects of the subject matter described herein relate to predicting and using search engine switching behavior. In aspects, switching components receive a representation of user interactions with at least one browser. The switching components derive information from the representation that is useful in predicting whether a user will switch search engines. The derived information and information about a user's current interaction with a browser is then used by a switch predictor to predict whether the user will switch search engines. This prediction may be used in a variety of ways examples of which are given herein.Type: ApplicationFiled: May 7, 2012Publication date: October 25, 2012Applicant: Microsoft CorporationInventors: Allison P. Heath, Ryen William White, Christopher J.C. Burges, Eric David Brill, Robert L. Rounthwaite
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Patent number: 8185484Abstract: Aspects of the subject matter described herein relate to predicting and using search engine switching behavior. In aspects, switching components receive a representation of user interactions with at least one browser. The switching components derive information from the representation that is useful in predicting whether a user will switch search engines. The derived information and information about a user's current interaction with a browser is then used by a switch predictor to predict whether the user will switch search engines. This prediction may be used in a variety of ways examples of which are given herein.Type: GrantFiled: June 6, 2011Date of Patent: May 22, 2012Assignee: Microsoft CorporationInventors: Allison P Heath, Ryen William White, Christopher J. C. Burges, Eric David Brill, Robert L Rounthwaite
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Patent number: 8156129Abstract: A system described herein includes analyzer component that analyzes queries submitted by users and corresponding URLs selected by the users, wherein the queries include a first query and a second query, and wherein the analyzer component determines that the first query and the second query are substantially similar queries. The system additionally includes a correlator component that, responsive to the analyzer component determining that the first query and the second query are substantially similar, generates correlation data that indicates that the first and second queries are substantially similar.Type: GrantFiled: January 15, 2009Date of Patent: April 10, 2012Assignee: Microsoft CorporationInventors: Dengyong Zhou, Christopher J. C. Burges, Robert L. Rounthwaite
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Publication number: 20110295847Abstract: Concepts are presented related to a search engine query. Users can subsequently navigate search results and/or reformulate a query at a conceptual level. In one instance, users can specify weight with respect to one or more concepts to capture interest or lack of interest with respect to search intent. Based on one or more weights, a search query can be modified and results presented to a user along with associated concepts to enable continued interaction. Additionally or alternatively, organization and/or presentation of search results as well as advertisements can be influenced by user-specified weights or other interactions with concepts.Type: ApplicationFiled: June 1, 2010Publication date: December 1, 2011Applicant: MICROSOFT CORPORATIONInventors: Silviu-Petru Cucerzan, Christopher J. C. Burges
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Publication number: 20110282816Abstract: A spam detection system is disclosed. The system includes a classifier training component that receives a first set of training pages labeled as normal pages and a second set of training pages labeled as spam pages. The training component trains a web page classifier based on both the first set of training pages and the second set of training pages. A spam detector then receives unlabeled web pages uses the web page classifier to classify the unlabeled web pages as spam pages or normal pages.Type: ApplicationFiled: April 1, 2011Publication date: November 17, 2011Applicant: MICROSOFT CORPORATIONInventors: Dengyong Zhou, Christopher J.C. Burges, Tao Tao
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Publication number: 20110238648Abstract: Aspects of the subject matter described herein relate to predicting and using search engine switching behavior. In aspects, switching components receive a representation of user interactions with at least one browser. The switching components derive information from the representation that is useful in predicting whether a user will switch search engines. The derived information and information about a user's current interaction with a browser is then used by a switch predictor to predict whether the user will switch search engines. This prediction may be used in a variety of ways examples of which are given herein.Type: ApplicationFiled: June 6, 2011Publication date: September 29, 2011Applicant: Microsoft CorporationInventors: Allison P. Heath, Ryen William White, Christopher J.C. Burges, Eric David Brill, Robert L. Rounthwaite
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Patent number: 7984000Abstract: Aspects of the subject matter described herein relate to predicting and using search engine switching behavior. In aspects, switching components receive a representation of user interactions with at least one browser. The switching components derive information from the representation that is useful in predicting whether a user will switch search engines. The derived information and information about a user's current interaction with a browser is then used by a switch predictor to predict whether the user will switch search engines. This prediction may be used in a variety of ways examples of which are given herein.Type: GrantFiled: December 18, 2007Date of Patent: July 19, 2011Assignee: Microsoft CorporationInventors: Allison P Heath, Ryen William White, Christopher J. C. Burges, Eric David Brill, Robert L Rounthwaite
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Patent number: 7941391Abstract: A collection of web pages is considered as a directed graph in which the pages themselves are nodes and the hyperlinks between the pages are directed edges in the graph. A trusted entity identifies training examples for spam pages and normal pages. A random walk is conducted through the directed graph that includes the collection of web pages and the stationary probabilities, and transitional probabilities, among the nodes in the directed graph are obtained. A classifier training component estimates a classification function that changes slowly on densely connected subgraphs within the directed graph. The classification function assigns a value to each of the nodes in the directed graph and identifies them as spam or normal pages based upon whether the value meets a given function threshold value.Type: GrantFiled: September 14, 2007Date of Patent: May 10, 2011Assignee: Microsoft CorporationInventors: Dengyong Zhou, Christopher J. C. Burges, Tao Tao
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Patent number: 7937264Abstract: A general probabilistic formulation referred to as ‘Conditional Harmonic Mixing’ is provided, in which links between classification nodes are directed, a conditional probability matrix is associated with each link, and where the numbers of classes can vary from node to node. A posterior class probability at each node is updated by minimizing a divergence between its distribution and that predicted by its neighbors. For arbitrary graphs, as long as each unlabeled point is reachable from at least one training point, a solution generally always exists, is unique, and can be found by solving a sparse linear system iteratively. In one aspect, an automated data classification system is provided. The system includes a data set having at least one labeled category node in the data set. A semi-supervised learning component employs directed arcs to determine the label of at least one other unlabeled category node in the data set.Type: GrantFiled: June 30, 2005Date of Patent: May 3, 2011Assignee: Microsoft CorporationInventors: Christopher J. C. Burges, John C. Platt
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Patent number: 7925651Abstract: A dependency structure is used to divide samples corresponding to items to be ranked into leaf nodes, based on the rank of the items. The dependency structure is trained by splitting or merging training data received at given nodes based on selected features and selected thresholds for those features. A metric is then calculated which is indicative of performance of the node, in splitting the data. The trained structure is then used during runtime to rank items.Type: GrantFiled: January 11, 2007Date of Patent: April 12, 2011Assignee: Microsoft CorporationInventors: Christopher J. C. Burges, Robert L. Rounthwaite
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Publication number: 20100318540Abstract: Described is a technology for identifying sample data items (e.g., documents corresponding to query-URL pairs) having the greatest likelihood of being mislabeled when previously judged, and selecting those data items for re-judging. In one aspect, lambda gradient scores (information associated with ranked sample data items that indicates a relative direction and how “strongly” to move each data item for lowering a ranking cost) are summed for pairs of sample data items to compute re-judgment scores for each of those sample data items. The re-judgment scores indicate a relative likelihood of mislabeling. Once the selected sample data items are re-judged, a new training set is available, whereby a new ranker may be trained.Type: ApplicationFiled: June 15, 2009Publication date: December 16, 2010Applicant: Microsoft CorporationInventors: Krysta M. Svore, Elbio Renato Torres Abib, Christopher J.C. Burges, Bhuvan Middha
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Publication number: 20100281024Abstract: Described herein is a system that includes a receiver component that receives first scores for training points and second scores for the training points, wherein the first scores are individually assigned to the training points by a first ranker component and the second scores are individually assigned to the training points by a second ranker component. The apparatus further includes a determiner component in communication with the receiver component that automatically outputs a value for a parameter ? based at least in part upon the first scores and the second scores, wherein ? is used to linearly combine the first ranker component and the second ranker component.Type: ApplicationFiled: July 15, 2010Publication date: November 4, 2010Applicant: MICROSOFT CORPORATIONInventor: Christopher J.C. Burges