Patents by Inventor Gregory T. Buehrer
Gregory T. Buehrer 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: 9477654Abstract: Functionality is described herein for transforming first and second symbolic linguistic items into respective first and second continuous-valued concept vectors, using a deep learning model, such as a convolutional latent semantic model. The model is designed to capture both the local and global linguistic contexts of the linguistic items. The functionality then compares the first concept vector with the second concept vector to produce a similarity measure. More specifically, the similarity measure expresses the closeness between the first and second linguistic items in a high-level semantic space. In one case, the first linguistic item corresponds to a query, and the second linguistic item may correspond to a phrase, or a document, or a keyword, or an ad, etc. In one implementation, the convolutional latent semantic model is produced in a training phase based on click-through data.Type: GrantFiled: April 1, 2014Date of Patent: October 25, 2016Assignee: Microsoft CorporationInventors: Xiaodong He, Jianfeng Gao, Li Deng, Qiang Lou, Yunhong Zhou, Guowei Liu, Gregory T. Buehrer, Jianchang Mao, Yelong Shen, Ruofei Zhang
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Publication number: 20150278200Abstract: Functionality is described herein for transforming first and second symbolic linguistic items into respective first and second continuous-valued concept vectors, using a deep learning model, such as a convolutional latent semantic model. The model is designed to capture both the local and global linguistic contexts of the linguistic items. The functionality then compares the first concept vector with the second concept vector to produce a similarity measure. More specifically, the similarity measure expresses the closeness between the first and second linguistic items in a high-level semantic space. In one case, the first linguistic item corresponds to a query, and the second linguistic item may correspond to a phrase, or a document, or a keyword, or an ad, etc. In one implementation, the convolutional latent semantic model is produced in a training phase based on click-through data.Type: ApplicationFiled: April 1, 2014Publication date: October 1, 2015Applicant: Microsoft CorporationInventors: Xiaodong He, Jianfeng Gao, Li Deng, Qiang Lou, Yunhong Zhou, Guowei Liu, Gregory T. Buehrer, Jianchang Mao, Yelong Shen, Ruofei Zhang
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Patent number: 8977625Abstract: Methods, systems, and media are provided for facilitating generation of an inference index. In embodiments, a canonical entity is referenced. The canonical entity is associated with web documents. One or more queries that, when input, result in a selection of at least one of the web documents are identified. An entity document is generated for the canonical entity. The entity document includes the identified queries and/or associated text from the content of a document or from an entity title that result in the selection of the at least one of the web documents. The entity document and corresponding canonical entity can be combined with additional related entity documents and canonical entities to generate an inference index.Type: GrantFiled: December 15, 2010Date of Patent: March 10, 2015Assignee: Microsoft Technology Licensing, LLCInventors: Gregory T. Buehrer, Li Jiang, Paul Alfred Viola, Andrew Paul McGovern, Jakub Jan Szymanski, Sanaz Ahari
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Publication number: 20120158738Abstract: Methods, systems, and media are provided for facilitating generation of an inference index. In embodiments, a canonical entity is referenced. The canonical entity is associated with web documents. One or more queries that, when input, result in a selection of at least one of the web documents are identified. An entity document is generated for the canonical entity. The entity document includes the identified queries and/or associated text from the content of a document or from an entity title that result in the selection of the at least one of the web documents. The entity document and corresponding canonical entity can be combined with additional related entity documents and canonical entities to generate an inference index.Type: ApplicationFiled: December 15, 2010Publication date: June 21, 2012Applicant: MICROSOFT CORPORATIONInventors: Gregory T. Buehrer, Li Jiang, Paul Alfred Viola, Andrew Paul McGovern, Jakub Jan Szymanski, Sanaz Ahari
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Patent number: 7912818Abstract: A method and a processing device are provided for compressing a web graph including multiple nodes and links between the multiple nodes. Nodes of the web graph may be clustered into groups including no more than a predetermined number of nodes. A list of links of the clustered nodes may be created and sorted based on a frequency of occurrence of each of the links. A prefix tree may be created based on the sorted list of links. The prefix tree may be walked to find candidate virtual nodes. The candidate virtual nodes may be analyzed according to a selection criteria and a virtual node may be selected. The prefix tree may be adjusted to account for the selection of the virtual node and the virtual node may be added to the web graph.Type: GrantFiled: September 13, 2010Date of Patent: March 22, 2011Assignee: Microsoft CorporationInventors: Gregory T. Buehrer, Kumar Hemachandra Chellapilla
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Publication number: 20100332476Abstract: A method and a processing device are provided for compressing a web graph including multiple nodes and links between the multiple nodes. Nodes of the web graph may be clustered into groups including no more than a predetermined number of nodes. A list of links of the clustered nodes may be created and sorted based on a frequency of occurrence of each of the links. A prefix tree may be created based on the sorted list of links. The prefix tree may be walked to find candidate virtual nodes. The candidate virtual nodes may be analyzed according to a selection criteria and a virtual node may be selected. The prefix tree may be adjusted to account for the selection of the virtual node and the virtual node may be added to the web graph.Type: ApplicationFiled: September 13, 2010Publication date: December 30, 2010Applicant: MICROSOFT CORPORATIONInventors: Gregory T. Buehrer, Kumar Hemachandra Chellapilla
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Patent number: 7818303Abstract: A method and a processing device are provided for compressing a web graph including multiple nodes and links between the multiple nodes. Nodes of the web graph may be clustered into groups including no more than a predetermined number of nodes. A list of links of the clustered nodes may be created and sorted based on a frequency of occurrence of each of the links. A prefix tree may be created based on the sorted list of links. The prefix tree may be walked to find candidate virtual nodes. The candidate virtual nodes may be analyzed according to a selection criteria and a virtual node may be selected. The prefix tree may be adjusted to account for the selection of the virtual node and the virtual node may be added to the web graph.Type: GrantFiled: January 29, 2008Date of Patent: October 19, 2010Assignee: Microsoft CorporationInventors: Gregory T. Buehrer, Kumar Hemachandra Chellapilla
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Publication number: 20090193044Abstract: A method and a processing device are provided for compressing a web graph including multiple nodes and links between the multiple nodes. Nodes of the web graph may be clustered into groups including no more than a predetermined number of nodes. A list of links of the clustered nodes may be created and sorted based on a frequency of occurrence of each of the links. A prefix tree may be created based on the sorted list of links. The prefix tree may be walked to find candidate virtual nodes. The candidate virtual nodes may be analyzed according to a selection criteria and a virtual node may be selected. The prefix tree may be adjusted to account for the selection of the virtual node and the virtual node may be added to the web graph.Type: ApplicationFiled: January 29, 2008Publication date: July 30, 2009Applicant: MICROSOFT CORPORATIONInventors: Gregory T. Buehrer, Kumar Hemachandra Chellapilla