Patents by Inventor Pavel MYSHKOV
Pavel MYSHKOV 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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Publication number: 20230076773Abstract: In various examples there is a computer-implemented method of database construction. The method comprises storing a knowledge graph comprising nodes connected by edges, each node representing a topic. Accessing a topic type hierarchy comprising a plurality of types of topics, the topic type hierarchy having been computed from a corpus of text documents. One or more text documents are accessed and the method involves labelling a plurality of the nodes with one or more labels, each label denoting a topic type from the topic type hierarchy, by, using a deep language model; or for an individual one of the nodes representing a given topic, searching the accessed text documents for matches to at least one template, the template being a sequence of words and containing the given topic and a placeholder for a topic type; and storing the knowledge graph comprising the plurality of labelled nodes.Type: ApplicationFiled: October 4, 2021Publication date: March 9, 2023Inventors: Elena POCHERNINA, John WINN, Matteo VENANZI, Ivan KOROSTELEV, Pavel MYSHKOV, Samuel Alexander WEBSTER, Yordan Kirilov ZAYKOV, Nikita VORONKOV, Dmitriy MEYERZON, Marius Alexandru BUNESCU, Alexander Armin SPENGLER, Vladimir GVOZDEV, Thomas P. MINKA, Anthony Arnold WIESER, Sanil RAJPUT, John GUIVER
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Publication number: 20230067688Abstract: In various examples there is a computer-implemented method of database construction. The method comprises storing a knowledge graph comprising nodes connected by edges, each node representing a topic. Accessing a topic type hierarchy comprising a plurality of types of topics, the topic type hierarchy having been computed from a corpus of text documents. One or more text documents are accessed and the method involves labelling a plurality of the nodes with one or more labels, each label denoting a topic type from the topic type hierarchy, by, using a deep language model; or for an individual one of the nodes representing a given topic, searching the accessed text documents for matches to at least one template, the template being a sequence of words and containing the given topic and a placeholder for a topic type; and storing the knowledge graph comprising the plurality of labelled nodes.Type: ApplicationFiled: August 27, 2021Publication date: March 2, 2023Inventors: Elena POCHERNINA, John WINN, Matteo VENANZI, Ivan KOROSTELEV, Pavel MYSHKOV, Samuel Alexander WEBSTER, Yordan Kirilov ZAYKOV, Nikita VORONKOV, Dmitriy MEYERZON, Marius Alexandru BUNESCU, Alexander Armin SPENGLER, Vladimir GVOZDEV, Thomas P. MINKA, Anthony Arnold WIESER, Sanil RAJPUT
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Patent number: 11573967Abstract: Examples described herein generally relate to a computer system including a knowledge graph storing a plurality of entities. A mining of a set of enterprise source documents within an enterprise intranet is performed, by a plurality of knowledge mining toolkits, to determine a plurality of entity names. The plurality of entity names are linked based on entity metadata by traversing various relationships between people, files, sites, groups, associated with entities. An entity record is generated within a knowledge graph for a mined entity name from the linked entity names based on an entity schema and ones of the set of enterprise source documents associated with the mined entity name. The entity record includes attributes aggregated from the ones of the set of enterprise source documents associated with the mined entity name.Type: GrantFiled: July 20, 2020Date of Patent: February 7, 2023Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Dmitriy Meyerzon, Omar Zia Khan, Hui Li, Vladimir V. Gvozdev, John M. Winn, John Guiver, Ivan Korostelev, Matteo Venanzi, Alexander Armin Spengler, Pavel Myshkov, Elena Pochernina, Martin Kukla, Yordan Kirilov Zaykov
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Patent number: 11544323Abstract: Mining of a set of enterprise source documents within an enterprise intranet is performed, by a plurality of knowledge mining toolkits, to determine a plurality of entity names. A plurality of entity records are generated within a knowledge graph for mined entity names from the entity names based on an entity schema and ones of the set of enterprise source documents associated with the mined entity names. Pattern recognition is applied to an active document using an enterprise named entity recognition (ENER) system to identify potential entity names within the document that match a respective one of a plurality of entity records in the knowledge graph. One or more matching entity names are annotated within the document with information from the knowledge graph for the respective ones of the plurality of entity records. The annotated information is displayed with the active document.Type: GrantFiled: July 20, 2020Date of Patent: January 3, 2023Assignee: MICROSOFT TECHNOLOGY LICENSING, LLCInventors: Dmitriy Meyerzon, Omar Zia Khan, Hui Li, John M. Winn, John Guiver, Ivan Korostelev, Matteo Venanzi, Alexander Armin Spengler, Pavel Myshkov, Elena Pochernina, Martin Kukla, Yordan Kirilov Zaykov, Junyi Chai, Noura Farra, Sravya Narala
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Publication number: 20220342871Abstract: Examples of the present disclosure describe systems and methods for cross-provider topic conflation. In aspects, a request relating to one or more topics may be received by a content surfacing platform. One or more data sources of multiple content providers may be searched for documents relating to the topic(s). Document content (e.g., document metadata and sentences, phrases, and other word content within the document) relating to the topic(s) may be extracted from the documents of the various content providers. The document content may be classified and/or separated into subparts. The subparts may be clustered and/or conflated by topic, thereby removing duplicated data while preserving the unique information in each subpart. The conflated topics may be stored in a single knowledge base, such as an enterprise knowledge graph, and/or presented in response to the request.Type: ApplicationFiled: April 27, 2021Publication date: October 27, 2022Applicant: Microsoft Technology Licensing, LLCInventors: Matteo VENANZI, John M. WINN, Ivan KOROSTELEV, Elena POCHERNINA, Samuel WEBSTER, Pavel MYSHKOV, Yordan ZAYKOV, Dmitriy MEYERZON, Vladimir V. GVOZDEV, Nikita VORONKOV, Alexander A. SPENGLER
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Patent number: 11348022Abstract: Methods for providing a computer implemented medical diagnosis are provided. In one aspect, a method includes receiving an input from a user comprising at least one symptom of the user, and providing the at least one symptom as an input to a medical model. The method also includes deriving estimates of the probability of the user having a disease from the discriminative model, inputting the estimates to the inference engine, performing approximate inference on the probabilistic graphical model to obtain a prediction of the probability that the user has that disease, and outputting the probability of the user having the disease for display by a display device.Type: GrantFiled: February 15, 2019Date of Patent: May 31, 2022Assignee: Babylon Partners LimitedInventors: Laura Helen Douglas, Pavel Myshkov, Robert Walecki, Iliyan Radev Zarov, Konstantinos Gourgoulias, Christopher Lucas, Christopher Robert Hart, Adam Philip Baker, Maneesh Sahani, Iurii Perov, Saurabh Johri
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Patent number: 11328215Abstract: Methods for providing a computer implemented medical diagnosis are provided. In one aspect, a method includes receiving an input from a user comprising at least one symptom of the user, and providing the at least one symptom as an input to a medical model. The method also includes deriving estimates of the probability of the user having a disease from the discriminative model, inputting the estimates to the inference engine, performing approximate inference on the probabilistic graphical model to obtain a prediction of the probability that the user has that disease, and outputting the probability of the user having the disease for display by a display device.Type: GrantFiled: February 15, 2019Date of Patent: May 10, 2022Assignee: Babylon Partners LimitedInventors: Laura Helen Douglas, Pavel Myshkov, Robert Walecki, Iliyan Radev Zarov, Konstantinos Gourgoulias, Christopher Lucas, Christopher Robert Hart, Adam Philip Baker, Maneesh Sahani, Iurii Perov, Saurabh Johri
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Publication number: 20220019579Abstract: Examples described herein generally relate to a computer system including a knowledge graph storing a plurality of entities. A mining of a set of enterprise source documents within an enterprise intranet is performed, by a plurality of knowledge mining toolkits, to determine a plurality of entity names. The plurality of entity names are linked based on entity metadata by traversing various relationships between people, files, sites, groups, associated with entities. An entity record is generated within a knowledge graph for a mined entity name from the linked entity names based on an entity schema and ones of the set of enterprise source documents associated with the mined entity name. The entity record includes attributes aggregated from the ones of the set of enterprise source documents associated with the mined entity name.Type: ApplicationFiled: July 20, 2020Publication date: January 20, 2022Inventors: Dmitriy MEYERZON, Omar Zia KHAN, Hui LI, Vladimir V. GVOZDEV, John M. WINN, John GUIVER, Ivan KOROSTELEV, Matteo VENANZI, Alexander Armin SPENGLER, Pavel MYSHKOV, Elena POCHERNINA, Martin KUKLA, Yordan Kirilov ZAYKOV
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Publication number: 20220019622Abstract: Mining of a set of enterprise source documents within an enterprise intranet is performed, by a plurality of knowledge mining toolkits, to determine a plurality of entity names. A plurality of entity records are generated within a knowledge graph for mined entity names from the entity names based on an entity schema and ones of the set of enterprise source documents associated with the mined entity names. Pattern recognition is applied to an active document using an enterprise named entity recognition (ENER) system to identify potential entity names within the document that match a respective one of a plurality of entity records in the knowledge graph. One or more matching entity names are annotated within the document with information from the knowledge graph for the respective ones of the plurality of entity records. The annotated information is displayed with the active document.Type: ApplicationFiled: July 20, 2020Publication date: January 20, 2022Inventors: Dmitriy MEYERZON, Omar Zia KHAN, Hui LI, John M. WINN, John GUIVER, Ivan KOROSTELEV, Matteo VENANZI, Alexander Armin SPENGLER, Pavel MYSHKOV, Elena POCHERNINA, Martin KUKLA, Yordan Kirilov ZAYKOV, Junyi CHAI, Noura FARRA, Sravya NARALA
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Publication number: 20210358624Abstract: Methods for providing a computer implemented medical diagnosis are provided. In one aspect, a method includes receiving an input from a user comprising at least one symptom of the user, and providing the at least one symptom as an input to a medical model. The method also includes deriving estimates of the probability of the user having a disease from the discriminative model, inputting the estimates to the inference engine, performing approximate inference on the probabilistic graphical model to obtain a prediction of the probability that the user has that disease, and outputting the probability of the user having the disease for display by a display device.Type: ApplicationFiled: October 31, 2018Publication date: November 18, 2021Inventors: Laura Helen DOUGLAS, Pavel MYSHKOV, Robert WALECKI, Iliyan Radev ZAROV, Konstantinos GOURGOULIAS, Christopher LUCAS, Christopher Robert HART, Adam Philip BAKER, Maneesh SAHANI, Iurii PEROV, Saurabh JOHRI
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Publication number: 20190251461Abstract: Methods for providing a computer implemented medical diagnosis are provided. In one aspect, a method includes receiving an input from a user comprising at least one symptom of the user, and providing the at least one symptom as an input to a medical model. The method also includes deriving estimates of the probability of the user having a disease from the discriminative model, inputting the estimates to the inference engine, performing approximate inference on the probabilistic graphical model to obtain a prediction of the probability that the user has that disease, and outputting the probability of the user having the disease for display by a display device.Type: ApplicationFiled: February 15, 2019Publication date: August 15, 2019Inventors: Laura Helen DOUGLAS, Pavel MYSHKOV, Robert WALECKI, Iliyan Radev ZAROV, Konstantinos GOURGOULIAS, Christopher LUCAS, Christopher Robert HART, Adam Philip BAKER, Maneesh SAHANI, Iurii PEROV, Saurabh JOHRI
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Publication number: 20190252076Abstract: Methods for providing a computer implemented medical diagnosis are provided. In one aspect, a method includes receiving an input from a user comprising at least one symptom of the user, and providing the at least one symptom as an input to a medical model. The method also includes deriving estimates of the probability of the user having a disease from the discriminative model, inputting the estimates to the inference engine, performing approximate inference on the probabilistic graphical model to obtain a prediction of the probability that the user has that disease, and outputting the probability of the user having the disease for display by a display device.Type: ApplicationFiled: February 15, 2019Publication date: August 15, 2019Inventors: Laura Helen DOUGLAS, Pavel MYSHKOV, Robert WALECKI, Iliyan Radev ZAROV, Konstantinos GOURGOULIAS, Christopher LUCAS, Christopher Robert HART, Adam Philip BAKER, Maneesh SAHANI, Iurii PEROV, Saurabh JOHRI
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Publication number: 20190180841Abstract: Methods for providing a computer implemented medical diagnosis are provided. In one aspect, a method includes receiving an input from a user comprising at least one symptom of the user, and providing the at least one symptom as an input to a medical model. The method also includes deriving estimates of the probability of the user having a disease from the discriminative model, inputting the estimates to the inference engine, performing approximate inference on the probabilistic graphical model to obtain a prediction of the probability that the user has that disease, and outputting the probability of the user having the disease for display by a display device.Type: ApplicationFiled: February 15, 2019Publication date: June 13, 2019Inventors: Laura Helen DOUGLAS, Pavel MYSHKOV, Robert WALECKI, Iliyan Radev ZAROV, Konstantinos GOURGOULIAS, Christopher LUCAS, Christopher Robert HART, Adam Philip BAKER, Maneesh SAHANI, Iurii PEROV, Saurabh JOHRI