公开(公告)号：US20220019622A1

公开(公告)日：2022-01-20

申请号：US16933947

申请日：2020-07-20

Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

Inventor： 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

IPC: G06F16/901 ,  G06F16/93

Abstract: 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.

公开(公告)号：US20230076773A1

公开(公告)日：2023-03-09

申请号：US17493819

申请日：2021-10-04

Applicant: Microsoft Technology Licensing, LLC

Inventor： 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

IPC: G06F40/30 ,  G06F16/901 ,  G06F16/903

Abstract: 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.

公开(公告)号：US20230067688A1

公开(公告)日：2023-03-02

申请号：US17460123

申请日：2021-08-27

Applicant: Microsoft Technology Licensing, LLC

Inventor： 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

IPC: G06N5/02 ,  G06F40/186

Abstract: 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.

公开(公告)号：US20220342871A1

公开(公告)日：2022-10-27

申请号：US17241217

申请日：2021-04-27

Applicant: Microsoft Technology Licensing, LLC

Inventor： 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

IPC: G06F16/23 ,  G06F7/14 ,  G06F16/28

Abstract: 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.

公开(公告)号：US20220019579A1

公开(公告)日：2022-01-20

申请号：US16933888

申请日：2020-07-20

Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC.

Inventor： 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

IPC: G06F16/2458 ,  G06N3/04 ,  G06N5/04 ,  G06F16/28

Abstract: 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.