Invention Grant
- Patent Title: Representation learning method and device based on natural language and knowledge graph
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Application No.: US17124030Application Date: 2020-12-16
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Publication No.: US12019990B2Publication Date: 2024-06-25
- Inventor: Haifeng Wang , Wenbin Jiang , Yajuan Lv , Yong Zhu , Hua Wu
- Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.
- Applicant Address: CN Beijing
- Assignee: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.
- Current Assignee: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.
- Current Assignee Address: CN
- Agency: Dilworth IP, LLC
- Priority: CN 1911297702.X 2019.12.17
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06F18/214 ; G06F18/2413 ; G06F40/279 ; G06F40/30 ; G06N5/022

Abstract:
The present application discloses a text processing method and device based on natural language processing and a knowledge graph, and relates to the in-depth field of artificial intelligence technology. A specific implementation is: an electronic device uses a joint learning model to obtain a semantic representation, which is obtained by the joint learning model by combining knowledge graph representation learning and natural language representation learning, it combines a knowledge graph representation learning and a natural language representation learning, compared to using only the knowledge graph representation learning or the natural language representation learning to learn semantic representation of a prediction object, factors considered by the joint learning model are more in quantity and comprehensiveness, so accuracy of semantic representation can be improved, and thus accuracy of text processing can be improved.
Public/Granted literature
- US20210192364A1 REPRESENTATION LEARNING METHOD AND DEVICE BASED ON NATURAL LANGUAGE AND KNOWLEDGE GRAPH Public/Granted day:2021-06-24
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