Title:
ENTITY RELATION MINING METHOD BASED ON BIOMEDICAL LITERATURE
Document Type and Number:
WIPO Patent Application WO/2021/190236
Kind Code:
A1
Abstract:
Disclosed in the present invention are an entity relation mining method based on biomedical literature, comprising the following steps: querying disease-related biomedical literature in a public database, and performing data preprocessing to obtain biomedical text data; performing biomedical named entity recognition on the obtained biomedical text data in combination with a regular matching template and a deep learning model; and mining entity relations on the basis of the entity recognition result by transfer learning and reinforcement learning methods. According to the present invention, by obtaining disease-related biomedical literature from a network, extracting abstracts and the titles and performing entity recognition and relation mining, biomedical named entities in the literature can be effectively recognized and hidden relations among various entities can be mined.
Inventors:
CHEN MING (CN)
CHEN QI (CN)
ZHOU YINCONG (CN)
HU DAHUI (CN)
WU WENYI (CN)
CHEN QI (CN)
ZHOU YINCONG (CN)
HU DAHUI (CN)
WU WENYI (CN)
Application Number:
PCT/CN2021/077892
Publication Date:
September 30, 2021
Filing Date:
February 25, 2021
Export Citation:
Assignee:
UNIV ZHEJIANG (CN)
International Classes:
G06F16/35
Foreign References:
| CN111428036A | 2020-07-17 | |||
| CN107609163A | 2018-01-19 | |||
| CN109871538A | 2019-06-11 | |||
| CN109446338A | 2019-03-08 | |||
| US20200065374A1 | 2020-02-27 |
Other References:
LUO ZHE-HENG, TONG FAN, ZHAO DONG-SHENG: "An integrated algorithm based on deep neural network and regular expression patterns to recognize gene mutation entities in biomedical literature", MILITARY MEDICAL SCIENCES, CN, vol. 42, no. 11, 25 November 2018 (2018-11-25), CN, pages 872 - 876, XP055852841, ISSN: 1674-9960, DOI: 10.7644/j.issn.1674-9960.2018.11.015
Attorney, Agent or Firm:
FANG & ASSOCIATES (CN)
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