Efficient multiple biomedical events extraction via reinforcement learning

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成果类型：

期刊论文

作者：

Zhao, Weizhong;Zhao, Yao;Jiang, Xingpeng（蒋兴鹏）;He, Tingting（何婷婷）;Liu, Fan;...

通讯作者：

Weizhong Zhao

作者机构：

[Jiang, Xingpeng; He, Tingting; Zhao, Weizhong; Zhao, Yao] Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smar, Wuhan 430079, Hubei, Peoples R China.

[Jiang, Xingpeng; He, Tingting; Zhao, Weizhong; Zhao, Yao] Cent China Normal Univ, Sch Comp, Wuhan 430079, Hubei, Peoples R China.

[Jiang, Xingpeng; He, Tingting; Zhao, Weizhong; Zhao, Yao] Cent China Normal Univ, Natl Language Resources Monitoring & Res Ctr Netw, Wuhan 430079, Hubei, Peoples R China.

[Zhao, Weizhong] Guilin Univ Elect Technol, Guangxi Key Lab Trusted Software, Guilin 541004, Peoples R China.

[Zhao, Weizhong] Guangxi Normal Univ, Guangxi Key Lab Multisource Informat Min & Secur, Guilin 541004, Peoples R China.

通讯机构：

[Weizhong Zhao] H

Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University , Wuhan, Hubei 430079, China<&wdkj&>School of Computer, Central China Normal University, Wuhan, Hubei 430079, China<&wdkj&>National Language Resources Monitoring & Research Center for Network Media, Central China Normal University , Wuhan, Hubei 430079, China<&wdkj&>Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology , Guilin 541004, China<&wdkj&>Guangxi Key Lab of Multi-source Information Mining & Security, Guangxi Normal University , Guilin 541004, China

语种：

英文

期刊：

BIOINFORMATICS

ISSN：

1367-4803

年：

2021

卷：

期：

页码：

1891-1899

DOI：

10.1093/bioinformatics/btab024

基金类别：

National Key Research and Development Program of China [2017YFC0909502]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61532008, 61932008, 61802404, 61872157]; Wuhan Science and Technology Program [20190107010 11392]; Fundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central Universities [CCNU19TD004]; Research Fund of Guangxi Key Lab of Multi-source Information Mining Security [MIMS19-02]; Guangxi Key Laboratory of Trusted Software [kx201905]

机构署名：

本校为第一机构

院系归属：

计算机学院

摘要：

Abstract Motivation Multiple events extraction from biomedical literature is a challenging task for biomedical community. Usually, biomedical event extraction is modeled as two sub-tasks, trigger identification and argument detection. Most existing methods perform these two sub-tasks sequentially, and fail to make full use of the interaction between them, leading to suboptimal results for multiple biomedical events extraction. Results We propose a novel framework of reinforcement learning (RL) for the task of multiple biomedical event...

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Efficient multiple biomedical events extraction via reinforcement learning

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