期刊论文

Zhao, Weizhong;Yang, Jincai

英文

Information Sciences

0020-0255

2021

550

27-40

10.1016/j.ins.2020.10.047

The work is partially supported by the National Key Research and Development Program of China (2017YFC0909502), the National Natural Science Foundation of China (No. 61532008, No. 61932008, No. 61762078 and No. 61966004), the Wuhan Science and Technology Program (2019010701011392), the Fundamental Research Funds for the Central Universities (CCNU19TD004), Research Fund of Guangxi Key Lab of Multi-source Information Mining & Security (MIMS19-02), and the Guangxi Key Laboratory of Trusted Software (No. kx201905). Authors are grateful to the anonymous reviewers for helpful comments.

本校为第一且通讯机构

With the rapid development of information technology, the amount of textual data generated in biomedical field becomes larger and larger. Biomedical event extraction, which is a fundamental information extraction task, has gained a growing interest in biomedical community. Although researchers have proposed various approaches to this task, the performance is still undesirable since previous approaches fail to model biomedical documents effectively. In this paper, we propose an end-to-end framework for document-level joint biomedical event extraction. To better capture the complex relationships...