Surveys on the application of neural networks to event extraction

doi:10.19682/j.cnki.1005-8885.2023.2015

中国邮电高校学报(英文) ›› 2023, Vol. 30 ›› Issue (4): 43-54.doi: 10.19682/j.cnki.1005-8885.2023.2015

• Artificial Intelligence • 上一篇下一篇

Surveys on the application of neural networks to event extraction

Duan Li, Chen Lin, Luo Bing

School of Electronic Engineering, Naval University of Engineering, Wuhan 430033, China

收稿日期:2022-02-26 修回日期:2022-11-08 接受日期:2023-08-31 出版日期:2023-08-31 发布日期:2023-08-31
通讯作者: Chen Lin, E-mail: forever_chenlin@126.com E-mail:forever_chenlin@126.com
基金资助:
This work was supported by the National Natural Science Foundation of China (U21A20488).

Surveys on the application of neural networks to event extraction

Duan Li, Chen Lin, Luo Bing

School of Electronic Engineering, Naval University of Engineering, Wuhan 430033, China

Received:2022-02-26 Revised:2022-11-08 Accepted:2023-08-31 Online:2023-08-31 Published:2023-08-31
Contact: Chen Lin, E-mail: forever_chenlin@126.com E-mail:forever_chenlin@126.com
Supported by:
This work was supported by the National Natural Science Foundation of China (U21A20488).

摘要/Abstract

摘要： Event extraction (EE) is a significant part of natural language information extraction, and it is widely adopted in other natural language processing (NLP) tasks such as question answering and machine reading comprehension. With the development of the NLP field, numerous datasets and approaches for EE are promoted, raising the need for a comprehensive review. In this paper, the resources for EE are reviewed, and then the numerous neural network models currently employed in EE tasks are classified into three types: Word sequence-based methods, graph-based neural network methods, and external knowledge-based approaches. And then the methods are compared and contrasted in detail, and their flaws and difficulties are analyzed with existing research in this survey. Finally, the future research tendency is discussed for EE.

关键词: event extraction, natural language processing, event extraction methods, neural networks

Abstract: Event extraction (EE) is a significant part of natural language information extraction, and it is widely adopted in other natural language processing (NLP) tasks such as question answering and machine reading comprehension. With the development of the NLP field, numerous datasets and approaches for EE are promoted, raising the need for a comprehensive review. In this paper, the resources for EE are reviewed, and then the numerous neural network models currently employed in EE tasks are classified into three types: Word sequence-based methods, graph-based neural network methods, and external knowledge-based approaches. And then the methods are compared and contrasted in detail, and their flaws and difficulties are analyzed with existing research in this survey. Finally, the future research tendency is discussed for EE.

Key words: event extraction, natural language processing, event extraction methods, neural networks

Duan Li, Chen Lin, Luo Bing. Surveys on the application of neural networks to event extraction[J]. The Journal of China Universities of Posts and Telecommunications, 2023, 30(4): 43-54.

参考文献

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Surveys on the application of neural networks to event extraction

Surveys on the application of neural networks to event extraction

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