Surveys on the application of neural networks to event extraction

作     者：Duan Li Chen Lin Luo Bing Duan Li;Chen Lin;Luo Bing

作者机构：School of Electronic EngineeringNaval University of EngineeringWuhan 430033China 

出 版 物：《The Journal of China Universities of Posts and Telecommunications》 (中国邮电高校学报（英文版）)

年 卷 期：2023年第30卷第4期

页      面：43-54,66页

核心收录：

学科分类：08[工学] 081104[工学-模式识别与智能系统] 081203[工学-计算机应用技术] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China(U21A20488)。 

主　　题：event extraction natural language processing event extraction methods neural networks 

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.