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Label-Aware Chinese Event Detection with Heterogeneous Graph Attention Network

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Abstract

Event detection (ED) seeks to recognize event triggers and classify them into the predefined event types. Chinese ED is formulated as a character-level task owing to the uncertain word boundaries. Prior methods try to incorporate word-level information into characters to enhance their semantics. However, they experience two problems. First, they fail to incorporate word-level information into each character the word encompasses, causing the insufficient word-character interaction problem. Second, they struggle to distinguish events of similar types with limited annotated instances, which is called the event confusing problem. This paper proposes a novel model named Label-Aware Heterogeneous Graph Attention Network (L-HGAT) to address these two problems. Specifically, we first build a heterogeneous graph of two node types and three edge types to maximally preserve word-character interactions, and then deploy a heterogeneous graph attention network to enhance the semantic propagation between characters and words. Furthermore, we design a pushing-away game to enlarge the predicting gap between the ground-truth event type and its confusing counterpart for each character. Experimental results show that our L-HGAT model consistently achieves superior performance over prior competitive methods.

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Authors and Affiliations

  1. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100190, China

    Shi-Yao Cui, Bo-Wen Yu, Xin Cong & Ting-Wen Liu

  2. School of Cyber Security, University of Chinese Academy of Sciences, Beijing, 100049, China

    Shi-Yao Cui, Bo-Wen Yu, Xin Cong & Ting-Wen Liu

  3. Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou, 510006, China

    Qing-Feng Tan

  4. School of Cyber Security, Beijing University of Posts and Telecommunications, Beijing, 100088, China

    Jin-Qiao Shi

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  1. Shi-Yao Cui
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  2. Bo-Wen Yu
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Correspondence to Ting-Wen Liu.

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Cui, SY., Yu, BW., Cong, X. et al. Label-Aware Chinese Event Detection with Heterogeneous Graph Attention Network. J. Comput. Sci. Technol. 39, 227–242 (2024). https://doi.org/10.1007/s11390-023-1541-6

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