"Killing Me" Is Not a Spoiler: Spoiler Detection Model using Graph Neural Networks with Dependency Relation-Aware Attention Mechanism

被引:0
|
作者
Chang, Buru [1 ]
Lee, Inggeol [2 ]
Kim, Hyunjae [2 ]
Kang, Jaewoo [2 ]
机构
[1] Hyperconnect, Seoul, South Korea
[2] Korea Univ, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Several machine learning-based spoiler detection models have been proposed recently to protect users from spoilers on review websites. Although dependency relations between context words are important for detecting spoilers, current attention-based spoiler detection models are insufficient for utilizing dependency relations. To address this problem, we propose a new spoiler detection model called SDGNN that is based on syntax-aware graph neural networks. In the experiments on two real-world benchmark datasets, we show that our SDGNN outperforms the existing spoiler detection models.
引用
收藏
页码:3613 / 3617
页数:5
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