电子学报2024，Vol.52Issue(4)：1377-1388,12.DOI:10.12263/DZXB.20220246
融合特征编码和短语交互感知的隐式篇章关系识别
Implicit Discourse Relation Recognition Integrating Feature Coding and Phrase Interaction Perception
摘要
Abstract
Implicit discourse relation recognition is a challenging task because of its difficulty and universality.From the perspective of argument coding and argument interaction,an implicit discourse relation recognition model integrating feature coding and phrase interaction perception is proposed.The model considers both the characteristics of argument it-self and the interaction characteristics between arguments,and optimizes separately.The part of argument coding incorpo-rates bidirectional long short-term memory(BiLSTM)and recurrent attention convolution neural network(RACNN),which can capture global and local features of arguments in a more comprehensive way;in the part of argument interaction,the se-mantic relationship between arguments is modeled from phrase level,and a mechanism of phrase-level interactive attention is constructed.Also,neural tensor network(NTN)is used to dig into the relational pattern,which can better reflect the po-tential deeper relational relationship between arguments.Experimental results on penn discourse treebank(PDTB)dataset show that the F1 values of this model are superior to other comparison models.关键词
隐式篇章关系识别/双向长短时记忆网络/循环注意力卷积神经网络/短语级交互注意力/神经张量网络Key words
implicit discourse relation recognition/bidirectional long short-term memory/recurrent attention convo-lution neural network/phrase-level interactive attention/neural tensor network分类
信息技术与安全科学引用本文复制引用
王秀利,金方焱..融合特征编码和短语交互感知的隐式篇章关系识别[J].电子学报,2024,52(4):1377-1388,12.基金项目
教育部哲学社会科学研究重大课题攻关项目(No.22JZD011) （No.22JZD011）
中央财经大学新兴交叉学科建设项目 Key Projects of Philosophy and Social Sciences Research,Ministry of Education of the People's Republic of China(No.22JZD011) （No.22JZD011）
Emerging Interdisciplinary Project of CUFE （）
