Implicit discourse relation detection using concatenated word embeddings and a gated relevance network
Implicit discourse relation detection using concatenated word embeddings and a gated relevance network作者机构：Shanghai Key Laboratory of Data Science School of Computer Science Fudan University
出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))
年 卷 期：2019年第62卷第11期
页 面：195-197页
核心收录：
学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：partially funded by National Natural Science Foundation of China(Grant Nos.61532011,61473092,61472088) Science and Technology Commission Shanghai Municipality(Grant Nos.16JC1420401,17JC1420200)
主 题：Implicit discourse relation detection using concatenated word embeddings and a gated relevance network
摘 要：Dear editor,Discourse relation detection involves recognizing the relationships between pairs of discourse fragments (e.g., clauses or sentences). As compared with explicit detection, implicit discourse relation detection is much more challenging, owing to connective words, such as so or because, being ab-
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