Constructing Chinese Macro Discourse Tree via Multiple Views and Word Pair Similarity

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NETL
Springer Nature

外文摘要：Macro-discourse structure recognition is an important task in macro-discourse analysis。 At present， the research on macro-discourse analysis mostly uses the manual features (e。g。， the position features)， and ignores the semantic information in topic level。 In this paper， we first propose a multi-view neural network to construct Chinese macro discourse trees from three views， i。e。， the word view， the context view and the topic view。 Besides， we propose a novel word-pair similarity mechanism to capture the interaction among the discourse units and the topic。 The experimental results on MCDTB， a Chinese discourse corpus， show that our model outperforms the baseline significantly。

外文关键词：

Macro discourseDiscourse tree constructionWord-pair similarityMultiple views

作者：

Yi Zhou、Xiaomin Chu、Peifeng Li、Qiaoming Zhu

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作者单位：

School of Computer Sciences and Technology, Soochow University, Suzhou, Jiangsu, China

会议名称：

CCF international conference on natural language processing and Chinese computing

会议地点：

Dunhuang(CN)

会议母体文献：

Natural language processing and Chinese computing

页码：

773-786

出版时间：

2019

DOI：

10.1007/978-3-030-32233-5_60