Memory Augmented Attention Model for Chinese Implicit Discourse Relation Recognition

摘要：

　　Recently,Chinese implicit discourse relation recognition has attracted more and more attention,since it is crucial to understand the Chinese discourse text.In this paper,we propose a novel memory augmented attention model which represents the arguments using an attention-based neural network and preserves the crucial information with an external memory network which captures each discourse relation clustering structure to support the relation inference.Exten-sive experiments demonstrate that our proposed model can achieve the new state-of-the-art results on Chinese Discourse Treebank.We further leverage network visualization to show why our attention and memory model are effective.

关键词： Chinese Implicit Relation Recognition Memory Agumented Neural Network Attention Neural Model

作者: Yang Liu Jiajun Zhang Chengqing Zong

作者单位: Institute of automation,Chinese Academy of Sciences

会议类型: 国内会议

会议名称: 第十六届全国计算语言学学术会议暨第五届基于自然标注大数据的自然语言处理国际学术研讨会

会议地点: 南京

会议语种:英文

页码: 1-12

在线出版日期: 2017-10-13（万方平台首次上网日期，不代表论文的发表时间）