Variational Attention for Commonsense Knowledge Aware Conversation Generation
Bai GR(白桂荣)1,2; He SZ(何世柱)1,2; Liu K(刘康)1,2; Zhao J(赵军)1,2
2019
会议日期2019
会议地点Dunhuang
DOI10.1007/978-3-030- 32233-5_1
页码3-15
英文摘要

Conversation generation is an important task in natural language processing, and commonsense knowledge is vital to provide a shared background for better replying. In this paper, we present a novel commonsense knowledge aware conversation generation model, which adopts variational attention for incorporating commonsense knowledge to generate more appropriate conversation. Given a post, the model retrieves relevant knowledge graphs from a knowledge base, and then attentively incorporates knowledge to its response. For enhancing attention to incorporate more clean and suitable knowledge into response generation, we adopt variational attention rather than standard neural attention on knowledge graphs, which is unlike previous knowledge aware generation models. Experimental results show that the variational attention based model can incorporate more clean and suitable knowledge into response generation.

会议录出版者Technical Committee of Chinese Information, China Computer Federation
会议录出版地Dunhuang
语种英语
内容类型会议论文
源URL[http://ir.ia.ac.cn/handle/173211/48870]  
专题模式识别国家重点实验室_自然语言处理
作者单位1.中国科学院大学人工智能学院
2.中国科学院自动化研究所
推荐引用方式
GB/T 7714
Bai GR,He SZ,Liu K,et al. Variational Attention for Commonsense Knowledge Aware Conversation Generation[C]. 见:. Dunhuang. 2019.
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