Learning to balance the coherence and diversity of response generation in generation-based chatbots | |
Wang, Shuliang1,2; Li, Dapeng1; Geng, Jing1,2; Yang, Longxing3; Leng, Hongyong1 | |
刊名 | INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS |
2020-07-01 | |
卷号 | 17期号:4页码:11 |
关键词 | Variational autoencoder dialog system deep learning response generation chatbots |
ISSN号 | 1729-8814 |
DOI | 10.1177/1729881420953006 |
英文摘要 | Generating response with both coherence and diversity is a challenging task in generation-based chatbots. It is more difficult to improve the coherence and diversity of dialog generation at the same time in the response generation model. In this article, we propose an improved method that improves the coherence and diversity of dialog generation by changing the model to use gamma sampling and adding attention mechanism to the knowledge-guided conditional variational autoencoder. The experimental results demonstrate that our proposed method can significantly improve the coherence and diversity of knowledge-guided conditional variational autoencoder for response generation in generation-based chatbots at the same time. |
资助项目 | Beijing Municipal Science and Technology Project[Z171100005117002] ; Open Fund of Key Laboratory for National Geographic Census and Monitoring, National Administration of Surveying, Mapping and Geoformation[2017NGCMZD03] |
WOS研究方向 | Robotics |
语种 | 英语 |
出版者 | SAGE PUBLICATIONS INC |
WOS记录号 | WOS:000567168500001 |
内容类型 | 期刊论文 |
源URL | [http://119.78.100.204/handle/2XEOYT63/15502] |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Li, Dapeng; Geng, Jing |
作者单位 | 1.Beijing Inst Technol, Sch Comp Sci & Technol, 5 South St, Beijing 100081, Peoples R China 2.Beijing Inst Technol, Acad E Govt, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Shuliang,Li, Dapeng,Geng, Jing,et al. Learning to balance the coherence and diversity of response generation in generation-based chatbots[J]. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,2020,17(4):11. |
APA | Wang, Shuliang,Li, Dapeng,Geng, Jing,Yang, Longxing,&Leng, Hongyong.(2020).Learning to balance the coherence and diversity of response generation in generation-based chatbots.INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,17(4),11. |
MLA | Wang, Shuliang,et al."Learning to balance the coherence and diversity of response generation in generation-based chatbots".INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 17.4(2020):11. |
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