An ensemble of retrieval-based and generation-based human-computer conversation systems

Yiping Song, Cheng Te Li, Jian Yun Nie, Ming Zhang, Dongyan Zhao, Rui Yan

研究成果: Conference contribution

23 引文 斯高帕斯(Scopus)

摘要

Human-computer conversation systems have attracted much attention in Natural Language Processing. Conversation systems can be roughly divided into two categories: retrieval-based and generation-based systems. Retrieval systems search a user-issued utterance (namely a query) in a large conversational repository and return a reply that best matches the query. Generative approaches synthesize new replies. Both ways have certain advantages but suffer from their own disadvantages. We propose a novel ensemble of retrieval-based and generation-based conversation system. The retrieved candidates, in addition to the original query, are fed to a reply generator via a neural network, so that the model is aware of more information. The generated reply together with the retrieved ones then participates in a re-ranking process to find the final reply to output. Experimental results show that such an ensemble system outperforms each single module by a large margin.

原文English
主出版物標題Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018
編輯Jerome Lang
發行者International Joint Conferences on Artificial Intelligence
頁面4382-4388
頁數7
ISBN(電子)9780999241127
DOIs
出版狀態Published - 2018
事件27th International Joint Conference on Artificial Intelligence, IJCAI 2018 - Stockholm, Sweden
持續時間: 2018 七月 132018 七月 19

出版系列

名字IJCAI International Joint Conference on Artificial Intelligence
2018-July
ISSN(列印)1045-0823

Other

Other27th International Joint Conference on Artificial Intelligence, IJCAI 2018
國家Sweden
城市Stockholm
期間18-07-1318-07-19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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