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2021 | OriginalPaper | Buchkapitel

Content Selection Network for Document-Grounded Retrieval-Based Chatbots

verfasst von : Yutao Zhu, Jian-Yun Nie, Kun Zhou, Pan Du, Zhicheng Dou

Erschienen in: Advances in Information Retrieval

Verlag: Springer International Publishing

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Abstract

Grounding human-machine conversation in a document is an effective way to improve the performance of retrieval-based chatbots. However, only a part of the document content may be relevant to help select the appropriate response at a round. It is thus crucial to select the part of document content relevant to the current conversation context. In this paper, we propose a document content selection network (CSN) to perform explicit selection of relevant document contents, and filter out the irrelevant parts. We show in experiments on two public document-grounded conversation datasets that CSN can effectively help select the relevant document contents to the conversation context, and it produces better results than the state-of-the-art approaches. Our code and datasets are available at https://github.com/DaoD/CSN.

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Titel: Content Selection Network for Document-Grounded Retrieval-Based Chatbots
verfasst von: Yutao Zhu
Jian-Yun Nie
Kun Zhou
Pan Du
Zhicheng Dou
Verlag: Springer International Publishing
Buch: Advances in Information Retrieval
Print ISBN: 978-3-030-72112-1

Electronic ISBN: 978-3-030-72113-8

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-72113-8_50

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