Towards Topic-Guided Conversational Recommender System

Kun Zhou, Yuanhang Zhou, Wayne Xin Zhao, Xiaoke Wang, Ji-Rong Wen

Abstract
Conversational recommender systems (CRS) aim to recommend high-quality items to users through interactive conversations. To develop an effective CRS, the support of high-quality datasets is essential. Existing CRS datasets mainly focus on immediate requests from users, while lack proactive guidance to the recommendation scenario. In this paper, we contribute a new CRS dataset named TG-ReDial (Recommendation through Topic-Guided Dialog). Our dataset has two major features. First, it incorporates topic threads to enforce natural semantic transitions towards the recommendation scenario. Second, it is created in a semi-automatic way, hence human annotation is more reasonable and controllable. Based on TG-ReDial, we present the task of topic-guided conversational recommendation, and propose an effective approach to this task. Extensive experiments have demonstrated the effectiveness of our approach on three sub-tasks, namely topic prediction, item recommendation and response generation. TG-ReDial is available at bluehttps://github.com/RUCAIBox/TG-ReDial.
Anthology ID:
2020.coling-main.365
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
4128–4139
Language:
URL:
https://aclanthology.org/2020.coling-main.365
DOI:
10.18653/v1/2020.coling-main.365
Bibkey:
Cite (ACL):
Kun Zhou, Yuanhang Zhou, Wayne Xin Zhao, Xiaoke Wang, and Ji-Rong Wen. 2020. Towards Topic-Guided Conversational Recommender System. In Proceedings of the 28th International Conference on Computational Linguistics, pages 4128–4139, Barcelona, Spain (Online). International Committee on Computational Linguistics.
Cite (Informal):
Towards Topic-Guided Conversational Recommender System (Zhou et al., COLING 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2020.coling-main.365.pdf
Code
 RUCAIBox/TG-ReDial +  additional community code
Data
TG-ReDial, ConceptNet, Douban, DuRecDial, ReDial
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