Abstract
Conversational recommender systems (CRSs) capture a user preference through a conversation. However, the existing CRSs lack capturing comprehensive user preferences. This is because the items mentioned in a conversation are mainly regarded as a user preference. Thus, they have limitations in identifying a user preference from a dialogue context expressed without preferred items. Inspired by the characteristic of an online recommendation community where participants identify a context of a recommendation request and then comment with appropriate items, we exploit the Reddit data. Specifically, we propose a Contrastive Learning approach for Injecting Contextual Knowledge (CLICK) from the Reddit data to the CRS task, which facilitates the capture of a context-level user preference from a dialogue context, regardless of the existence of preferred item-entities. Moreover, we devise a relevance-enhanced contrastive learning loss to consider the fine-grained reflection of multiple recommendable items. We further develop a response generation module to generate a persuasive rationale for a recommendation. Extensive experiments on the benchmark CRS dataset show the effectiveness of CLICK, achieving significant improvements over state-of-the-art methods.- Anthology ID:
- 2023.eacl-main.137
- Volume:
- Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
- Month:
- May
- Year:
- 2023
- Address:
- Dubrovnik, Croatia
- Editors:
- Andreas Vlachos, Isabelle Augenstein
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1875–1885
- Language:
- URL:
- https://aclanthology.org/2023.eacl-main.137
- DOI:
- 10.18653/v1/2023.eacl-main.137
- Cite (ACL):
- Hyeongjun Yang, Heesoo Won, Youbin Ahn, and Kyong-Ho Lee. 2023. CLICK: Contrastive Learning for Injecting Contextual Knowledge to Conversational Recommender System. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, pages 1875–1885, Dubrovnik, Croatia. Association for Computational Linguistics.
- Cite (Informal):
- CLICK: Contrastive Learning for Injecting Contextual Knowledge to Conversational Recommender System (Yang et al., EACL 2023)
- PDF:
- https://preview.aclanthology.org/revert-3132-ingestion-checklist/2023.eacl-main.137.pdf