Towards Topic-Guided Conversational Recommender System

Understand

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 \textbf{TG-ReDial} (\textbf{Re}commendation through \textbf{T}opic-\textbf{G}uided \textbf{Dial}og).