In this work, We delve into the interactions between CC and RC, with the goal of building an
effective and practical CRS. Specifically, we propose a new CRS framework named …

Recommender systems are embracing conversational technologies to obtain user
preferences dynamically, and to overcome inherent limitations of their static models. A …

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 …

State-of-the-art methods on conversational recommender systems (CRS) leverage external
knowledge to enhance both items' and contextual words' representations to achieve high …

Recently, conversational recommender system (CRS) has become an emerging and
practical research topic. Most of the existing CRS methods focus on learning effective …

Conversational recommender systems (CRS) aim to recommend relevant items to users by
eliciting user preference through natural language conversation. Prior work often utilizes …

Conversational recommender systems (CRS) dynamically obtain the users' preferences via
multi-turn questions and answers. The existing CRS solutions are widely dominated by deep …

Conversational Recommender System (CRS), which aims to recommend high-quality items
to users through interactive conversations, has gained great research interest recently. A …

In recent years, conversational recommender system (CRS) has received much attention in
the research community. However, existing studies on CRS vary in scenarios, goals and …

Conversational recommender systems (CRS) enable traditional recommender systems to
interact with users by asking questions about attributes and recommending items. The …