Typical conversational recommender systems support interactive strategies that are hard-coded in advance and followed rigidly during a recommendation session. In fact, Reinforceme...
Conversational recommender systems have been introduced in Travel and Tourism applications in order to support interactive dialogues which assist users in acquiring their goals, e...
Tariq Mahmood, Francesco Ricci, Adriano Venturini,...
Conventional conversational recommender systems support interaction strategies that are hard-coded into the system in advance. In this context, Reinforcement Learning techniques h...
Abstract. Critiquing techniques provide an easy way for users to feedback their preferences over one or several attributes of the products in a conversational recommender system. W...
In the past conversational recommender systems have adopted a similarity-based approach to recommendation, preferring cases that are similar to some user query or profile. Recent ...
Conversational recommender systems guide users through a product space, alternatively making concrete product suggestions and eliciting the user’s feedback. Critiquing is a comm...
James Reilly, Kevin McCarthy, Lorraine McGinty, Ba...
Conversational recommender systems help to guide users through a product-space towards a particular product that meets their specific requirements. During the course of a “conve...
Kevin McCarthy, James Reilly, Lorraine McGinty, Ba...
Abstract. Conversational recommender systems adapt the sets of products they recommend in light of user feedback. Our contribution here is to devise and compare four different mec...
Current conversational recommender systems are unable to offer guarantees on the quality of their recommendations due to a lack of principled user utility models. We develop an ap...
Conversational recommender systems (CRSs) assist online users in their information-seeking and decision making tasks by supporting an interactive process. Although these processes...