We examine the problems with automated recommendation systems when information about user preferences is limited. We equate the problem to one of content similarity measurement an...
A conversational recommender system iteratively shows a small set of options for its user to choose between. In order to select these options, the system may analyze the queries tr...
Walid Trabelsi, Nic Wilson, Derek G. Bridge, Franc...
This paper describes the process by which we constructed a user model for ERST - an External Representation Selection Tutor - which recommends external representations (ERs) for pa...
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...
Abstract. Recommender systems face up to current information overload by selecting automatically items that match the personal preferences of each user. The so-called content-based...