Current recommender systems have to cope with a certain reservation because they are considered to be hard to maintain and to give rather schematic advice. This paper presents an a...
This research proposes a decision aid based on a novel type of preference relaxation, which enables consumers to easily make quality choices in online multiattribute choice scenari...
In this paper, we describe area of recommender systems, with focus on user preference learning problem. We describe such system and identify some interesting problems. We will comp...
A recommender system has to collect users' preference data. To collect such data, rating or scoring methods that use rating scales, such as good-fair-poor or a five-point-sca...
Typical conversational recommender systems support interactive strategies that are hard-coded in advance and followed rigidly during a recommendation session. In fact, Reinforceme...