Abstract. This paper presents a unifying framework to model casebased reasoning recommender systems (CBR-RSs). CBR-RSs have complex architectures and specialize the CBR problem sol...
Initial successes in the area of recommender systems have led to considerable early optimism. However as a research community, we are still in the early days of our understanding ...
Abstract. We develop a model of Parametric Probabilistic Transition Systems, where probabilities associated with transitions may be parameters. We show how to find instances of th...
Ruggero Lanotte, Andrea Maggiolo-Schettini, Angelo...
Recommender systems, notably collaborative and hybrid information filtering approaches, vitally depend on neighborhood formation, i.e., selecting small subsets of most relevant pee...
Collaborative filtering (CF) recommender systems are very popular and successful in commercial application fields. However, robustness analysis research has shown that conventional...