Given a set of rating data for a set of items, determining the values of items is a matter of importance and various probability models have been proposed. The Plackett-Luce model ...
We investigate two recommendation approaches suitable for online multimedia sharing services. Our first approach, UserRank, recommends items by global interestingness irrespective...
The majority of recommender systems are designed to make recommendations for individual users. However, in some circumstances the items to be selected are not intended for persona...
Linas Baltrunas, Tadas Makcinskas, Francesco Ricci
Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of it...
This paper presents a statistical model for expressing preferences through rankings, when the number of alternatives (items to rank) is large. A human ranker will then typically r...