From "I Like" to "I Prefer" in Collaborative Filtering
Armelle Brun, Ahmad Hamad, Olivier Buffet, Anne Boyer · 2010
Collaborative filtering exploits user preferences, generally ratings, to provide them with recommendations. However, the ratings may not be completely trustworthy: the rating scale is usually reduced and the rating values may be influenced by many factors. This paper is a first attempt at studying the expression of preferences under the form of preference relations where users are asked to compare pairs of resources. First experiments show that this new approach compares with, and sometimes improves, the classical one.