The performance of recommender systems in online shopping: A user-centric study
We evaluate four approaches to online product search in an extensive user study with real data. The approaches that we study exploit novel preference relaxation methods to recommend products. We compare the results of a user experiment with simulations, using two large sets of products. We show that a particular preference relaxation method improves the decisions of online shoppers.
nr no relaxation sr standard relaxation sbr soft-boundary preference relaxation sbradd soft-boundary preference relaxation with addition sbrrep soft-boundary preference relaxation with replacement