An investigation on the serendipity problem in recommender systems. Issue 5 (September 2015) - de Gemmis, Marco; Lops, Pasquale; Semeraro, Giovanni; Musto, Cataldo
Highlights We design a Knowledge Infusion (KI) process for providing systems with background knowledge. We design a KI-based recommendation algorithm for providing serendipitous recommendations. An in vitro evaluation shows the effectiveness of the proposed approach. We collected implicit emotional feedback on serendipitous recommendations. Results show that serendipity is moderately correlated with surprise and happiness.