Towards Reliable Recommender Systems for Rating Data

Aurore Archimbaud, Andreas Alfons, Ines Wilms

Recommender systems are widely used in the digital landscape to match users with content fitting their preferences. However, growing concerns about fake accounts, strategic manipul…