arXiv stat.ML
· Papers
Towards Reliable Recommender Systems for Rating Data
arXiv:2412.20802v3 Announce Type: replace Abstract: Recommender systems are widely used in the digital landscape to match users with content fitting their preferences. However, growing concerns about fake accounts, strategic manipulation, and other deceptive online behavior place increasing pressure on the reliability