Open access
Jul 2026
Fair assessment of fair recommender systems: an experimental framework on model and data characteristics
This study proposes an evaluation framework to address fair assessment among recommender systems by analyzing 900 experimental runs across two widely used datasets, three state-of-the-art recommenders, five fairness metrics, and two sensitive attributes.
Yaren Yılmaz, Umutcan Karakas, Yildiz Ulasli et al.
· PeerJ Computer Science · 0 citations