GNN recommender uses edge classification and cost-sensitive learning to disentangle popularity bias from quality, reporting ~32% average fairness gains with competitive accuracy.
Addressing marketing bias in product recommendations
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Disentangling Popularity and Quality: An Edge Classification Approach for Fair Recommendation
GNN recommender uses edge classification and cost-sensitive learning to disentangle popularity bias from quality, reporting ~32% average fairness gains with competitive accuracy.