Mitigating Consistency Bias in Recommender Systems via Transformer-Based Dynamic Fuzzy Bias Adjustment
The proposed consistency-bias mitigation framework combines Transformer-based sequential modeling with dynamic fuzzy bias adjustment and temporal change detection and adaptive weighting can reduce the excessive influence of repeated historical patterns without discarding useful behavioral evidence.