Eduardo Ferreira da Silva

Despite innovative fusion strategies, textual reviews add minimal value to recommendation systems dominated by collaborative signals.

Injecting review semantics into collaborative filtering via adaptive gating and contrastive learning substantially boosts top-N recommendation accuracy, outperforming existing review-aware methods.