Enhanced Deep Reinforcement Learning based Group Recommendation System with Multi-head Attention for Varied Group Sizes
Saba Izadkhah, Banafsheh Rekabdar · 2024
This paper introduces EnGRMA, an Enhanced deep reinforcement learning-based Group Recommendation system with Multi-head Attention for varied group sizes.EnGRMA adapts its recommendation strategy according to group sizes, using individual member preferences in smaller groups through a weighted average method, and leveraging multihead attention to aggregate diverse opinions effectively in larger groups.This method helps model dynamic member-item interactions, enhancing the system's ability to deliver personalized recommendations.Our evaluation of the MovieLens-Rand dataset shows that EnGRMA not only outperforms GRMA and DRGR in Recall, NDCG, Precision, and F1 scores but also demonstrates superior performance in NDCG against AGREE.