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GNN-Enhanced RL for Dynamic Recommendations by Pavithradevi is a document available to read on EtoBox.

This paper presents a novel recommender system that integrates Graph Neural Networks (GNNs) with Reinforcement Learning (RL) to enhance recommendation accuracy and adaptability to dynamic user preferences. The proposed system employs a self-attention-based state encoder, residual connections in the actor network, and a hybrid reward function to improve user engagement and recommendation performance. Experimental results on real-world datasets demonstrate significant improvements in key metrics compared to t

Author

Pavithradevi

Language

EN