REDRL: A review-enhanced Deep Reinforcement Learning model for interactive recommendation

Huiting Liu, Kun Cai, Peipei Li, Cheng Qian, Peng Zhao, Xindong Wu

Abstract: Highlights•Mining information in reviews and interaction data via the pretrained model.•Modeling long-term dynamic preferences of users accurately and discriminately.•Filtering irrelevant items and getting candidate items dynamically from a new anger.•Better interactive recommendation based on deep reinforcement learning.