QAGCF: Graph Collaborative Filtering for Q&A Recommendation

no code implementations • 7 Jun 2024 • Changshuo Zhang, Teng Shi, Xiao Zhang, Yanping Zheng, Ruobing Xie, Qi Liu, Jun Xu, Ji-Rong Wen

Traditional recommendation methods treat the question-answer pair as a whole or only consider the answer as a single item, which overlooks the two challenges and cannot effectively model user interests.

UOEP: User-Oriented Exploration Policy for Enhancing Long-Term User Experiences in Recommender Systems

no code implementations • 17 Jan 2024 • Changshuo Zhang, Sirui Chen, Xiao Zhang, Sunhao Dai, Weijie Yu, Jun Xu

Reinforcement learning (RL) has gained traction for enhancing user long-term experiences in recommender systems by effectively exploring users' interests.

Fairness Recommendation Systems +1

Controllable Multi-Objective Re-ranking with Policy Hypernetworks

1 code implementation • 8 Jun 2023 • Sirui Chen, YuAn Wang, Zijing Wen, Zhiyu Li, Changshuo Zhang, Xiao Zhang, Quan Lin, Cheng Zhu, Jun Xu

In this paper, we propose a framework called controllable multi-objective re-ranking (CMR) which incorporates a hypernetwork to generate parameters for a re-ranking model according to different preference weights.

Recommendation Systems Re-Ranking