Multi-Task Fusion via Reinforcement Learning for Long-Term User Satisfaction in Recommender Systems

no code implementations • 9 Aug 2022 • Qihua Zhang, Junning Liu, Yuzhuo Dai, Yiyan Qi, Yifan Yuan, Kunlun Zheng, Fan Huang, Xianfeng Tan

The mainstream RS ranking framework is composed of two parts: a Multi-Task Learning model (MTL) that predicts various user feedback, i. e., clicks, likes, sharings, and a Multi-Task Fusion model (MTF) that combines the multi-task outputs into one final ranking score with respect to user satisfaction.

Multi-Task Learning Recommendation Systems +1