51 citations · 75 across the 2 of their papers we have counts for
2 papers
cs.IR2022★ 51 cited
Multi-Task Fusion via Reinforcement Learning for Long-Term User Satisfaction in Recommender Systems
Qihua Zhang, Junning Liu, Yuzhuo Dai +5
Recommender System (RS) is an important online application that affects billions of users every day. The mainstream RS ranking framework is composed of two parts: a Multi-Task Lear…
cs.IR2020★ 24 cited
TFNet: Multi-Semantic Feature Interaction for CTR Prediction
Shu Wu, Feng Yu, Xueli Yu +5
The CTR (Click-Through Rate) prediction plays a central role in the domain of computational advertising and recommender systems. There exists several kinds of methods proposed in t…