Multi-factor Sequential Re-ranking with Perception-Aware Diversification

no code implementations • 21 May 2023 • Yue Xu, Hao Chen, Zefan Wang, Jianwen Yin, Qijie Shen, Dimin Wang, Feiran Huang, Lixiang Lai, Tao Zhuang, Junfeng Ge, Xia Hu

Feed recommendation systems, which recommend a sequence of items for users to browse and interact with, have gained significant popularity in practical applications.

Graph Clustering Recommendation Systems +1

Multi-channel Integrated Recommendation with Exposure Constraints

no code implementations • 21 May 2023 • Yue Xu, Qijie Shen, Jianwen Yin, Zengde Deng, Dimin Wang, Hao Chen, Lixiang Lai, Tao Zhuang, Junfeng Ge

Integrated recommendation, which aims at jointly recommending heterogeneous items from different channels in a main feed, has been widely applied to various online platforms.

Recommendation Systems

Learning Transferrable Parameters for Long-tailed Sequential User Behavior Modeling

no code implementations • 22 Oct 2020 • Jianwen Yin, Chenghao Liu, Weiqing Wang, Jianling Sun, Steven C. H. Hoi

Sequential user behavior modeling plays a crucial role in online user-oriented services, such as product purchasing, news feed consumption, and online advertising.

Transfer Learning