1 code implementation • 8 Feb 2022 • Yue He, Zimu Wang, Peng Cui, Hao Zou, Yafeng Zhang, Qiang Cui, Yong Jiang
In spite of the tremendous development of recommender system owing to the progressive capability of machine learning recently, the current recommender system is still vulnerable to the distribution shift of users and items in realistic scenarios, leading to the sharp decline of performance in testing environments.
no code implementations • 6 Apr 2021 • Qiang Cui, Chenrui Zhang, Yafeng Zhang, Jinpeng Wang, Mingchen Cai
Specifically, in the long-term module, we learn the temporal periodic interest of daily granularity, then utilize intra-level attention to form long-term interest.
1 code implementation • 14 Nov 2017 • Qiang Cui, Shu Wu, Yan Huang, Liang Wang
We fuse the current hidden state and a contextual hidden state built by the attention mechanism, which leads to a more suitable user's overall interest.