no code implementations • 19 Mar 2024 • Zhichao Feng, Junjiie Xie, Kaiyuan Li, Yu Qin, Pengfei Wang, Qianzhong Li, Bin Yin, Xiang Li, Wei Lin, Shangguang Wang
We first identify contexts that share similar user preferences with the target context and then locate the corresponding PoIs based on these identified contexts.
no code implementations • 7 Aug 2023 • Bin Yin, Junjie Xie, Yu Qin, Zixiang Ding, Zhichao Feng, Xiang Li, Wei Lin
The analysis and mining of user heterogeneous behavior are of paramount importance in recommendation systems.
no code implementations • 17 Apr 2023 • Rui Liu, Bin Yin, Ziyi Cao, Qianchen Xia, Yong Chen, Dell Zhang
Personalized news recommender systems help users quickly find content of their interests from the sea of information.
no code implementations • 19 Feb 2023 • Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bin Yin, Tuo Zhao
Since the teacher model has a significantly larger capacity and stronger representation power than the student model, it is very difficult for the student to produce predictions that match the teacher's over a massive amount of open-domain training data.