no code implementations • 19 Nov 2023 • Juntao Zhang, Sheng Wang, Zhiyu Chen, Xiandi Yang, Zhiyong Peng
Finally, we develop an attention aggregator that aggregates users' preferences as the group's preferences for the group recommendation task.
1 code implementation • 12 Nov 2023 • Shengkun Zhu, Jinshan Zeng, Sheng Wang, Yuan Sun, Zhiyong Peng
Our experiments validate that FLAME, when trained on heterogeneous data, outperforms state-of-the-art methods in terms of model performance.
no code implementations • 28 Jun 2021 • Tieyun Qian, Yile Liang, Qing Li, Xuan Ma, Ke Sun, Zhiyong Peng
Improving the recommendation of tail items can promote novelty and bring positive effects to both users and providers, and thus is a desirable property of recommender systems.