no code implementations • 15 Aug 2023 • Xiaolin Zheng, Zhongyu Wang, Chaochao Chen, Jiashu Qian, Yao Yang
The first stage builds a local inner-item hypergraph for each user and a global inter-user graph.
no code implementations • 15 Aug 2023 • Xiaolin Zheng, Zhongyu Wang, Chaochao Chen, Feng Zhu, Jiashu Qian
In the model training, we propose a novel graph convolutional method named HLGCN, which leverages both high-pass and low-pass filters to deal with conversion and non-conversion relationships.
no code implementations • 8 Sep 2022 • Zeyu Liu, Yi Wang, Jing Wen, Yong Zhang, Hao Yin, Chao Guo, Zhongyu Wang
In addition, in order to improve the segmentation performance, we adopt multi-view and multi-window level method, at the same time we employ a fine-tune strategy to mitigate the impact of inconsistent labeling.