1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.SI2021★ 1 cited
Connecting Latent ReLationships over Heterogeneous Attributed Network for Recommendation
Ziheng Duan, Yueyang Wang, Weihao Ye +3
Recently, deep neural network models for graph-structured data have been demonstrating to be influential in recommendation systems. Graph Neural Network (GNN), which can generate h…
cs.LG2020
Incorporating User's Preference into Attributed Graph Clustering
Wei Ye, Dominik Mautz, Christian Boehm +2
Graph clustering has been studied extensively on both plain graphs and attributed graphs. However, all these methods need to partition the whole graph to find cluster structures. S…
cs.LG2020
Tree++: Truncated Tree Based Graph Kernels
Wei Ye, Zhen Wang, Rachel Redberg +1
Graph-structured data arise ubiquitously in many application domains. A fundamental problem is to quantify their similarities. Graph kernels are often used for this purpose, which…