15 citations · 38 across the 3 of their papers we have counts for
3 papers
cs.IR2020★ 15 cited
Joint Item Recommendation and Attribute Inference: An Adaptive Graph Convolutional Network Approach
Le Wu, Yonghui Yang, Kun Zhang +3
In many recommender systems, users and items are associated with attributes, and users show preferences to items. The attribute information describes users'(items') characteristics…
cs.IR2020★ 13 cited
Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach
Lei Chen, Le Wu, Richang Hong +2
Graph Convolutional Networks (GCNs) are state-of-the-art graph based representation learning models by iteratively stacking multiple layers of convolution aggregation operations an…
cs.LG2020★ 10 cited
Deep Technology Tracing for High-tech Companies
Han Wu, Kun Zhang, Guangyi Lv +5
Technological change and innovation are vitally important, especially for high-tech companies. However, factors influencing their future research and development (R&D) trends are b…