Collaborative contrastive learning for hypergraph node classification

Hanrui Wu, Nuosi Li, Jia Zhang, Sentao Chen, Michael K. Ng, Jinyi Long

Abstract: Highlights•CCL is proposed to handle hypergraph node classification problem.•CCL considers the contrast in each layer from GCN and HGCN.•CCL exploits the convolutional networks on the standard graph and hypergraph.•Experimental results demonstrate the superior performance of the proposed model.