Visual aggregation of large multivariate networks with attribute-enhanced representation learning

Yuhua Liu, Miaoxin Hu, Rumin Zhang, Ting Xu, Yigang Wang, Zhiguang Zhou

Abstract: Highlights•An attribute-enhanced graph representation learning model is proposed to transform multivariate network nodes into vectors.•A scalable aggregation scheme is proposed to enhance the visual perception of large multivariate graph visualization.•A set of visual interfaces are provided enabling users to intuitively explore large multivariate networks.