Corpus ID: 212717738

Heterogeneous-Temporal Graph Convolutional Networks: Make the Community Detection Much Better

@article{Zheng2019HeterogeneousTemporalGC,
  title={Heterogeneous-Temporal Graph Convolutional Networks: Make the Community Detection Much Better},
  author={Yaping Zheng and Shiyi Chen and Xinni Zhang and Xiaofeng Zhang and Xiaofei Yang and Di Wang},
  journal={arXiv: Learning},
  year={2019}
}
Community detection has long been an important yet challenging task to analyze complex networks with a focus on detecting topological structures of graph data. Essentially, real-world graph data contains various features, node and edge types which dynamically vary over time, and this invalidates most existing community detection approaches. To cope with these issues, this paper proposes the heterogeneous-temporal graph convolutional networks (HTGCN) to detect communities from hetergeneous and… Expand

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