• Corpus ID: 231839439

Self-Supervised Deep Graph Embedding with High-Order Information Fusion for Community Discovery

@article{Xu2021SelfSupervisedDG,
  title={Self-Supervised Deep Graph Embedding with High-Order Information Fusion for Community Discovery},
  author={Shuliang Xu and Sheng-lan Liu and Lin Feng},
  journal={ArXiv},
  year={2021},
  volume={abs/2102.03302}
}
Deep graph embedding is an important approach for community discovery. Deep graph neural network with self-supervised mechanism can obtain the low-dimensional embedding vectors of nodes from unlabeled and unstructured graph data. The high-order information of graph can provide more abundant structure information for the representation learning of nodes. However, most self-supervised graph neural networks only use adjacency matrix as the input topology information of graph and cannot obtain too… 

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