Community detection based on unsupervised attributed network embedding

作者：

Highlights：

• We present a Community Detection algorithm based on attributed Network Embedding.

• It jointly model topology and attributes with the graph attention auto-encoder.

• We conduct experiments and compare the performance with 10 competitive baselines.

• The experiment results demonstrate the effectiveness of the proposed community detection model.

摘要

•We present a Community Detection algorithm based on attributed Network Embedding.•It jointly model topology and attributes with the graph attention auto-encoder.•We conduct experiments and compare the performance with 10 competitive baselines.•The experiment results demonstrate the effectiveness of the proposed community detection model.

论文关键词：Community detection,Graph auto-encoder,Unsupervised representation learning

论文评审过程：Received 29 July 2022, Revised 10 September 2022, Accepted 27 September 2022, Available online 3 October 2022, Version of Record 12 October 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118937