Deep neighbor-aware embedding for node clustering in attributed graphs

作者：

Highlights：

• We proposed a neighbor-aware embedding algorithm for attributed graph clustering.

• Embedding learning and clustering are jointly optimized in an end-to-end manner.

• The embedding learning is specialized for clustering task.

• The experiment results outperform state-of-the-art graph clustering methods.

摘要

•We proposed a neighbor-aware embedding algorithm for attributed graph clustering.•Embedding learning and clustering are jointly optimized in an end-to-end manner.•The embedding learning is specialized for clustering task.•The experiment results outperform state-of-the-art graph clustering methods.

论文关键词：Attributed graph,Node clustering,Graph attention network,Graph convolutional network,Network representation

论文评审过程：Received 5 March 2019, Revised 18 July 2021, Accepted 6 August 2021, Available online 15 August 2021, Version of Record 23 August 2021.

论文官网地址：https://doi.org/10.1016/j.patcog.2021.108230