CaEGCN: Cross-Attention Fusion based Enhanced Graph Convolutional Network for Clustering

1 code implementation • 18 Jan 2021 • Guangyu Huo, Yong Zhang, Junbin Gao, Boyue Wang, Yongli Hu, BaoCai Yin

In this paper, we propose a cross-attention based deep clustering framework, named Cross-Attention Fusion based Enhanced Graph Convolutional Network (CaEGCN), which contains four main modules: the cross-attention fusion module which innovatively concatenates the Content Auto-encoder module (CAE) relating to the individual data and Graph Convolutional Auto-encoder module (GAE) relating to the relationship between the data in a layer-by-layer manner, and the self-supervised model that highlights the discriminative information for clustering tasks.

Clustering Deep Clustering