Deep embedded clustering with distribution consistency preservation for attributed networks

•A distribution consistency preserving deep embedded clustering model is proposed.•The model exploits GAE and AE to learn node representations and clusters jointly.•A consistency constraint is designed to maintain the consistency of the clusters.•The empirical study verifies the effectiveness of the...

Full description

Bibliographic Details

Published in:	Pattern recognition Vol. 139; p. 109469
Main Authors:	Zheng, Yimei, Jia, Caiyan, Yu, Jian, Li, Xuanya
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.07.2023
Subjects:	Autoencoder Cluster distribution consistency Deep embedded clustering Graph autoencoder Node representation learning Graph autoencoder Node representation learning Autoencoder Cluster distribution consistency Deep embedded clustering
ISSN:	0031-3203, 1873-5142
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!