Enhanced Graph Autoencoder for Graph Anomaly Detection Using Subgraph Information

Graph anomaly detection aims at identifying rare, unusual entities in attributed networks with respect to their patterns or structures that deviate significantly from the majority within a graph. Over the years, extensive efforts in this field have been dedicated to the powerful capability of attrib...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Applied sciences Jg. 15; H. 15; S. 8691
Hauptverfasser:	Zhang, Chi, Jung, Jin-Woo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.08.2025
Schlagworte:	Analysis Datasets Deep learning Design Detectors Euclidean space graph anomaly detection graph autoencoders graph neural networks graph structure learning Neighborhoods Neural networks Social network analysis Social networks
ISSN:	2076-3417, 2076-3417
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!