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...

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Vydané v:	Applied sciences Ročník 15; číslo 15; s. 8691
Hlavní autori:	Zhang, Chi, Jung, Jin-Woo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.08.2025
Predmet:	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
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