Multi-view discriminative edge heterophily contrastive learning network for attributed graph anomaly detection

Wangyu Jin; Huifang Ma; Yingyue Zhang; Zhixin Li; Liang Chang

doi:10.1016/j.eswa.2024.124460

ScienceGate Book Chapters

JOURNAL ARTICLE

Multi-view discriminative edge heterophily contrastive learning network for attributed graph anomaly detection

Wangyu Jin Huifang Ma Yingyue Zhang Zhixin Li Liang Chang

Year: 2024 Journal: Expert Systems with Applications Vol: 255 Pages: 124460-124460 Publisher: Elsevier BV

DOI: 10.1016/j.eswa.2024.124460

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Discriminative model Anomaly detection Artificial intelligence Anomaly (physics) Pattern recognition (psychology) Graph Enhanced Data Rates for GSM Evolution Theoretical computer science Physics

Metrics

Cited By

5.11

FWCI (Field Weighted Citation Impact)

Refs

0.93

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Advanced Graph Neural Networks

Physical Sciences → Computer Science → Artificial Intelligence

Complex Network Analysis Techniques

Physical Sciences → Physics and Astronomy → Statistical and Nonlinear Physics

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Multi-view discriminative edge heterophily contrastive learning network for attributed graph anomaly detection

Metrics

Citation History

Topics

Related Documents

Beyond Homophily: Attributed Graph Anomaly Detection via Heterophily-Aware Contrastive Learning Network

Graph Anomaly Detection via Multi-View Discriminative Awareness Learning

Enhancing Multi-view Contrastive Learning for Graph Anomaly Detection

Semi-supervised Graph Anomaly Detection via Multi-view Contrastive Learning

Graph Anomaly Detection via Diffusion Enhanced Multi-View Contrastive Learning