DCOR: Anomaly Detection in Attributed Networks via Dual Contrastive Learning Reconstruction

Hossein Rafiee Zade; Hadi Zare; Mohsen Ghassemi Parsa; Hadi Davardoust; Mehdi Bagheri

doi:10.1007/978-3-031-82435-7_1

ScienceGate Book Chapters

BOOK-CHAPTER

DCOR: Anomaly Detection in Attributed Networks via Dual Contrastive Learning Reconstruction

Hossein Rafiee Zade Hadi Zare Mohsen Ghassemi Parsa Hadi Davardoust Mehdi Bagheri

Year: 2025 Studies in computational intelligence Pages: 3-15 Publisher: Springer Nature

DOI: 10.1007/978-3-031-82435-7_1

Get Full-Text PDF Get Analytical Report

Keywords:

Dual (grammatical number) Anomaly (physics) Anomaly detection Artificial intelligence Computer science Pattern recognition (psychology) Machine learning Linguistics Physics Philosophy

Metrics

Cited By

9.06

FWCI (Field Weighted Citation Impact)

Refs

0.93

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Adversarial Robustness in Machine Learning

Physical Sciences → Computer Science → Artificial Intelligence

DCOR: Anomaly Detection in Attributed Networks via Dual Contrastive Learning Reconstruction

Metrics

Citation History

Topics

Related Documents

Dual contrastive learning-based reconstruction for anomaly detection in attributed networks

Dual Contrastive Learning for Anomaly Detection in Attributed Networks

Dual Perspective Contrastive Learning Based Subgraph Anomaly Detection on Attributed Networks

Reconstruction Enhanced Multi-View Contrastive Learning for Anomaly Detection on Attributed Networks

Community-Guided Contrastive Learning with Anomaly-Aware Reconstruction for Anomaly Detection on Attributed Networks