Multi-task Contrastive Learning for Anomaly Detection on Attributed Networks

Junjie Zhang; Yuxin Ding

doi:10.1007/978-981-97-2242-6_2

ScienceGate Book Chapters

BOOK-CHAPTER

Multi-task Contrastive Learning for Anomaly Detection on Attributed Networks

Junjie Zhang Yuxin Ding

Year: 2024 Lecture notes in computer science Pages: 15-26 Publisher: Springer Science+Business Media

DOI: 10.1007/978-981-97-2242-6_2

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Anomaly detection Benchmark (surveying) Artificial intelligence Matching (statistics) Context (archaeology) Task (project management) Machine learning Anomaly (physics) Exploit Ensemble learning

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.12

Citation Normalized Percentile

Is in top 1%

Is in top 10%

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

Complex Network Analysis Techniques

Physical Sciences → Physics and Astronomy → Statistical and Nonlinear Physics

Multi-task Contrastive Learning for Anomaly Detection on Attributed Networks

Metrics

Topics

Related Documents

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

Dual Contrastive Learning for Anomaly Detection in Attributed Networks

Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning

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

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