HRGCN: Heterogeneous graph-level anomaly detection with hierarchical relation-augmented graph neural networks

• Main Authors: LI, Jiaxi, PANG, Guansong, CHEN, Ling, NAMAZI-RAD, Mohammad-Reza
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Training; Representation learning; Analytical models; Image edge detection; Systems operation; Self-supervised learning; Data models; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/8412; https://ink.library.smu.edu.sg/context/sis_research/article/9415/viewcontent/HRGCN_av.pdf
• Institution: Singapore Management University

This work considers the problem of heterogeneous graph-level anomaly detection. Heterogeneous graphs are commonly used to represent behaviours between different types of entities in complex industrial systems for capturing as much information about the system operations as possible. Detecting anomal...