We investigate runtime environment characteristics and explore the challenges of conventional in-memory graph processing. This system-level analysis includes empirical results and observations, which ...

Graph anomaly detection is a crucial area in data mining and machine learning, with applications in network security, fraud detection, and health monitoring. Current methods, however, face limitations ...