Graph Outlier Detection

Graph Outlier Detection is an anomaly detection technique designed for graph data, aiming to identify outliers in the graph that significantly differ from normal nodes or subgraphs. This method analyzes the connection patterns, attribute features, and subgraph structures to uncover potential abnormal behaviors and patterns. It is widely applied in areas such as cybersecurity, social network analysis, and financial fraud detection, making it a valuable tool with significant practical importance.