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Global Attribute-Association Pattern Aggregation for Graph Fraud Detection

Fraud is increasingly prevalent, and its patterns are frequently changing, posing challenges for fraud detection methods such as random forests and Graph Neural Networks (GNNs), which rely on bin-based and mixture features separately. The former may lose crucial graph-associated features, while the…