GCRMF builds a cross-industry heterogeneous graph and applies temporal dual-graph attention with contrastive meta-path reasoning and self-supervised learning to improve AML detection F1 scores by over 17.8% in mobility-energy networks.
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Graph-Driven Cross-Industry Real-Time Monitoring Framework for Anti-Money Laundering Detection in Converged Mobility-Energy Supply Chain Networks
GCRMF builds a cross-industry heterogeneous graph and applies temporal dual-graph attention with contrastive meta-path reasoning and self-supervised learning to improve AML detection F1 scores by over 17.8% in mobility-energy networks.