Ye Yuan

A Novel Graph Fraud Detector via Grouped Attribute Completion and Confidence-Aware Contrastive Learning

A novel framework for Graph Fraud Detection with Grouped attribute completion and Confidence-aware Contrastive learning, named GFD-GC, which introduces a confidence-aware supervised contrastive learning strategy to augment scarce labeled fraud nodes with high confidence pseudo-fraud nodes, which enhances the compactness of fraud representations and their separability from non-fraud nodes.