Spectrum-Constrained and Skip-Enhanced Graph Fraud Detection: Addressing Heterophily in Fraud Detect...
Spectrum-Constrained and Skip-Enhanced Graph Fraud Detection: Addressing Heterophily in Fraud Detection with Spectral and Spatial Modeling
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English
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Fraud detection in large-scale graphs presents significant challenges, especially in heterophilic graphs where linked nodes often belong to dissimilar classes or exhibit contrasting attributes. These asymmetric interactions, combined with class imbalance and limited labeled data, make it difficult to fully leverage node labels in semi-supervised le...
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Spectrum-Constrained and Skip-Enhanced Graph Fraud Detection: Addressing Heterophily in Fraud Detection with Spectral and Spatial Modeling
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TN_cdi_crossref_primary_10_3390_sym17040476
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_crossref_primary_10_3390_sym17040476
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ISSN
2073-8994
E-ISSN
2073-8994
DOI
10.3390/sym17040476
