Prior Structural Information-GNN,PSI-GNN

Attribute information characterizing the topology of the central node is embedded in the feature vector through structural information encoding; Secondly, message passing is divided into proximal and distal aspects, one of which is based on a shallow GNN model that aggregates the proximal node information, and the other is oriented to random wander structural similarity to filter and aggregate distal homophilic information; Finally, fusing the above two node embedding results and accomplishing fraud identification.