Social user classification method and system based on graph neural network

• Main Authors: ZHANG WEIYU, GUO XINCHAO
• Format: Patent
• Language: Chinese; English
• Published: 20.01.2023
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a social user classification method and system based on a graph neural network, electronic equipment and a computer readable storage medium, and belongs to the technical field of social user classification. Comprising the steps of obtaining node representation for input original graph structure data constructed based on social user data, and executing oversampling operation based on the node representation; generating composite nodes for a few nodes in the data; acquiring adjacency information of the synthesis node based on the synthesis node; allocating pseudo labels to the synthetic nodes; and combining the synthetic nodes, the adjacency information and the real nodes, constructing a node balance graph, and performing classification. The problem of unbalanced classification can be solved, the accuracy of social user classification is improved, and the problems of low accuracy and high calculation cost caused by category imbalance in social user classification in the prior art are sol