Data mining method of false transaction in webcast platform based on Cluster Learning

In order to improve the authenticity of transactions on the webcast platform, it is necessary to mine the false transaction data in the webcast platform. However, the traditional false transaction data mining methods have the problem of low feature extraction accuracy and mining accuracy of false transaction data. Therefore, a false transaction data mining method on the webcast platform based on cluster learning is proposed. Firstly, the transaction data of the webcast platform is collected through the network sensor; Secondly, the features of false transaction data on webcast platform are extracted by clustering learning. Finally, the false transaction data is mined by genetic algorithm. Experimental results show that this method can effectively extract the characteristics of false transaction data, and the accuracy of false transaction data mining is significantly improved.