Research on Decision Tree-Based Risk Control Strategies in E-Commerce Platforms

In this paper, the weights of different risks in the management process of e-commerce platforms are calculated on the basis of hierarchical analysis. After that, with the help of fuzzy comprehensive assessment algorithm, the risk level is divided. Finally, with the assistance of decision tree, simulation is carried out to simulate the risk of the first-level indicators affecting the risk control of e-commerce platform. According to the survey results, reasonable countermeasures are given to the management of e-commerce platform risks. Among the first-level indicators of the five major risk categories, the business model risk belongs to the high-risk category of Class I, with a fuzzy comprehensive evaluation score of >4.5. The rest belong to the risk category of Class II, with fuzzy comprehensive evaluation scores ranging from 3.5 to 4.5. Among the Level II indicators, there are 6, 6 and 3 Level II indicators rated as high risk category, medium risk and low risk respectively, with their fuzzy composite scores ranging from 4.7495-5.6370, 3.6807-4.4988 and 3.1356-3.2435 respectively Between. In the comprehensive risk simulation prediction of the case-based e-commerce platform, only the logistics model risk belongs to the medium risk control strategy with a risk value of 4.8614 (day 60). The simulation results for the remaining four risk types were all low risk, and their risk values decreased (3.5 points) when the simulation time was day 60. The experimental results provide a prediction for the change of risk and provide reasonable countermeasures and suggestions for the risk control of e-commerce platforms.