Simulation of E-Commerce Big Data Classification Model Based on Artificial Intelligence Algorithm

In the era of artificial intelligence (AI), it has become an essential tool for e-commerce platform to analyze the real consumption potential of its users. In the classification and mining of e-commerce BD (big data), the low accuracy of the algorithm is the main reason that restricts the development of e-commerce. For this reason, in order to solve the problem that e-commerce needs to classify and process data quickly, this paper combines clustering theory, fuzzy logic theory, and artificial neural network (ANN) theory to design an e-commerce BD classification model based on AI algorithm. The simulation results show that compared with support vector machine (SVM) and fuzzy c-means (FCM) algorithms, our proposed fusion algorithm has better performance in clustering effect and convergence speed, and the error rate is low. Through the research of this project, more accurate data mining (DM) can be realized, thus improving the accuracy of the existing DM algorithm.