Research on E-commerce Big Data Classification and Mining Algorithm Based on BP Neural Network Technology

Abstract

With the development of the Internet, with the gradual increase of people's needs, more and more people are engaged in various activities on the Internet, such as online transactions. This article mainly studies the classification and mining algorithm of e-commerce big data based on BP neural network technology. Take user movie rating data as the object of analysis and mining, and use platform functions to complete the whole process of data from preprocessing to data mining to result data storage. According to the requirements of the platform design modules and functions, the construction process from the installation of the cluster dependent tool software, node communication, cluster configuration to the final operation monitoring was completed, and the experimental environment of the e-commerce big data platform was established. According to the real open source movie rating data, according to the BP neural network algorithm, relying on the function of the module, the whole recommendation task from data processing, algorithm mining to the final result generation is completed. Through the comparison of speedup, accuracy, recall and coverage indicators, it can be seen that when the experimental data set is 100K, the recommendation efficiency in the cluster environment is not improved. The results show that the BP neural network improves the efficiency of the e-commerce big data platform and the accuracy of task execution results.