基于机器学习的智能终端用户行为分析研究

he characteristics of the network traffic of mobile intelligent terminals can reflect the user\'s network access behavior in some way, and then can reflect user\'s own characteristics.In this paper, we propose a program about intelligent terminal user behavior analysis based on machine learning by studyingtraditional and machine learning network traffic classification methods. By extracting traffic characteristics and using a support vector machine approach to classify network traffic, we have a higher classification accuracy. Finally, we test the program on Android terminal and analyze users with multiple dimensions. the results show that there are obvious behavior patterns in different users.