基于内容偏好的移动客户互联网访问行为分析-《计算机技术与发展》

文章信息/Info

Title:: Analysis of Clients Internet Access Behavior of China Mobile Based on Content Preference

Author(s):: GONG Jing; ZHOU Fei-fei ; LU Jia ; LIU Chen-wei; [1]College of Science of Nanjing University of Posts and Telecommunications[2]College of Internet of Things of Nanjing University of Posts and Telecommunications

Keywords:: content preference; visit behavior analysis; improved ORAR association rules algorithm

摘要:: 文中主要研究基于内容偏好的移动客户互联网访问行为。首先，进行移动客户互联网访问偏好内容的细分，对原始数据进行剔除噪声数据及转化数据为布尔类型的预处理。其次，基于改进的ORAR关联规则算法分析布尔类型的数据，挖掘出各偏好间的关联程度。最后，根据移动公司提供的4万条移动客户互联网访问的随机数据对改进的ORAR关联规则算法进行验证，得到各个子偏好间的关联程度且改进的算法使结果更加准确。结果表明，根据关联程度能够能有效命中目标客户群的偏好访问内容，借此向特定用户推销相关的业务，从而达到精确营销、获得最大客户满意度的要求

Abstract:: It is studying the analysis of the clients internet access behavior of China mobile based on the content preference. Firstly, subdivide the content preferences of mobile clients intemet access behavior, removing the noise data from original data and converting the original data into Boolean type. Secondly, analyze the Boolean type data based on the improved ORAR association rules algorithm and dig out the connection degree between individual preferences. Lastly, give the validation of the improved ORAR association rules algorithm according to 40,000 random data of surfing the internet which mobile company provided of,achieve a better conclusion of the connection degree between individual preferences. The result shows that the accuracy clients content preferences will come true when using connec tion degree, taking the opportunity to sell to a specific user-related business, then achieving precise marketing and obtaining customer sat isfaction requirements