Research On User Behavior Analysis Model Based On Log Data

According to CNNIC(China Internet Network Information Center)report pointed out that[1]the number of Internet users in China has more than half of the proportion of mobile phone users accounted for more than Jiucheng.The report shows that Internet users are mainly focused on mobile devices,mobile phones become the main tool for people online.Based on the above background,this paper puts forward the analysis of user log data and puts forward the user behavior analysis model of log data,which mainly includes two aspects:(1)network user behavior analysis;(2)user grouping model establishment.And discusses how to establish a better user segmentation model to identify the target user base,so as to lay the foundation for the precise marketing of marketers.Thus,this article carried out the following work:First,select the user grouping model.By comparing the data mining algorithms,the K-Means algorithm in the clustering algorithm with obvious advantages is selected,and the clustering center selection and user clustering model are discussed.Second,the user behavior of HTTP log data is analyzed.By comparing the different user log data types,the paper analyzes the value of the log data based on the HTTP protocol,then analyzes the URL characteristics in the log data,combines the user grouping results,identifies the user identity,and sets out the marketing strategy.Third,carry out simulation experiments.In order to understand the different user's consumption behavior by using the SPSS software to analyze the K-Means algorithm,the user group is subdivided into the log data obtained from the log data during the internship.Through the simulation experiment,this article has successfully divided the mobile phone users,and according to the consumption characteristics of various types of customers will be divided into five categories,namely,high-end commercial customers,terminal business customers,the end of daily customers,long customers and customers Often use the customer,a preliminary understanding of the user's spending habits and needs for the operator's future lay the foundation for business.