The Research And Implementation Of Network User Behavior Analysis System Based On MongoDB

With the rapid development and wide application of the Internet,a variety of websites have brought great changes to people’s work and life.In order to understand the user’s behavior more clearly,to improve the user experience,and to provide valuable suggestions for the construction of websites,it is necessary to analyze user behavior data.On the basis of the traditional relational database,the network user behavior analysis system realizes the analysis of the network user data by using the fast data processing ability and the horizontal extension of the non relational database.It is a new research direction in the field of data mining and data analysis.MapReduce is a programming model for large-scale data sets,the main thought is‘divide-and-rule’ and parallel processing,in order to achieve efficient processing of complex tasks.Clustering algorithm divides data into clusters composed of similar objects,including K-means algorithm,CURE algorithm and so on.With the advent of the era of big data,it’s difficult to cluster the massive data.It is feasible to parallelize the clustering algorithm and improve the efficiency of the algorithm by using the distributed database Mongo DB and combining Map Reduce and K-means clustering algorithm.This thesis takes the user data of online learning system of network and Continuing Education College of Xi Dian University as the data source,studies and implements the network user behavior analysis system based on Mongo DB.The main research content of the network user behavior analysis system is to collect and store the data generated by the users when they visit the website regularly,and to clean,transform and analyze the data.Use the built-in Mongo DB Map Reduce,realize the parallel K-means algorithm,improve the efficiency of data processing,extract user data of user learning behavior and make the cluster analysis,explore the feature of user learning behavior.The purpose is to analyze the data generated by network users and explore the rules and habits of users accessing websites,which can provide valuable information for the construction and optimization of websites and the improvement of user experience.After testing,the system can collect and process network user behavior data regularly,store the data in Mongo DB,cluster analysis of user data by using K-means algorithm based on Map Reduce,and achieve good results.It has positive implications for online learning system optimization and college instructional planning.