Design And Implementation Of Campus Network User Behavior Analysis System Based On Multi-source Data Fusion

With the emergence and rapid development of the Internet,the network has gradually integrated into people's work and life.At the same time,user behavior analysis has emerged,which brings opportunities and challenges for the mining and analysis of network information.This field can study students' online behavior in school,understand students' online situation and its impact on learning,so that the academic administrators can manage students more effectively.The thesis is mainly used to analyze and manage the situation of users' access to the Internet in the campus network,to detect and guide the severe users as early as possible.However,with a single data source,the conclusion may not be accurate.In addition,the location of online log storage may be relatively scattered,so it is difficult to achieve correlation analysis.Based on the multi-source data such as the campus network online log,traffic log and academic performance,the thesis builds a campus network user behavior analysis system to realize the multi-source data fusion,completes the unified processing and analysis of the multi-source data,and then displays it through the interface.The main work of the the thesis is as follows:(1)We investigate the research background and significance of user behavior analysis,and understands the research status of domestic and foreign scholars on user behavior analysis of campus network.(2)We analyze the necessity and urgency of user behavior analysis in campus network,studies the related technologies involved in user behavior analysis,and proposes a scheme of user behavior analysis system based on multi-source data fusion.(3)We propose an improved k-means algorithm,which can reduce the error of clustering by improving the selection of initial clustering center,and uses the distributed characteristics of Hadoop platform to parallel the improved k-means algorithm to solve the problem of processing efficiency in the system.(4)An improved TF-IDF algorithm is proposed.Combined with the structural features of HTML in web pages,TF-IDF algorithm is improved to extract text keywords more accurately.(5)A campus network user behavior analysis system based on multi-source data fusion is designed and implemented.The system is mainly divided into three modules:data access module,data processing module and data display module.Through this system,we can understand the Internet behavior of users in campus,and manage and guide heavy Internet users in time.