Font Size: a A A

Campus Network User Behavior Analysis System Research And Implementation

Posted on:2010-12-02Degree:MasterType:Thesis
Country:ChinaCandidate:W LiangFull Text:PDF
GTID:2178360275973671Subject:Computer Science and Technology
Abstract/Summary:PDF Full Text Request
In the age of information, people's work, study and living is increasingly dependent on the network. Construction and the use of campus network in colleges and universities has become an important sign of education modernization. As an important part of Internet, campus network has more professional user, and user's purpose of visit the Internet is more clearly, so campus network users access the network compared to the general public users have a more obvious characteristics. Research and analysis of campus network user behavior characteristics, can provide important theoretical basis for network planning and construction, so the study of campus network user behavior is increasingly important. Meanwhile, as the development of information technology, Internet addiction is attract increasingly concerning of society, Internet Addiction is not only hazardous to the physical and mental health of young people, but also affected the family harmony and social stability. Research and analysis of campus network student users' online behavior has a positive meaning to identify potential network addicts, and to intervene and guide them.In this paper, study focused on five aspects of user behavior, the analysis of time-divided number of online users, analysis of the network using time, analysis of user network flow, analysis of the use of common network applications, analysis of user access destination address. In addition, the CIDR-based clustering algorithm is put forward to deal with mass data of the destination address, obtain the preferences destination address of the campus network while access the Internet. Mastered the network flow of the mainly destination, can guide the allocation of network bandwidth and other related work.
Keywords/Search Tags:Campus Network User Behavior, Behavior Analysis, Data Mining, Hierarchical Clustering
PDF Full Text Request
Related items