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Clustering Optimization and Evaluation of Campus Network User Behavior Analysis System

  • Hong Jiang
  • Qingsong YuEmail author
  • Yingying Xu
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1075)

Abstract

The access logs of the flow control server in the campus network of A university are extracted and analyzed in this paper. A hybrid clustering combined with sampling, K-means algorithm and agglomerative hierarchical method is proposed to analyze users’ behavior and classify users’ access objectives and habits, which can not only make clustering results more stable, but also enhance the analysis efficiency of the algorithm.

Keywords

User behavior analysis Campus network Data mining Cluster analysis 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Computer CenterEast China Normal UniversityShanghaiChina

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