现代电子技术2016，Vol.39Issue(7)：29-32,4.DOI:10.16652/j.issn.1004-373x.2016.07.007
聚类算法在高校网络用户行为分析中的应用
Application of clustering algorithm in university network user behavior analysis
摘要
Abstract
The network management departments in universities have accumulated users′ mass online behavior data in ope⁃ration management process,which can master users′ online habit and regular pattern by reorganizing and analyzing the users′ on⁃line behavior,and formulate the online management strategy scientifically and effectively. A specific college is taken as the ex⁃ample,the users′ online data is preprocessed,and corresponding field is extracted to built the analysis dataset. The online login time is showed in graphic form after statistics. By taking online time as the index value,the clustering analysis for the online record is conducted with K⁃means clustering and Kohonen neural network clustering methods to obtain the clustering results. In combi⁃nation with the user information,the results obtained from the two clustering methods are compared by taking corresponding cri⁃terion of user and online record as the criterion to judge the clustering effect,and the suitable result is selected. The online con⁃dition of the experimental unit is analyzed with the computed results to propose some suggestions for online management strategy.关键词
Kohonen神经网络/高校网络管理/上网行为/上网管理策略Key words
Kohonen neural network/university network management/online behavior/online management strategy分类
信息技术与安全科学引用本文复制引用
薛黎明,栾维新..聚类算法在高校网络用户行为分析中的应用[J].现代电子技术,2016,39(7):29-32,4.
