Abstract

Clustering is one of the important part in web usage miningfor the purpose of segmenting visitors. This action is very important for web personalization orweb modification. In this paper, we perform clustering of the web visitors using a combination of methods of hierarchical and non-hierarchical clustering toward web log data. Hierarchical clustering method used to determine the number of clusters, and non-hierarchical clustering method is used in forming clusters. The stages of cluster analysis are preceded by pre-processing the data and factor analysis. With this approach, the owner of the web is more effective at finding access patterns of web visitors and can have new knowledge about visitors' segmentation. From the test applied on ITS's web log data, 6 clusters of web visitors are resulted. Among the 6 cluster, cluster 3 has the biggest number of members. This information can be useful for web management to pay attention on members' behavioral patterns of the 3rd cluster's either to make personalization or modification on the web. The test results show the feasibility and efficiency of application of this method.

Original languageEnglish
Pages (from-to)207-214
Number of pages8
JournalTelkomnika (Telecommunication Computing Electronics and Control)
Volume11
Issue number1
DOIs
Publication statusPublished - Mar 2013

Keywords

  • Cluster analysis
  • Web logs
  • Web modification
  • Web personalization
  • Web usage mining

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