Brigitte Trousse
580 California St., Suite 400
San Francisco, CA, 94104
Automatic clustering for the web usage mining
2003
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Abstract
In this paper we present an approach based on two hybrid clustering methods for Web Usage Mining (WUM). The WUM process contains three steps: pre-processing, data mining and result analysis. First, we give a brief description of the WUM process and Web data, followed in section 2 by the presentation of the pre-processing step and the data warehouse that we employed. Two hybrid clustering methods based on Principal Components Analysis (PCA), Multiple Classification Analysis (MCA) and Dynamic Clustering, are used for analysing the Web logs taken from INRIA's Web servers. The results obtained after applying these methods and the corresponding interpretations are presented in section four of the article. Finally, we provide some perspectives and future work.
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