Abstract
The obtention of a set of homogeneous classes of pages according to the browsing patterns identified in web server log files can be very useful for the analysis of organization of the site and of its adequacy to user needs. Such a set of homogeneous classes is often obtained from a dissimilarity measure between the visited pages defined via the visits extracted from the logs. There are however many possibilities for defined such a measure. This paper presents an analysis of different dissimilarity measures based on the comparison between the semantic structure of the site identified by experts and the clustering constructed with standard algorithms applied to the dissimilarity matrices generated by the chosen measures.
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Rossi, F., De Carvalho, F., Lechevallier, Y., Da Silva, A. (2006). Dissimilarities for Web Usage Mining. In: Batagelj, V., Bock, HH., Ferligoj, A., Žiberna, A. (eds) Data Science and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-34416-0_5
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DOI: https://doi.org/10.1007/3-540-34416-0_5
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