Predicting page occurrence in a click-stream data: statistical and rule-based approach

Authors:
Petr Berka;Martin Labsky
Affiliations:
Department of Information and Knowledge Engineering, University of Economics, Prague, Czech Republic;Department of Information and Knowledge Engineering, University of Economics, Prague, Czech Republic
Venue:
ICDM'07 Proceedings of the 7th industrial conference on Advances in data mining: theoretical aspects and applications
Year:
2007

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Abstract

We present an analysis of the click-stream data with the aim to predict the next page that will be visited by an user based on a history of visited pages. We present one statistical method (based on Markov models) and two rule induction methods (first based on well known set covering approach, the other base on our compositional algorithm KEX). We compare the achieved results and discuss interesting patterns that appear in the data.