Abstract
The explosive growth of the web is at the basis of the great interest into web usage mining techniques in both the commercial and academic communities. This paper presents a classification algorithm for web personalization based on web usage mining techniques. The algorithm takes into account both static information, by means of classical clustering techniques, and dynamic user behavior, thus proposing a novel and effective re-classification algorithm. Experiments have been carried out in order to validate our approach and evaluate the proposed algorithm.
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