Creating adaptive Web sites through usage-based clustering of URLs

We describe an approach to usage based Web personalization taking into account both the offline tasks related to the mining of usage data, and the online process of automatic Web page customization based on the mined knowledge. Specifically, we propose an effective technique for capturing common user profiles based on association rule discovery and usage based clustering. We also propose techniques for combining this knowledge with the current status of an ongoing Web activity to perform real time personalization. Finally, we provide an experimental evaluation of the proposed techniques using real Web usage data