Effective Web Personalization Using Clustering

This paper describes web personalization, the essence of personalization is the adaptability of information systems to the needs of the adaptability of information system to the needs of their users. This issue is becoming increasing important on the web, as non-expert users are overwhelmed by the quantity of information available online. The proposed approach aims to mine a reduced set of effective association pattern rules for enhancing the online performance of web recommendations and proposed approach is evaluated based on the efficiency and quality. Adaptive user clustering and profiling is essential to be able to accurately predict user actions. In this paper we present results of our clustering and personalization project. We compare several distance measures used in clustering. We introduce a new measure to assess the quality of clustering independent of the distance measure used in the clustering process. We also compare different strategies(such as clustering users vs. clustering urls).