Measuring similarity of interests for clustering Web-users

Abstract

There has been an increased demand for understanding of Web-users due to the Web development and the increased number of Web-based applications. Informative knowledge extracted from Web user access patterns has been used for many applications, such as the prefetching of pages between clients and proxies. This paper presents an approach for measuring similarity of interests among Web users, based on the interest items collected from Web user's access logs. A matrix-based algorithm is then developed to cluster Web users such that the users in the same cluster are closely related with respect to the similarity measure. As an application example, a Web document prefetching technique is proposed that utilises the similarity measure and clusters obtained. Experiments have been conducted and the results have shown that our clustering method is capable of clustering Web users with similar interests, and the prefetching method is practical.