Towards adaptive Web sites: conceptual framework and case study
The creation of a complex Web site is a thorny problem in user interface design. In this paper we explore the notion of adaptive Web sites: sites that semi-automatically improve their organization and presentation by learning from visitor access patterns. It is easy to imagine and implement Web sites that offer shortcuts to popular pages. Are more sophisticated adaptive Web sites feasible? What degree of automation can we achieve? To address the questions above, we describe the design space of adaptive Web sites and consider a case study: the problem of synthesizing new index pages that facilitate navigation of a Web site. We present the PageGather algorithm, which automatically identifies candidate link sets to include in index pages based on user access logs. We demonstrate experimentally that PageGather outperforms the Apriori data mining algorithm on this task. In addition, we compare PageGather's link sets to pre-existing, human-authored index pages.
adaptive data mining clustering