Multi-objective optimization for adaptive web site generation

Abstract

Designing web sites is a complex problem. Adaptive sites are those which improve themselves by learning from user access patterns. In this paper we have considered a problem of index page synthesis for an adaptive website and framed it in a new type of Multi-Objective Optimization problem. We give a solution to index page synthesis which uses a popular clustering algorithm DBSCAN alongwith NSGA-II-an evolutionary algorithm-to find out best index pages for a website. Our experiments shows that very good candidate index pages can be generated automatically, and that our technique outperforms various existing methods such as PageGather, K-Means and Hierarchical Agglomerative Clustering. © Springer-Verlag Berlin Heidelberg 2005.