An Evolutionary Web Clustering for Web Page Predicting

Abstract

In this paper a web user's surfing behavior is represented as a web access pattern. Then we adopt a fuzzy rough c-means method to cluster these web access patterns into groups. Each group includes patterns disclosing same or similar surfing behaviors. And an optimized algorithm is employed to gain the better clustering results. Finally, we have performed an evaluation of the proposed approach with an example and an experiment. We have found that the proposed algorithm is feasible and effective.