Multiobjective evolutionary clustering of Web user sessions: a case study in Web page recommendation


Demir G. N. , Uyar A. Ş. , GUNDUZ-OGUDUCU S.

SOFT COMPUTING, vol.14, no.6, pp.579-597, 2010 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 14 Issue: 6
  • Publication Date: 2010
  • Doi Number: 10.1007/s00500-009-0428-y
  • Title of Journal : SOFT COMPUTING
  • Page Numbers: pp.579-597

Abstract

In this study, we experiment with several multiobjective evolutionary algorithms to determine a suitable approach for clustering Web user sessions, which consist of sequences of Web pages visited by the users. Our experimental results show that the multiobjective evolutionary algorithm-based approaches are successful for sequence clustering. We look at a commonly used cluster validity index to verify our findings. The results for this index indicate that the clustering solutions are of high quality. As a case study, the obtained clusters are then used in a Web recommender system for representing usage patterns. As a result of the experiments, we see that these approaches can successfully be applied for generating clustering solutions that lead to a high recommendation accuracy in the recommender model we used in this paper.