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

Authors:
G. Nildem Demir;A. Şima Uyar;Şule Gündüz-Öğüdücü
Affiliations:
Istanbul Technical University, Department of Computer Engineering, 34469, Maslak, Istanbul, Turkey;Istanbul Technical University, Department of Computer Engineering, 34469, Maslak, Istanbul, Turkey;Istanbul Technical University, Department of Computer Engineering, 34469, Maslak, Istanbul, Turkey
Venue:
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Year:
2010

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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.