Abstract
Session similarity is a key issue in web session clustering. Existing approaches vary on session representation and similarity computation. However, they do not consider the similarity between pages, which is crucial due to the semantic gap between URLs and corresponding application events. This paper presents a domain taxonomy-based clustering approach, which extends the WLCS technique by integrating page similarity to compute session similarity. The approach can be applied to both usage and navigation clustering purposes.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Banerjee, A., Ghosh, J.: Clickstream Clustering Using Weighted Longest Common Subsequences. In: Proceedings of the Web Mining Workshop at the 1st SIAM Conference on Data Mining, Chicago (2001)
Cooley, R., Mobasher, B., Srivastava, J.: Data Preparation for Mining Word Wide Web Browsing Patterns. Knowledge and Information Systems (1999)
Fu, Y., Sandhu, K., Shih, M.: A Generalization-Based Approach to Clustering of Web Usage Sessions. In: Masand, B., Spiliopoulou, M. (eds.) WebKDD 1999. LNCS (LNAI), vol. 1836, pp. 21–38. Springer, Heidelberg (2000)
Ganesan, P., Garcia-Molina, H., Widom, J.: Exploiting Hierarchical Domain Structure to Compute Similarity. ACM TOIS 21(1), 64–93 (2003)
Gündüz, S., Özsu, M.T.: A Web page prediction model based on click-stream tree representation of user behavior. In: Proceedings of the 9th ACM (SIGKDD), pp. 535–540 (2003)
Marquardt, C., Becker, K., Ruiz, D.: A Pre-processing Tool for Web Usage Mining in the Distance Education Domain. In: Proceedings of the 8th IDEAS, Coimbra, pp. 78–87 (2004)
Mobasher, B.: Web Usage Mining and Personalization. In: Singh, M.P. (ed.) Draft Chapter in Practical Handbook of Internet Computing. CRC Press, Boca Raton (2004)
Stume, G., Berendt, B., Hotho, A.: Usage Mining for and on the Semantic Web. In: Proceedings of NSF Workshop, Baltimore, pp. 77–86 (2002)
Wang, W., Zaiane, O.Z.: Clustering Web Sessions by Sequence Alignment. In: International Workshop on DEXA, pp. 394–398 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Nichele, C.M., Becker, K. (2006). Clustering Web Sessions by Levels of Page Similarity. In: Ng, WK., Kitsuregawa, M., Li, J., Chang, K. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2006. Lecture Notes in Computer Science(), vol 3918. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11731139_40
Download citation
DOI: https://doi.org/10.1007/11731139_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33206-0
Online ISBN: 978-3-540-33207-7
eBook Packages: Computer ScienceComputer Science (R0)