Navigation Patterns Mining Approach based on Expectation Maximization Algorithm
Abstract:Web usage mining algorithms have been widely
utilized for modeling user web navigation behavior. In this study we
advance a model for mining of user-s navigation pattern. The model
makes user model based on expectation-maximization (EM)
algorithm.An EM algorithm is used in statistics for finding maximum
likelihood estimates of parameters in probabilistic models, where the
model depends on unobserved latent variables. The experimental
results represent that by decreasing the number of clusters, the log
likelihood converges toward lower values and probability of the
largest cluster will be decreased while the number of the clusters
increases in each treatment.
 B. Mobasher, R. Cooley, and J. Srivastava, "Automatic personalization
based on Web usage mining," Communications of the ACM, vol. 43, pp.
 T. W. Yan, M. Jacobsen, H. Garcia-Molina, and U. Dayal, "From user
access patterns to dynamic hypertext linking," Computer Networks and
ISDN Systems, vol. 28, pp. 1007-1014, 1996.
 I. Cadez, D. Heckerman, C. Meek, P. Smyth, and S. White, "Visualization
of navigation patterns on a Web site using model-based clustering,"
Proceedings of the sixth ACM SIGKDD international conference on
Knowledge discovery and data mining, pp. 280-284, 2000.
 A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum likelihood from
incomplete data via the EM algorithm," Journal of the Royal Statistical
Society, vol. 39, pp. 1-38, 1977.
 C. R. Anderson, P. Domingos, and D. S. Weld, "Adaptive Web Navigation
for Wireless Devices," 2001, pp. 879-884.
 D. Tanasa and B. Trousse, "Advanced data preprocessing for intersites
Web usage mining," Intelligent Systems, IEEE, vol. 19, pp. 59-65, 2004.
 M. Spiliopoulou, B. Mobasher, B. Berendt, and M. Nakagawa, "A
Framework for the Evaluation of Session Reconstruction Heuristics in
Web-Usage Analysis," INFORMS Journal on Computing, vol. 15, pp. 171-
 R. Cooley, B. Mobasher, and J. Srivastava, "Data Preparation for Mining
World Wide Web Browsing Patterns," Knowledge and Information
Systems, vol. 1, pp. 5-32, 1999.