Abstract
The paper presents new measures for characterizing sequences of user actions. They are aimed at categorizing user behavior on intranet sites. Their relevance is evaluated using different encoding and clustering algorithms. New criteria are introduced for comparing clustering methods.
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References
Chen M., Park J., Yu P., Data mining for path traversal patterns in a web environment, 16th ICDCP, 1996.
Catledge L., Pitkow J.E.: Characterizing Browsing Strategies in the world wide web, Comp. Net. and ISDN systems, 27, 1995.
The comprehensive r archive network, http://www.//r-project.org
Cheeseman P., Kelly J., Self M., Stutz J., Taylor W., Freeman D., Autoclass: a Bayesian classification system, Fifth ICML. Morgan Kaufmann, 1988.
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Draier, T., Gallinari, P. (2001). Characterizing Sequences of User Actions for Access Logs Analysis. In: Bauer, M., Gmytrasiewicz, P.J., Vassileva, J. (eds) User Modeling 2001. UM 2001. Lecture Notes in Computer Science(), vol 2109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44566-8_29
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DOI: https://doi.org/10.1007/3-540-44566-8_29
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