Abstract
Web personalization is the process of customizing a Web site to the preferences of users, according to the knowledge gained from usage data in the form of user profiles. In this work, we experimentally evaluate a fuzzy clustering approach for the discovery of usage profiles that can be effective in Web personalization. The approach derives profiles in the form of clusters extracted from preprocessed Web usage data. The use of a fuzzy clustering algorithm enable the generation of overlapping clusters that can capture the uncertainty among Web users navigation behavior based on their interest. Preliminary experimental results are presented to show the clusters generated by mining the access log data of a Web site.
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References
Anderson, C.R., Domingos, P., Weld, D.S.: Adaptive Web navigation for wireless devices. In: Proc. of the 17th International Joint Conference on Artificial Intelligence(IJCAI-01), pp. 879–884 (2001)
Bezdek, J.C.: Pattern recognition with fuzzy objective function algorithms. Plenum Press, New York (1981)
Castellano, G., Fanelli, A.M., Torsello, M.A.: LODAP: A Log Data Preprocessor for mining Web browsing patterns. In: Proc. of The 6th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases (AIKED 2007), Corfu Island, Greece (2007)
Facca, F.M., Lanzi, P.L.: Mining interesting knowledge from weblogs: a survey. Data and Knowledge Engineering 53, 225–241 (2005)
Frias-Martinez, E., Magoulas, G., Chen, S., Macredie, R.: Modeling human behavior in user-adaptive systems: Recent advances using soft computing techniques. Expert Systems with Applications 29, 320–329 (2005)
Garofalakis, M.N., Rastogi, R., Seshadri, S., Shim, K.: Data mining and the web: past, present and future. In: Proc. of the second international workshop on web information and data management, ACM, New York (1999)
Joshi, A., Joshi, K.: On mining Web access logs. In: ACM SIGMOID Workshop on Research issues in Data Mining and Knowledge discovery, pp. 63–69 (2000)
Mobasher, B., Cooley, R., Srivastava, J.: Automatic personalization based on Web usage mining. TR-99010, Department of Computer Science. DePaul University (1999)
Nasraoui, O.: World Wide Web Personalization. In: Wang, J. (ed.) Encyclopedia of Data Mining and Data Warehousing, Idea Group (2005)
Nasraoui, O., Frigui, H., Joshi, A., Krishnapuram, R.: Mining Web access log using relational competitive fuzzy clustering. In: Proc. of the Eight International Fuzzy System Association World Congress (1999)
Pierrakos, D., Paliouras, G., Papatheodorou, C., Spyropoulos, C.D.: Web usage mining as a tool for personalization: a survey. User Modeling and User-Adapted Interaction 13(4), 311–372 (2003)
Suryavanshi, B.S., Shiri, N., Mudur, S.P.: An efficient technique for mining usage profiles using Relational Fuzzy Subtractive Clustering. In: Proc. of WIRI 2005, Tokyo, Japan (2005)
Vakali, A., Pokorny, J., Dalamagas, T.: An Overview of Web Data Clustering Practices. In: EDBT Workshops, pp. 597–606 (2004)
Velasquez, J.D., Yasuda, H., Aoki, T., Weber, R., Vera, E.: Using Self Organizing Feature Maps to Acquire Knowledge about Visitor Behavior in a Web Site. In: Palade, V., Howlett, R.J., Jain, L. (eds.) KES 2003. LNCS, vol. 2773, pp. 951–958. Springer, Heidelberg (2003)
Wang, X., Abraham, A., Smith, K.A.: Intelligent web traffic mining and analysis. Journal of Network and Computer Applications 28, 147–165 (2005)
W3C. Logging Control in W3C httpd, http://www.w3.org/Daemon/User/Config/Logging.html
Xie, Y., Phoha, V.V.: Web user clustering from access log using belief function. In: Proc. of the First International Conference on Knowledge capture (K-CAP 2001), pp. 202–208. ACM Press, New York (2001)
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Castellano, G., Mesto, F., Minunno, M., Torsello, M.A. (2007). Web User Profiling Using Fuzzy Clustering. In: Masulli, F., Mitra, S., Pasi, G. (eds) Applications of Fuzzy Sets Theory. WILF 2007. Lecture Notes in Computer Science(), vol 4578. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73400-0_12
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DOI: https://doi.org/10.1007/978-3-540-73400-0_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73399-7
Online ISBN: 978-3-540-73400-0
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