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http://dx.doi.org/10.5391/IJFIS.2007.7.2.091

A Web Recommendation System using Grid based Support Vector Machines  

Jun, Sung-Hae (Department of Bioinformatics & Statistics, Cheongju University)
Publication Information
International Journal of Fuzzy Logic and Intelligent Systems / v.7, no.2, 2007 , pp. 91-95 More about this Journal
Abstract
Main goal of web recommendation system is to study how user behavior on a website can be predicted by analyzing web log data which contain the visited web pages. Many researches of the web recommendation system have been studied. To construct web recommendation system, web mining is needed. Especially, web usage analysis of web mining is a tool for recommendation model. In this paper, we propose web recommendation system using grid based support vector machines for improvement of web recommendation system. To verify the performance of our system, we make experiments using the data set from our web server.
Keywords
Web Recommendation System; Support Vector Machines; Grid Search;
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Times Cited By KSCI : 1  (Citation Analysis)
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1 T. M. Mitchell, Machine Learning, McGraw-Hill, 1997
2 R. Cooley, P. N. Tan, J. Srivastava, 'Discovery of interesting usage patterns from web data', Technical Report TR 99-022, University of Minnesota, 1999
3 P. Kazienko, P. Kuzminska, 'The influence of indirect association rules on recommendation ranking lists Intelligent Systems Design and Applications', Proceedings of 5th International Conference on ISDA, pp. 482 - 487, 2005
4 D. Fisher, K. Hildrum, J. Hong, M. Newman, M. Thomas, R. Vuduc, 'SWAMI: A Framework for Collaborative Filtering Algorithm Development and Evaluation', Proceeding of SIGIR 2000, ACM Press, 2000
5 S. H. Jun, 'Web Usage Mining Using Support Vector Machine', Lecture Note in Computer Science, vol. 3512, pp. 349-356, 2005
6 R. Agrawal, T. Imielinski, A. Swami, 'Mining association rules between sets of items in large databases', Proceeding of the ACM SIGMOD International Conference on Management of Data, 1993
7 A. J. Smola, Regression estimation with support vector learning machines, Master's thesis, Technische University, 1996
8 J. S. Jang, S. H. Jun, K. W. Oh, 'Fuzzy Web Usage Mining for User Modeling', International Journal of Fuzzy Logic and Intelligent Systems, vol. 2, no. 3, pp. 204-209, 2002   DOI   ScienceOn
9 S. Haykin, Neural Networks: A Comprehensive Foundation, Prentice Hall, 1999
10 P. Resnick, N. Lacovou, M. Suchak, P. Berfstrom, J. Riedl, 'GroupLens: An Open Architecture for collaborative filtering of Netnews', Proceedings of ACM 1994 Conference on Computer Supported Cooperative Work, 1994
11 J. Han, M. Kamber, Data Mining Concepts and Techniques, Morgan Kaufmann, 2001
12 V. Vapnik, Statistical Learning Theory, John Wiley & Sons
13 P. Giudici, Applied Data Mining, Wiley, 2003