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Please use this identifier to cite or link to this item: http://hdl.handle.net/2031/3563

Title: Web profiling and navigation path analysis
Authors: Lam, Ming Yan (林洺因)
Department: Department of Computer Science
Issue Date: Jul-2006
Award: Won the Second Class Award in the Pan-Pearl River Delta Region University IT Project Competition (泛珠三角大學生計算機作品賽) organized by Guangdong Computer Federation (China) (廣東省計算機學會) in 2006.
Supervisor: Dr. Wong, Hau San
Type: Software
Abstract: The rich information in the World Wide Web has created an information overloading problem for web users. The technology of Web personalization targets to solve such a problem and thus recommendation systems were studied. Nowadays, Web Usage Mining technique is overtaking the position of traditional collaborative filtering technology, moving traditional ranking style into web log and navigation path analysis approach. The Markov model is one of the well performed prediction model that is suitable for a recommendation system. However, it suffers from state complexity problem and needs to be improved. Association Rule mining is another technique for data mining and pattern discovery. There is also room to improve for the performance of Association Rule. This project focuses on the studies of different optimization schemes for Markov model and Association Rule. It takes experiments on different kinds of improvement studies. It also shows the result of different kinds of model optimization scheme. A profiling modeler and an online recommendation engine are also implemented for testing and simulation.
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