Siriporn, Chimphlee and Salim, Naomie and Ngadiman, Mohd Salihin and Witcha, Chimphlee (2006) Using Markov Model and Association Rules for Web Access Prediction. In: -, 2003, -.
Mining user patterns of log file can provide significant and useful informative knowledge. A large amount of research has been done on trying to predict correctly the pages a user will request. This task requires the development of models that can predicts a userâ€™s next request to a web server. In this paper, we propose a method for constructing first-order and second-order Markov models of Web site access prediction based on past visitor behavior and compare it association rules technique. This algorithm has been used to cluster similar transition behaviors for efficient used to further improve the efficiency of prediction. From this comparison we propose a best overall method and empirically test the proposed model on real web logs.
|Item Type:||Conference or Workshop Item (Paper)|
|Uncontrolled Keywords:||Association rules, Marov Model,prediction|
|Subjects:||Q Science > Q Science (General)|
|Divisions:||Computer Science and Information System (Formerly known)|
|Deposited By:||Norazlizafarah Anuar|
|Deposited On:||24 May 2007 07:28|
|Last Modified:||01 Jun 2010 03:08|
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