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《Computer Engineering and Applications》 2009-08
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Application of Web usage mining based on improved genetic algorithm

LEI Liang,LI Shan-jun,PENG Jun 1.School of Electronic Information Engineering,Chongqing University of Science and Technology,Chongqing 400050,China 2.Information Center of Chongqing Association for Science and Technology,Chongqing 401174,China  
Web usage mining is a hot research direction of Web data mining.In this paper,an improved genetic algorithm is pro-posed to overcome the shortage of early convergence and stagnation in the traditional genetic algorithm,which is based on uncon-vertible rate of crossover operator and mutation operator.Moreover,the user page interest measure threshold is introduced into the association rules mining.Lastly,the improved genetic algorithm is successfully applied to a commerce Web server log mining and the experiment results indicate that the proposed algorithm is an effective method to avoid early convergence.
【Fund】: 重庆市科技攻关计划No.CSTC2007AB2047~~
【CateGory Index】: TP311.13;TP18
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