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A Cluster Analysis for Personalized web Recommendation

CHEN Xue-gang1,2,YANG Lei1(1.School of Computer and Communication,Hunan University,Changsha 410082,China;2.Department of Computer,Xiangnan University,Chenzhou 423000,China)  
In order to provide better personalized recommendation service,and cluster analysis methods based on association has been improved,which mining model of the users access with interests of similar access,and user model of non-related is separated a clustering.An algorithm based on association is proposed.It is proved that the algorithm can reduce a large number of user model of non-related,so improve the quality of the personalized recommendations.It is laid the foundation to further study the personalized recommendation technology.
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