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《Journal of Chongqing University of Posts and Telecommunications(Natural Science)》 2006-04
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Improved Bayesian mail filtering algorithm based on slipping window

LAN Ya,WU Yu,WANG Guo-yin,DONG Bei(College of Computer Science and Tecnology,Chongqing University of Posts and Telecommunication,Chongqing 400065,P.R.China)  
In text classification,Bayesianalgorithmneeds feature selection,but the traditional feature selection algorithmis not accurate enough,which affects classification precision.To order to resolve the problem,a new improved bayes algorithm based on slipping window method is proposed.The algorithm can extend the character's number to improve the efficiency.Experimental results showed that our algorithm performed more efficienthy than the traditional methods in classification precision.
【Fund】: 新世纪优秀人才支持计划(NCET);; 重庆市自然科学基金项目(2005BB2063)
【CateGory Index】: TP393.098
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