%0 Journal Article
%T Spam filtering algorithm based on supervised Bayesian parameter estimation<br>基于有监督Bayesian网络的垃圾邮件过滤
%A LIU Zhen
%A ZHOU Ming-tian
%A <br>刘震
%A 周明天
%J 计算机应用
%D 2006
%I 
%X To improve the reliability and completeness of spam filtering, the E-mail message format was carefully analyzed, and the spam characteristics were generalized and classified. Based on these analysis, a supervised Bayesian network for E-mail classifer was constructed. Parameter estimation on this network realized an uncertain inference to identify E-mail's sort. On-line learning for different E-mail testing sets shows that such a classifying network can ensure the classification and filtering efficiently. It practically provides a viable solution by building a supervised Bayesian classifying network to execute relatively complete characteristics learning and improve the accuracy of E-mail filtering.
%K spam
%K Bayesian network
%K E-mail filtering
%K parameter estimation<br>垃圾邮件
%K Bayesian网络
%K 邮件过滤
%K 参数估计
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=79C73891293AF429&yid=37904DC365DD7266&vid=96C778EE049EE47D&iid=38B194292C032A66&sid=C7A2B92569DF5458&eid=08CFB5BB972ABBF3&journal_id=1001-9081&journal_name=计算机应用&referenced_num=5&reference_num=8