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Typically, spam filters are built on the assumption that the characteristics of e-mails in the training set is identical to those in individual users' inboxes on which it will be applied. This assumption is oftentimes incorrect leading to poor performance of the filter. A personalized spam filter is built by taking into account the characteristics of e-mails in individual users' inboxes. We present an automatic approach for personalized spam filtering that does not require users' feedback. Thedoi:10.1109/ictai.2007.66 dblp:conf/ictai/JunejoK07 fatcat:ucyps6ixrnfk5jexny66sar75i