An Intelligent SPAM filter - GetEmail5
T. Hassan, P. Cole, Chun Che Fung · 2006
As the increasing reliance on electronic mail (email) continues, unsolicited bulk email (SPAM) also continues to grow because it is a very cheap way for advertising. These unwanted emails are now causing a serious problem in clogging the Internet traffic and filling up the email inboxes thereby leaving no space for legitimate emails to pass through. In addition, dealing with SPAM messages is costly to the users as it requires time and effort to examine them individually. In this paper, we propose an intelligent and trainable SPAM filter called GetEmail5. We have also evaluated the proposed filter against two commercial filters, EmailProtect and SpamEater