Spam filter using C4.5 decision trees - Alegre, Carlos Jr. H. (2003)
This paper describes the development of a prototype system of a spam filter to provide additional protection from unwanted, unsolicitated bulk email. The system will be using C4.5 decision trees as its method to classify whether a particular message is spam. Nowadays, spammers are continually adapting new strategies on how they can fool existing spam classifying software. The algorithm we are developing would be able to adapt to new formats spammers use to trick other filters through its ability to learn from the actions of the user. In this paper, we discuss problems brought about by the growing volume of spam emails and suggest solutions to automatically filter personal email. We also present a filtering system, UBE MASHER (Unsolicited Bulk Email Managing Agent; Studing Human Email Recognition patterns), which has been adapted to a popular e-mail client. Results are presented from a number of experiments and show that a system such as UBE MASHER could become a useful and valuable part of any e-mail client.