A Spam Filtering Scheme Based on Scalable Decision Tree
Jing Wang, Xing Wei Wang, Min Huang · Applied Mechanics and Materials · 2014
Nowadays, Internet has been flooded with spams, which not only disrupts routine network application, but also affects people’s normal life and work. Thus, an accurate and effective spam filtering scheme is indispensable. In this paper, the scalable decision tree is utilized to analyze feature information of email-header to obtain anti-spam rules, which can be further used to filter spams. As is shown in the test result that the proposed scheme has satisfying performance and it is feasible in spam filtering.