%0 Journal Article
%T SPAM E-MAIL CHARACTERIZATION: AN EXPERIMENTAL PERFORMANCE COMPARISON OF MACHINE LEARNING
%A Avijit Mallik
%A Md. Sabbir Ahmad
%A Md. Arman Arefin
%A Md. Sarwar Hosen
%J International Journal of Advanced Engineering and Science
%P 44-51
%@ 2304-7720
%D 2017
%R -
%X The increasing volume of unsolicited mass e-mail (otherwise called spam) has generated a need for reliable against spam filters. Utilizing a classifier based on machine learning techniques to naturally filter out spam e-mail has drawn many researchers' attention. In this paper, we review some of relevant ideas and do a set of systematic experiments on e-mail categorization, which has been conducted with four machine learning calculations applied to different parts of e-mail. Experimental results reveal that the header of e-mail provides very useful data for all the machine learning calculations considered to detect spam e-mail.
%K E-mail
%K Spam
%K Machine Learning
%K Networking.
%U http://ijaes.elitehall.com/Vol%206%20No%202-5.pdf