Title :
Anti-spam filtering: a centroid-based classification approach
Author :
Soonthornphisaj, Nuanwan ; Chaikulseriwat, Kanokwan ; Tang-On, Piyanan
Author_Institution :
Dept. of Comput. Sci., Kasetsart Univ., Bangkok, Thailand
Abstract :
Nowadays, electronic mail is the most popular and convenient way for communication in daily life. Spam or junk E-mails are also increasingly appearing in the mail box from commercial Web sites. Therefore, we investigated the way to filter these junk e-mails through a variety of techniques, i.e. naive Bayesian, k-nearest neighbor and centroid based approach. We found that the centroid-based approach is the most suitable for the mail filtering application with 83.00 % of correctness. The outcome of our research has been successfully implemented as an intelligent Web mail service with the anti-spam mail filtering feature plug-in.
Keywords :
Bayes methods; Web sites; electronic mail; E-mails; anti-spam filtering; centroid-based classification; commercial Web sites; electronic mail; intelligent Web mail service; k-nearest neighbor technique; mail filtering plug-in; naive Bayesian technique; Bayesian methods; Classification algorithms; Electronic mail; Frequency; Information filtering; Information filters; Postal services; Power capacitors; Supervised learning; Unsolicited electronic mail;
Conference_Titel :
Signal Processing, 2002 6th International Conference on
Print_ISBN :
0-7803-7488-6
DOI :
10.1109/ICOSP.2002.1179980
