Implementation of vocabulary-based classification for spam filtering
Mallikka Rajalingam, Valliappan Raman, Putra Sumari · 2016
The excessive consumption of network bandwidth for transmitting unwanted emails has always been a major problem in the web, since, the existing classification approaches are still lacking for a complete solution. This paper presents an enhanced vocabulary-based dictionary algorithm for protecting web user by receiving unwanted spam mails. The proposed algorithm identifies and classifies legitimate incoming mails against unsolicited email attacks. We present a porter stemmer algorithm as a part of normalization process for removing the common morphological and inflexional endings from English words. A comparative study and evaluation of these classification approaches are carried out using machine-learning techniques. The performance of the proposed algorithm is visualized using confusion matrix. The experimental results show that our method produces less number of false negatives when compared with existing techniques.