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Finding Template Mails from Spam Corpus Using Genetic Algorithm and K-Means Algorithm

Spammers are using email templates for sending spam. To promote some service or product, they send mails by creating templates and merging the details of receivers with the template. Since they are using templates, similarities can be found among mails and spam detection softwares can easily ignore the forthcoming spam mails. Our objective is to identify the template mails from the whole corpora of training set emails to make the filtering process faster. In this paper we propose how supervised Genetic algorithm and K-Means algorithm can be used to generate the best population, which in turn used for spam classification.