Evaluating Arabic spam classifiers using link analysis
Proceedings of the 3rd International Conference on Information and Communication Systems
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Text classification algorithms, such SVM, and Naïve Bayes, have been developed to build up search engines and construct spam email filters. As a simple yet powerful sample of Bayesian Theorem, Naïve Bayes shows advantages in text classification yielding satisfactory results. In this paper, a spam email detector is developed using Naïve Bayes algorithm. We use pre-classified emails (priory knowledge) to train the spam email detector. With the model generated from the training step, the detector is able to decide whether an email is a spam email or an ordinary email.