Developing a Spam Email Detector
Email is obviously important for many types of group communication that have become most widely used by millions of people, individuals and organizations. At the same time it has become a prone to threats. The most popular such threats are what are called a spam, also known as unsolicited bulk email or junk email. To detect spams, this paper proposes a spam detection approach using Naive Bayesian (NB) classifier, where this classifier identifies email messages as being spam or legitimate, based on the content (i.e. body) of these messages.