The upsurge in the volume of unwanted emails called spam has created an intense need for
the development of more dependable and robust antispam filters. Machine learning …

In this paper, we present a comprehensive review of recent developments in the application
of machine learning algorithms to Spam filtering, focusing on both textual-and image-based …

Naive Bayes is very popular in commercial and open-source anti-spam e-mail filters. There
are, however, several forms of Naive Bayes, something the anti-spam literature does not …

Spam is information crafted to be delivered to a large number of recipients, in spite of their
wishes. A spam filter is an automated tool to recognize spam so as to prevent its delivery …

Electronic mail has eased communication methods for many organisations as well as
individuals. This method is exploited for fraudulent gain by spammers through sending …

Clearly, machine learning techniques can play an important role in filtering spam email
because ample training data is available to build a robust classifier. However, spam filtering …

Spam filtering poses a special problem in text categorization, of which the defining
characteristic is that filters face an active adversary, which constantly attempts to evade …

E-mail spam continues to become a problem on the Internet. Spammed e-mail may contain
many copies of the same message, commercial advertisement or other irrelevant posts like …

In this paper we analyse the strengths and weaknesses of the mainly used feature selection
methods in text categorization when they are applied to the spam problem domain. Several …

Junk e-mail detection and filtering can be considered a cost-sensitive classification problem.
Nevertheless, preprocessing methods and noise reduction strategies used to enhance the …