Spam emails have been traditionally seen as just annoying and unsolicited emails
containing advertisements, but they increasingly include scams, malware or phishing. In …

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 …

Many classification techniques used for identifying spam emails, treat spam filtering as a
binary classification problem. That is, the incoming email is either spam or non-spam. This …

Email spam is a serious problem that annoys recipients and wastes their time. Machine-
learning methods have been prevalent in spam detection systems owing to their efficiency in …

Technological advances are accelerating the dissemination of information. Today, millions
of devices and their users are connected to the Internet, allowing businesses to interact with …

Rapid growth in the volume of unsolicited and unwanted messages has inspired the
development of many anti-spam methods. Supervised anti-spam filters using machine …

We present an inclusive review of recent and successful content-based e-mail spam filtering
techniques. Our focus is mainly on machine learning-based spam filters and variants …

We present a comprehensive review of the most effective content-based e-mail spam
filtering techniques. We focus primarily on Machine Learning-based spam filters and their …

Spam represents a genuine irritation for email users, since it often disturbs them during their
work or free time. Machine learning approaches are commonly utilized as the engine of …

Email spam has been a big issue in recent years. As the percentage of internet users grows,
so does the number of spam emails. Technologies are being used for illegitimate and …