Learning Spam: Simple Techniques For Freely-Available Software

The problem of automatically filtering out spam e-mail using a classifier based on machine learning methods is of great recent interest. This paper gives an introduction to machine learning methods for spam filtering, reviewing some of the relevant ideas and work in the open source community. An overview of several feature detection and machine learning techniques for spam filtering is given. The authors’ freely-available implementations of these techniques are discussed. The techniques’ performance on several different corpora are evaluated. Finally, some conclusions are drawn about the state of the art and about fruitful directions for spam filtering for freely-available UNIX software practitioners.

• Type: Conference
• Year: 2003
• Where: USENIX
• Authors: Bart Massey, Mick Thomure, Raya Budrevich, Scott Long
• Keywords: Machine Learning, Machine Learning Methods, Machine Learning Techniques, Operating System, USENIX 2003