Machine Learning for Spam Detection References

José María Gómez Hidalgo
Universidad Europea de Madrid
jmgomez-AT-uem-DOT-es
http://www.esi.uem.es/~jmgomez

January 31, 2005

Abstract: This document contains a list of references to (mainly) research papers dealing with Machine Learning methods for building spam filters (often known as Bayesian filters). Papers discussing additional methods for addressing the spam problem, discussing the problem, or even industrial white papers and evaluations are included, as they may help to present the problem, current techniques and as a basis of integrated approaches. Feel free to suggest me new entries, or corrections in current references or in the document.

Important disclaimer: I only do list online references.

1  The spam problem

The reports referenced here discuss the problem of spam from a general point of view, including taxonomies of methods for dealing with it, as well as papers discussing integrated methods.

The entries in the BibTeX file are tagged with the keyword GENERAL, and include: [10, 26, 28, 38, 39, 47, 73, 82]

2  Machine Learning based (Bayesian) filters

These reports discuss Machine Learning methods building spam filters. These filters are also known as Bayesian or statistical filters. The Machine Learning approach consists of: Papers discussing one or more of the previous topics, as well as methods to attack them, are included in this section. I also include papers that describe spam trens and characteristics, as they affect the definition of attributes for learning. The entries in the BibTeX file are tagged with the keyword BAYESIAN, and include: [3, 4, 5, 6, 7, 8, 14, 17, 19, 20, 21, 24, 23, 25, 30, 31, 32, 33, 40, 42, 43, 48, 52, 53, 54, 55, 56, 57, 58, 60, 59, 61, 63, 64, 65, 66, 67, 69, 68, 70, 71, 72, 75, 76, 77, 78, 83, 84, 85, 86].

3  Other technical methods

Other methods include: Other papers on technical methods for stopping or controlling spam, are tagged with the keyword TECHNICAL in the BibTeX file, and include: [9, 37, 46, 80, 81].

4  Industrial white papers and evaluations, and miscelanea

The entries in the BibTeX file are tagged with the keyword OTHER, and include: [13, 62].

References

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