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Comparing content-filter techniques for stopping spam

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conference contribution
posted on 26.11.2008 by Andrew Akehurst, Iain Phillips, Mark S. Withall
There are many new theoretical techniques for detecting spam e-mail based upon the message contents. Although Bayesian methods are the most wellknown, there are other approaches for classifying information. This paper establishes some criteria for measuring spam filter effectiveness and compares the Boosting and Support Vector Machine approaches with some well-known existing filter software. It also examines ways of transforming e-mail messages into a form which is more readily processable by such algorithms.

History

School

  • Science

Department

  • Computer Science

Citation

AKEHURST, A., PHILLIPS, I. and WITHALL, M., 2004. Comparing content-filter techniques for stopping spam. Workshop on Computational Intelligence (UKCI 2004), 6-8 September, Loughborough University

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NA (Not Applicable or Unknown)

Publication date

2004

Notes

This is a conference paper.

Language

en

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