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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/4026

Title: Comparing content-filter techniques for stopping spam
Authors: Akehurst, Andrew
Phillips, Iain W.
Withall, Mark S.
Issue Date: 2004
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
Abstract: 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.
Description: This is a conference paper.
Version: Not specified
URI: https://dspace.lboro.ac.uk/2134/4026
Appears in Collections:Conference Papers and Presentations (Computer Science)

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