A suffix tree approach to anti-spam email filtering

Pampapathi, R.M. and Mirkin, B.G. and Levene, Mark (2006) A suffix tree approach to anti-spam email filtering. Machine Learning 65 (1), pp. 309-338. ISSN 0885-6125.

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Official URL: https://doi.org/10.1007/s10994-006-9505-y

Abstract

We present an approach to email filtering based on the suffix tree data structure. A method for the scoring of emails using the suffix tree is developed and a number of scoring and score normalisation functions are tested. Our results show that the character level representation of emails and classes facilitated by the suffix tree can significantly improve classification accuracy when compared with the currently popular methods, such as naive Bayes. We believe the method can be extended to the classification of documents in other domains.

Metadata

Item Type:	Article
School:	Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
Depositing User:	Sarah Hall
Date Deposited:	25 May 2021 19:08
Last Modified:	09 Aug 2023 12:51
URI:	https://eprints.bbk.ac.uk/id/eprint/44429

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