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    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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    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: School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Sarah Hall
    Date Deposited: 25 May 2021 19:08
    Last Modified: 25 May 2021 19:08
    URI: https://eprints.bbk.ac.uk/id/eprint/44429

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