A suffix tree approach to anti-spam email filtering |
| |
Authors: | Rajesh Pampapathi Boris Mirkin Mark Levene |
| |
Affiliation: | (1) School of Computer Science and Information Systems, Birkbeck College, University of London, London |
| |
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.
Editor: Tom Fawcett |
| |
Keywords: | Suffix tree Spam E-mail filtering Scoring function Text categorization |
本文献已被 SpringerLink 等数据库收录! |