ML Anthology

A Suffix Tree Approach to Anti-Spam Email Filtering

Rajesh Mysore Pampapathi, Boris G. Mirkin, Mark Levene
MLJ 2006 pp. 309-338
doi:10.1007/S10994-006-9505-Y /mlj/2006/pampapathi2006mlj-suffix/

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.

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Text

Pampapathi et al. "A Suffix Tree Approach to Anti-Spam Email Filtering." Machine Learning, 2006. doi:10.1007/S10994-006-9505-Y

Markdown

[Pampapathi et al. "A Suffix Tree Approach to Anti-Spam Email Filtering." Machine Learning, 2006.](https://mlanthology.org/mlj/2006/pampapathi2006mlj-suffix/) doi:10.1007/S10994-006-9505-Y

BibTeX

@article{pampapathi2006mlj-suffix,
  title     = {{A Suffix Tree Approach to Anti-Spam Email Filtering}},
  author    = {Pampapathi, Rajesh Mysore and Mirkin, Boris G. and Levene, Mark},
  journal   = {Machine Learning},
  year      = {2006},
  pages     = {309-338},
  doi       = {10.1007/S10994-006-9505-Y},
  volume    = {65},
  url       = {https://mlanthology.org/mlj/2006/pampapathi2006mlj-suffix/}
}