Comparison of a SOM based sequence analysis system and naive Bayesian classifier for spam filtering

@article{Luo2005ComparisonOA,
  title={Comparison of a SOM based sequence analysis system and naive Bayesian classifier for spam filtering},
  author={X. Luo and N. Zincir-Heywood},
  journal={Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.},
  year={2005},
  volume={4},
  pages={2571-2576 vol. 4}
}
  • X. Luo, N. Zincir-Heywood
  • Published 2005
  • Computer Science
  • Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.
  • The problem introduced by the unsolicited bulk emails, also known as "spam" generates a need for reliable anti-spam filters. In this paper, we design and compare the performance of a newly designed SOM based sequence analysis (SBSA) system for the spam filtering task. The system is based on a SOM based sequential data representation combined with a kNN classifier designed to make use of word sequence information. We compare this system with the traditional baseline method naive Bayesian filter… CONTINUE READING
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