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={Xiao Luo and Nur Zincir-Heywood},
  journal={Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.},
  year={2005},
  volume={4},
  pages={2571-2576 vol. 4}
}
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