论文信息 - A LVQ-based neural network anti-spam email approach

A LVQ-based neural network anti-spam email approach

Along with wide application of e-mail nowadays, many spam e-mails flood into people's email inboxes and bring catastrophe to their study and work. This paper presents a novel anti-spam e-mail filter based-LVQ network in terms of spam e-mails which are mainly made up of several kinds commercial or political spam emails at present. Our experiment has proved that the filter based on LVQ is superior to Bayes-based and BP-based approaches in total performances apparently.

Xu Zhou | Xianliang Lu | Chuan Zhan | Meng-shu Hou

[1] Kenneth Ward Church,et al. Word Association Norms, Mutual Information, and Lexicography , 1989, ACL.

[2] Lluís Màrquez i Villodre,et al. Boosting Trees for Anti-Spam Email Filtering , 2001, ArXiv.

[3] William W. Cohen. Learning Rules that Classify E-Mail , 1996 .

[4] Martin T. Hagan,et al. Neural network design , 1995 .

[5] Susan T. Dumais,et al. A Bayesian Approach to Filtering Junk E-Mail , 1998, AAAI 1998.

[6] Irena Koprinska,et al. A neural network based approach to automated e-mail classification , 2003, Proceedings IEEE/WIC International Conference on Web Intelligence (WI 2003).

[7] Gerard Salton,et al. A vector space model for automatic indexing , 1975, CACM.