Combining multiple email filters based on multivariate statistical analysis

Authors:
Wenbin Li;Ning Zhong;Chunnian Liu
Affiliations:
The International WIC Institute, Beijing University of Technology, Beijing, P.R. China;The International WIC Institute, Beijing University of Technology, Beijing, P.R. China;The International WIC Institute, Beijing University of Technology, Beijing, P.R. China
Venue:
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Year:
2006

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Abstract

In this paper, we investigate how to combine multiple e-mail filters based on multivariate statistical analysis for providing a barrier to spam, which is stronger than a single filter alone. Three evaluation criteria are suggested for cost-sensitive filters, and their rationality is discussed. Furthermore, a principle that minimizes the error cost is described to avoid filtering an e-mail of “Legitimate” into “Spam”. Comparing with other major methods, the experimental results show that our method of combining multiple filters has preferable performance when appropriate running parameters are adopted.