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2008
Springer

Personalized Spam Filtering for Gray Mail

9 years 8 months ago
Personalized Spam Filtering for Gray Mail
Gray mail, messages that could reasonably be considered either spam or good by different email users, is a commonly observed issue in production spam filtering systems. In this paper we study this class of mail using a large real-world email corpus and signaturebased campaign detection techniques. Our analysis shows that even an optimal filter will inevitably perform unsatisfactorily on gray mail, unless user preferences are taken into account. To overcome this difficulty we design a light-weight user model that is highly scalable and can be easily combined with a traditional global spam filter. Our approach is able to incorporate both partial and complete user feedback on message labels and catches up to 40% more spam from gray mail in the low false-positive region.
Ming-Wei Chang, Scott Yih, Robert McCann
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where CEAS
Authors Ming-Wei Chang, Scott Yih, Robert McCann
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