Identifying Junk Electronic Mail in Microsoft Outlook with a Support Vector Machine

Authors:
Matthew Woitaszek;Muhammad Shaaban;Roy Czernikowski
Affiliations:
-;-;-
Venue:
SAINT '03 Proceedings of the 2003 Symposium on Applications and the Internet
Year:
2003

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Abstract

In this paper, we utilize a simple support vectormachine to identify commercial electronic mail. The useof a personalized dictionary for model training provideda classification accuracy of 96.69%, while a much largersystem dictionary achieved 95.26%. The classificationsystem was subsequently implemented as an add-in forMicrosoft Outlook XP, providing sorting and groupingcapabilities using Outlook's interface to the typicaldesktop e-mail user.