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

In this paper, we utilize a simple support vector machine to identify commercial electronic mail. The use of a personalized dictionary for model training provided a classification accuracy of 96.69%, while a much larger system dictionary achieved 95.26%. The classification system was subsequently implemented as an add-in for Microsoft Outlook XP, providing sorting and grouping capabilities using Outlook’s interface to the typical desktop e-mail user.

• Type: Conference
• Year: 2003
• Where: SAINT
• Authors: Matthew Woitaszek, Muhammad Shaaban, Roy Czernikowski
• Keywords: Commercial Electronic Mail, Internet Technology, Microsoft Outlook XP, SAINT 2003, Simple Support Vector