Non-Parametric Spam Filtering based on kNN and LSA
نویسندگان
چکیده
The paper proposes a non-parametric approach to filtering of unsolicited commercial e-mail messages, also known as spam. The email messages text is represented as an LSA vector, which is then fed into a kNN classifier. The method shows a high accuracy on a collection of recent personal email messages. Tests on the standard LINGSPAM collection achieve an accuracy of over 99.65%, which is an improvement on the best-published results to date.
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تاریخ انتشار 2005