The Fight against Spam - A Machine Learning Approach
||Jezek, Karel; Hynek, Jiri
||The Fight against Spam - A Machine Learning Approach
||ELPUB2007. Openness in Digital Publishing: Awareness, Discovery and Access - Proceedings of the 11th International Conference on Electronic Publishing held in Vienna, Austria 13-15 June 2007 / Edited by: Leslie Chan and Bob Martens. ISBN 978-3-85437-292-9, 2007, pp. 381-392
||The paper presents a brief survey of the fight between spammers and antispam software developers, and also describes new approaches to spam filtering. In the first two sections we present a survey of the currently existing spam types. Some well-mapped spammer tricks are also described, although the imagination of spam distributors is endless, and therefore only the most common tricks are covered. We present some up-to-date spam blocking techniques currently integrated into today's spam filters. In the Methodology and Results sections we describe our implementation of Itemsets-based, Na´ve Bayes and LSI classifiers for classifying email messages into spam and non-spam (ham) categories.
||unsolicited mail; spam filter; machine learning; latent semantic indexing; classification
||file.pdf (709,596 bytes)
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