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, Naïve Bayes and LSI classifiers for classifying email messages into spam and non-spam (ham) categories.
Jezek, Karel, and Jiri Hynek. "The Fight against Spam - A Machine Learning Approach." In Openness in Digital Publishing: Awareness, Discovery and Access - Proceedings of the 11th International Conference on Electronic Publishing, 381-392. ELPUB. Vienna, Austria, 2007.
Keywords: Unsolicited Mail, Spam Filter, Machine Learning, Latent Semantic Indexing and Classification