Elpub : Digital Library : Works

Paper 120_elpub2007:
The Fight against Spam - A Machine Learning Approach

id 120_elpub2007
authors Jezek, Karel; Hynek, Jiri
year 2007
title The Fight against Spam - A Machine Learning Approach
source 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
summary 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.
keywords unsolicited mail; spam filter; machine learning; latent semantic indexing; classification
series ELPUB:2007
type normal paper
email jhynek@kiv.zcu.cz
more http://info.tuwien.ac.at/elpub2007/presentations/120.ppt
content file.pdf (709,596 bytes)
discussion No discussions. Post discussion ...
ratings Ratings: 1
urn:nbn urn:nbn:se:elpub-120_elpub2007
last changed 2007/06/10 21:16
HOMELOGIN (you are user _anon_853345 from group guest) Powered by SciX Open Publishing Services 1.002