Filtron: A Learning-Based Anti-Spam Filter
by Eirinaios Michelakis, Ion Androutsopoulos, Georgios Paliouras, George Sakkis, Panagiotis Stamatopoulos
Conference on Email and Anti-Spam,
2004-07-30
Language:
English
Note: Published at CEAS 2004.
Abstract
Abstract. We present Filtron, a prototype anti-spam lter that integrates the main empirical con- clusions of our comprehensive analysis on using machine learning to construct e ective personalized anti-spam lters. Filtron is based on the experimental results over several design parameters on four publicly available benchmark corpora. After describing Filtron's architecture, we assess its behavior in real use over a period of seven months. The results are deemed satisfactory, though they can be improved with more elaborate preprocessing and regular re-training.
