Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
552662 | Decision Support Systems | 2007 | 15 Pages |
Abstract
In this paper we show an instance-based reasoning e-mail filtering model that outperforms classical machine learning techniques and other successful lazy learners approaches in the domain of anti-spam filtering. The architecture of the learning-based anti-spam filter is based on a tuneable enhanced instance retrieval network able to accurately generalize e-mail representations. The reuse of similar messages is carried out by a simple unanimous voting mechanism to determine whether the target case is spam or not. Previous to the final response of the system, the revision stage is only performed when the assigned class is spam whereby the system employs general knowledge in the form of meta-rules.
Related Topics
Physical Sciences and Engineering
Computer Science
Information Systems
Authors
F. Fdez-Riverola, E.L. Iglesias, F. Díaz, J.R. Méndez, J.M. Corchado,