PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

GNUsmail: Open Framework for On-line Email Classification
José M. Carmona-Cejudo, Manuel Baena-García, José del Campo-Ávila, Rafael Morales and Albert Bifet
In: ECAI 2010, August 16-20, 2010, Lisbon, Portugal.

Abstract

Real-time classification of massive email data is a challenging task that presents its own particular difficulties. Since email data presents an important temporal component, several problems arise: emails arrive continuously, and the criteria used to classify those emails can change, so the learning algorithms have to be able to deal with concept drift. Our problem is more general than spam detection, which has received much more attention in the literature. In this paper we present GNUsmail, an open-source extensible framework for email classification, which structure supports incremental and on-line learning. This framework enables the incorporation of algorithms developed by other researchers, such as those included in WEKA and MOA. We evaluate this framework, characterized by two overlapping phases (pre-processing and learning), using the ENRON dataset, and we compare the results achieved by WEKA and MOA algorithms.

EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:7199
Deposited By:Albert Bifet
Deposited On:09 March 2011