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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 targetdoi:10.1016/j.dss.2006.11.012 fatcat:yibedumnmjeh3p2422rfg6vf3y