Spam Filtering Using Character-Level Markov Models: Experiments for the TREC 2005 Spam Track.
Andrej Bratko, Bogdan Filipič · 2005
This paper summarizes our participation in the TREC 2005 spam track, in which we consider the use of adaptive statistical data compression models for the spam filtering task. The nature of these models allows them to be employed as Bayesian text classifiers based on character sequences. We experimented with two different compression algorithms under varying model parameters. All four filters that we submitted exhibited strong performance in the o#cial evaluation, indicating that data compression models are well suited to the spam filtering problem.