Abstract
The paper proposes the use of the multilayer perceptron model to the problem of detecting ham and spam e-mail patterns. It also proposes an intensive use of data pre-processing and feature selection methods to simplify the task of the multilayer perceptron in classifying ham and spam e-mails. The multilayer perceptron is trained and assessed on patterns extracted from the SpamAssassin Public Corpus. It is required to classify novel types of ham and spam patterns. The results are presented and evaluated in the paper.
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Carpinteiro, O.A.S., Lima, I., Assis, J.M.C., de Souza, A.C.Z., Moreira, E.M., Pinheiro, C.A.M. (2006). A Neural Model in Anti-spam Systems. In: Kollias, S., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840930_88
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DOI: https://doi.org/10.1007/11840930_88
Publisher Name: Springer, Berlin, Heidelberg
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