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SPAM detection: Naïve bayesian classification and RPN expression-based LGP approaches compared
Authors
A Guven
A Khorsi
+18 more
AH Gandomi
AW Burks
C Sangeetha
Carlton Downey
CL Hamblin
E Stamatatos
GV Cormack
I Kononenko
J Pearl
L Hirsch
Lorrie Faith Cranor
M Basavaraju
M Brameier
M Matsumoto
M Zhang
PE Bennett
S Mukkamala
VA Yatsko
Publication date
26 July 2016
Publisher
'Springer Science and Business Media LLC'
Doi
Cite
Abstract
An investigation is performed of a machine learning algorithm and the Bayesian classifier in the spam-filtering context. The paper shows the advantage of the use of Reverse Polish Notation (RPN) expressions with feature extraction compared to the traditional Naïve Bayesian classifier used for spam detection assuming the same features. The performance of the two is investigated using a public corpus and a recent private spam collection, concluding that the system based on RPN LGP (Linear Genetic Programming) gave better results compared to two popularly used open source Bayesian spam filters. © Springer International Publishing Switzerland 2016
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oai:publikace.k.utb.cz:10563/1...
Last time updated on 09/08/2016
Crossref
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info:doi/10.1007%2F978-3-319-3...
Last time updated on 01/04/2019