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SPAM Detection: Naïve Bayesian Classification and RPN Expression-Based LGP Approaches Compared

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Software Engineering Perspectives and Application in Intelligent Systems ( ICTIS 2017, CSOC 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 465))

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.

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Acknowledgement

Acknowledgements go to my Ph.D. Supervisors Dr Vitezlav Nezval. Thanks also to Tom Fawcett who answered my email query about the subject of Bayesian classifiers and RPN. This work was supported by Grant Agency of the Czech Republic—GACR P103/15/06700S, further by financial support of research project NPU I No. MSMT-7778/2014 by the Ministry of Education of the Czech Republic and also by the European Regional Development Fund under the Project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089.

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Authors and Affiliations

  1. CIS Department, Faculty of ICT, University of Malta, Msida, Malta

    Clyde Meli

  2. Department of Informatics and Artificial Intelligence, Faculty of Applied Informatics, Tomas Bata University in Zlin, Nam. T.G. Masaryka 5555, Zlín, Czech Republic

    Zuzana Kominkova Oplatkova

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  1. Clyde Meli
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Correspondence to Clyde Meli .

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Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

  2. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Roman Senkerik

  3. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Zuzana Kominkova Oplatkova

  4. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Petr Silhavy

  5. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Zdenka Prokopova

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Meli, C., Oplatkova, Z.K. (2016). SPAM Detection: Naïve Bayesian Classification and RPN Expression-Based LGP Approaches Compared. In: Silhavy, R., Senkerik, R., Oplatkova, Z.K., Silhavy, P., Prokopova, Z. (eds) Software Engineering Perspectives and Application in Intelligent Systems. ICTIS CSOC 2017 2016. Advances in Intelligent Systems and Computing, vol 465. Springer, Cham. https://doi.org/10.1007/978-3-319-33622-0_36

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  • DOI: https://doi.org/10.1007/978-3-319-33622-0_36

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