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Machine Learning Techniques in Spam Detection

Machine Learning Techniques in Spam Detection

Yasmin Bouarara
Copyright: © 2021 |Pages: 11
ISBN13: 9781799827917|ISBN10: 1799827917|ISBN13 Softcover: 9781799827924|EISBN13: 9781799827931
DOI: 10.4018/978-1-7998-2791-7.ch008
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MLA

Bouarara, Yasmin. "Machine Learning Techniques in Spam Detection." Advanced Deep Learning Applications in Big Data Analytics, edited by Hadj Ahmed Bouarara, IGI Global, 2021, pp. 145-155. https://doi.org/10.4018/978-1-7998-2791-7.ch008

APA

Bouarara, Y. (2021). Machine Learning Techniques in Spam Detection. In H. Bouarara (Ed.), Advanced Deep Learning Applications in Big Data Analytics (pp. 145-155). IGI Global. https://doi.org/10.4018/978-1-7998-2791-7.ch008

Chicago

Bouarara, Yasmin. "Machine Learning Techniques in Spam Detection." In Advanced Deep Learning Applications in Big Data Analytics, edited by Hadj Ahmed Bouarara, 145-155. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-2791-7.ch008

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Abstract

Spam, a contraction of rotten email (or junk email), is a global and massive phenomenon. And as long as email exists, this real problem will always exist. However, it is possible to significantly limit the effects of spam. To do this, you just have to use various anti-spam technologies wisely. In this chapter, the authors present the definitions of spam and its evolution, its objectives and impacts, as well as the different approaches and techniques used for detecting and filtering it.

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