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

被引：0

作者：

Meli, Clyde ^{[1
]}

Oplatkova, Zuzana Kominkova ^{[2
]}

机构：

[1] Univ Malta, Fac ICT, CIS Dept, Msida, Malta

[2] Tomas Bata Univ Zlin, Fac Appl Informat, Dept Informat & Artificial Intelligence, Nam TG Masaryka 5555, Zlin, Czech Republic

来源：

SOFTWARE ENGINEERING PERSPECTIVES AND APPLICATION IN INTELLIGENT SYSTEMS, VOL 2 | 2016年 / 465卷

关键词：

Reverse polish notation (RPN); Naive bayesian classifier; Spam detection; Linear genetic programming (LGP); Genetic programming (GP);

D O I：

10.1007/978-3-319-33622-0_36

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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 Naive 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.

引用

页码：399 / 411

页数：13

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