Open AccessApplication and Research of Spam Classification Based on Cluster Intelligence Algorithm to Optimize SVM
Author(s) -
Zhennan Xia,
Jianzhi Deng
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1617/1/012050
Subject(s) - computer science , support vector machine , popularity , the internet , swarm intelligence , coding (social sciences) , data mining , statistical classification , artificial intelligence , machine learning , world wide web , particle swarm optimization , mathematics , psychology , social psychology , statistics
With the development of science and technology, the increasing popularity of the Internet, email has been widely used. Because of its convenience and low cost, e-mail has been used by more and more criminals to maliciously spread commercial advertisements, computer viruses and bad information. In order to resist spam, this paper proposes a spam classification method based on swarm intelligence algorithm optimized SVM. It classifies English spam and extracts features with special sensitive word coding. The model and method in this paper have certain reference value for spam classification research.