使用压缩和PSO的垃圾邮件检测

2012 Fourth International Conference on Computational Aspects of Social Networks (CASoN) Pub Date : 2012-11-01 DOI:10.1109/CASoN.2012.6412413

Michal Prilepok, T. Ježowicz, J. Platoš, V. Snás̃el

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引用次数: 7

摘要

垃圾邮件的问题仍在增长。因此，开发能够解决这一问题的算法也是一个非常活跃的领域。本文提出了两种不同的垃圾邮件检测算法。第一种算法是基于贝叶斯滤波的，但在贝叶斯滤波不能确定的情况下，使用数据压缩算法进行改进。第二种算法是基于粒子群算法的文档分类算法。所提出的算法的结果是有希望的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Spam detection using compression and PSO

The problem of spam emails is still growing. Therefore, developing of algorithms which are able to solve this problem is also very active area. This paper presents two different algorithms for spam detection. The first algorithm is based on Bayesian filter, but it is improved using data compression algorithms in case that the Bayesian filter cannot decide. The second algorithm is based on document classification algorithm using Particle Swarm Optimization. Results of presented algorithms are promising.

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来源期刊

2012 Fourth International Conference on Computational Aspects of Social Networks (CASoN)

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