首页> 外文会议>International Symposium on Computer and Information Sciences(ISCIS 2004); 20041027-29; Kemer-Antalya(TR) >An Approach for Spam E-mail Detection with Support Vector Machine and n-Gram Indexing
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An Approach for Spam E-mail Detection with Support Vector Machine and n-Gram Indexing

机译:支持向量机和n-Gram索引的垃圾邮件检测方法

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摘要

Many solutions have been deployed to prevent harmful effects from spam mail. Typical methods are either pattern matching using the keyword or method using the probability such as naive Bayesian method. In this paper, we proposed a classification method of spam mail from normal mail using support vector machine, which has excellent performance in binary pattern classification problems. Especially, the proposed method efficiently practices a learning procedure with a word dictionary by the n-gram. In the conclusion, we showed our proposed method being superior to others in the aspect of comparing performance.
机译:已经部署了许多解决方案来防止垃圾邮件的有害影响。典型的方法是使用关键字的模式匹配或使用概率的方法(例如朴素贝叶斯方法)。本文提出了一种利用支持向量机对普通邮件中垃圾邮件进行分类的方法,该方法在二进制模式分类问题中具有很好的性能。特别地,所提出的方法通过n-gram用单词字典有效地实践学习过程。总之,我们在比较性能方面表明了我们提出的方法优于其他方法。

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