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On the study of anomaly-based spam filtering using spam as representation of normality

机译:基于垃圾邮件作为正常现象的基于异常的垃圾邮件过滤的研究

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In previous work, we presented the first spam filtering method based on anomaly detection that reduces the necessity of labelling spam messages and only employs the representation of legitimate e-mails. This method achieved high accuracy rates detecting spam while maintaining a low false positive rate and reducing the effort produced by labelling spam. In this paper, we study the performance of our previous method when using spam messages to represent normality.
机译:在以前的工作中,我们介绍了第一种基于异常检测的垃圾邮件过滤方法,该方法减少了标记垃圾邮件消息的必要性,并且仅使用合法电子邮件的表示形式。该方法实现了检测垃圾邮件的高准确率,同时保持较低的误报率,并减少了标记垃圾邮件的工作量。在本文中,我们研究了使用垃圾邮件表示正常状态时先前方法的性能。

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