基于非特征信息的电子邮件表示及其应用

Pei-yu Liu, Jing Zhao, Zhen-fang Zhu
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引用次数: 3

摘要

针对基于电子邮件内容分类的不确定性和电子邮件表示的不完备性,提出了一种基于非特征信息的电子邮件表示方法。新方法涉及整个电子邮件,包含从电子邮件内容中提取的特征项和从电子邮件标题中提取的非特征项。在实验中,我们采用朴素贝叶斯分类器对邮件进行分类,分类结果表明,新方法克服了原有基于内容过滤的缺点,提高了垃圾邮件过滤的查全率和查准率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Email Representation using Noncharacteristic Information and its Application
Focusing on the uncertainty of classifying emails based-on email content and the incompleteness of email representation, the paper proposes a new representation using noncharacteristic information. The new approach refers to the whole email, contains feature items extracted from email content, and noncharacteristic items extracted from email header. In the expriment, we adopt Naive Bayes classifier to classify emails, classification results indicate that the new approach overcomes the shortcomings of original content-based filtering and improves the recall and the precision of spam filtering.
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