Electronic Mail Classification System Based on Machine Learning approach

Subhrajyoti Ranjan Sah, S. J
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Abstract

In current times, users depend comprehensively on electronic communication ways such as electronic mails as it is considered a foremost source of communication. A vast amount of time is invested in electronic mail for communication in the information technology field, due to which electronic mail management has become a prominent feature among the mailing applications. Electronic mail classification comes under this type of management which helps the expert to eliminate the time invested during un-necessary mail reading. Also, the content of electronic mail is further used in the analysis for future prediction and reading behaviors in which a good mail classification system would reduce a lot of time and resources. Conventionally many other systems or methods are present and widely popular in the market but there is no such system that achieves high accuracy. This paper proposes a novel electronic mail classification system that is based ensemble technique which combines the result of many classifiers to achieve good accuracy. Keyword : Electronic communication, Electronic mail, Content Analysis, Classifiers, Feature extraction.
基于机器学习方法的电子邮件分类系统
在当今时代,用户全面依赖电子邮件等电子通信方式,因为它被认为是最重要的通信来源。在信息技术领域,大量的时间被投入到电子邮件中进行通信,因此电子邮件管理已经成为邮件应用中的一个突出特征。电子邮件分类属于这种类型的管理,它可以帮助专家消除在不必要的邮件阅读中投入的时间。此外,电子邮件的内容还可以进一步用于对未来预测和阅读行为的分析,一个好的邮件分类系统可以减少大量的时间和资源。传统上有许多其他系统或方法存在并在市场上广泛流行,但没有这样的系统实现高精度。本文提出了一种基于集成技术的电子邮件分类系统,该系统综合了多个分类器的分类结果,达到了较好的分类精度。关键词:电子通信,电子邮件,内容分析,分类器,特征提取。
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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