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A hybrid approach to detecting alerts in Arabic e-mail messages

机译:一种检测阿拉伯电子邮件中警报的混合方法

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摘要

Detecting alert e-mails received daily by millions of subscribers from online news providers is a relatively new area of research which falls within the e-mail filtering field of research. Alert e-mails may address government, political issues, breaking news, and criminal attacks. This article proposes a hybrid approach based on both the Graham statistical filter and rule-based filters to detect and filter Arabic alert e-mails. The approach is basically language-independent. To test the performance of the proposed approach, several experiments have been conducted using a set of 1500 Arabic messages related to criminal activities collected manually from some news websites such as Al-Jazeera Net and BBC Arabic news. The results showed that the proposed approach has achieved a competitive performance in terms of accuracy, precision, and F-measure, where about 87% of the messages tested have been correctly detected and filtered by the proposed filter.
机译:检测每天有数百万订户从在线新闻提供者处收到的警报电子邮件是一个相对较新的研究领域,属于电子邮件过滤研究领域。警报电子邮件可能会涉及政府,政治问题,突发新闻和犯罪袭击。本文提出了一种基于Graham统计过滤器和基于规则的过滤器的混合方法,以检测和过滤阿拉伯警报电子邮件。该方法基本上与语言无关。为了测试所提出方法的性能,已经使用一组1500条与犯罪活动相关的阿拉伯语消息进行了一些实验,这些消息是从Al-Jazeera Net和BBC阿拉伯新闻等一些新闻网站上手动收集的。结果表明,所提出的方法在准确性,精确度和F度量方面均取得了竞争优势,其中所提出的过滤器正确检测和过滤了大约87%的测试消息。

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