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Filtering Turkish Spam Using LSTM From Deep Learning Techniques

机译:使用LSTM从深度学习技术过滤土耳其垃圾邮件

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E-mails are used effectively by people or communities who want to do propaganda, advertisement, and phishing because of their ease of use and low cost. People or communities who want to achieve their goals send unnecessary and spam to the e-mail accounts they never knew. These mails cause serious financial and moral damages to internet users and also engage in internet traffic. Unsolicited e-mails (spam) are a method sent to the recipient without their consent and generally for malicious or promotional purposes. In this study, spam was detected with Keras deep learning library on the Turkish dataset. Turkish email dataset contains 800 e-mails, half of which are spam e-mails. With the deep learning algorithm long short term memory (LSTM), a 100% accuracy rate has been achieved in the Turkish e-mail dataset.
机译:由于他们的易用性和低成本,由想要进行宣传,广告和网络钓鱼的人或社区有效地使用电子邮件。 想要实现目标的人或社区将不必要地发送到他们从未知道的电子邮件账户中的垃圾邮件。 这些邮件对互联网用户造成严重的财务和道德损害,并从事互联网交通。 未经请求的电子邮件(垃圾邮件)是在未经他们同意的情况下发送给收件人的方法,并且通常用于恶意或促销目的。 在这项研究中,用土耳其数据集上的Keras Deep学习图书馆检测到垃圾邮件。 土耳其电子邮件数据集包含800个电子邮件,其中一半是垃圾邮件电子邮件。 利用深度学习算法长短短期内存(LSTM),土耳其电子邮件数据集已经实现了100%的精度率。

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