使用数据挖掘技术检测阿拉伯语YouTube垃圾邮件

Yahya M. Tashtoush, Areen Magableh, Omar Darwish, Lujain Smadi, Omar Alomari, Anood ALghazoo
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引用次数: 3

摘要

自从YouTube成为收入来源之一以来,用户数量大幅增加,旨在传播病毒或宣传其视频和频道的垃圾邮件发送者的数量也大幅增加。这些行为导致许多YouTube用户关闭了他们的频道或禁用评论,因为YouTube没有足够的工具来防止它。过滤阿拉伯垃圾评论是一个很大的挑战,因为各种方言都有大量的同义词。在这项工作中,我们使用不同的算法,如决策树(DT)、支持向量机(SVM)、朴素贝叶斯(NB)、随机森林和k-近邻(k-NN),对这些评论进行了分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detecting Arabic YouTube Spam Using Data Mining Techniques
Since YouTube became one of the sources of income, the number of users has increased significantly and the number of spammers who aim to spread viruses or to promote their videos and channels. These behaviors have led many YouTubers to close their channels or to disable the comments because YouTube does not have enough tools to prevent it. Filtering Arabic spam comments is a big challenge at all according to various dialects which hold a huge number of synonyms. In this work, we have classified these comments using different algorithms such as Decision Tree(DT), Support Vector Machine (SVM), Naive Bayes(NB), Random Forest, and k-Nearest Neighbor (k-NN).
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