垃圾邮件
支持向量机
计算机科学
k-最近邻算法
机器学习
人工智能
特征选择
特征(语言学)
数据挖掘
最近的邻居
情报检索
模式识别(心理学)
万维网
互联网
语言学
哲学
作者
Nor Azwan Mohamed Kamari,Ismail Musirin,Zulkiffli Abdul Hamid,Ahmad Asrul Ibrahim
标识
DOI:10.11591/ijeecs.v12.i2.pp612-619
摘要
<p>Social networking such as YouTube, Facebook and others are very popular nowadays. The best thing about YouTube is user can subscribe also giving opinion on the comment section. However, this attract the spammer by spamming the comments on that videos. Thus, this study develop a YouTube detection framework by using Support Vector Machine (SVM) and K-Nearest Neighbor (k-NN). There are five (5) phases involved in this research such as Data Collection, Pre-processing, Feature Selection, Classification and Detection. The experiments is done by using Weka and RapidMiner. The accuracy result of SVM and KNN by using both machine learning tools show good accuracy result. Others solution to avoid spam attack is trying not to click the link on comments to avoid any problems.</p>
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