文章基本信息

标题：Detection of Spammer Group Using Semi- Supervised Learning
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作者：Bindhya Babu ; Sam G Benjamin
期刊名称：International Journal of Computer Science and Network
印刷版ISSN：2277-5420
出版年度：2019
卷号：8
期号：3
页码：213-216
出版社：IJCSN publisher
摘要：These days, online items survey assumes a pivotal job for purchasing online products. A high extent of positive surveys will bring considerable deals development while negative surveys will cause deals misfortune. Driven by huge money related benefits, various spammers attempt to advance their items or downgrade their rivals' items by posting fake and one-sided online surveys. Existing works extract spammer candidates and remove spammers from the review data using unsupervised spamicity positioning techniques. All things considered, as indicated by past research, marking few spammer group is simpler than one expect, number of techniques endeavor to utilize significant named information. In this paper, we propose a semi-supervised learning technique to distinguish spammers. Naive Bayesian model and EM calculations are used to organize a classifier for the detection of spammer groups.
关键词：Naive Bayesian Model; EM Calculations; Spammer Groups; Semi;Supervised Learning;