论文标题
通过检测不可靠的评论评论来隔离欺骗Yelp的用户
Quarantine Deceiving Yelp's Users by Detecting Unreliable Rating Reviews
论文作者
论文摘要
在线评论在决策中不仅是消费者，而且对公司而言，已成为一种有价值且重要的资源。在没有信任的系统的情况下，将假定非常受欢迎且值得信赖的互联网用户被视为受信任圈子的成员。在本文中，我们描述了我们对欺骗Yelp的用户的重点，这些用户既采用了桥接评论网络（BRN），既采用审查Spike检测（RSD）算法和垃圾邮件检测技术，又在提取的关键功能上。我们发现，Yelp的80％以上的帐户不可靠，超过80％的高评价企业受到垃圾邮件的影响。
Online reviews have become a valuable and significant resource, for not only consumers but companies, in decision making. In the absence of a trusted system, highly popular and trustworthy internet users will be assumed as members of the trusted circle. In this paper, we describe our focus on quarantining deceiving Yelp's users that employ both review spike detection (RSD) algorithm and spam detection technique in bridging review networks (BRN), on extracted key features. We found that more than 80% of Yelp's accounts are unreliable, and more than 80% of highly-rated businesses are subject to spamming.
