基于评论者关系的垃圾评论者识别研究

Research on Review Spammer Detection via Reviewer Relationship

垃圾评论者在很大程度上误导潜在消费者和观点挖掘系统。目前检测垃圾评论者的方法主要是基于评论、评论者和商店之间的关系,忽略了评论者之间的关系。针对上述问题,提出了基于评论者多边图的产品垃圾评论者检测方法。首先,以每个评论者为节点,评论者之间的关系为边,构建评论者之间的关系图模型;其次,根据多边图模型,提出了一种基于PageRank的评论者互评估可信度模型来检测垃圾评论者;最后,采用卓越亚马逊和Resellerrating.com平台上的数据进行验证。结果表明:该模型能够更有效地识别出垃圾评论者,在一定程度上解决了难识别仅发表一条评论的评论者的可信度问题。

The review spammer greatly misleads the consumers and opinion mining system. Presently, the research of review spammer detection mainly is based on relationships among reviewers, reviews and stores, which doesn＇t take the relationships among reviewers into consideration. This paper proposes a multi- edge graph model to identify review spammer. Firstly, in the multi-edge graph model, the nodes represent reviewers and the edges represent the relationships among reviewers. Secondly, according to multi-edge graph model, reviewers＇ inter-assess trustiness model is based on PageRank algorithm to identify review spammer. And lastly, the datasets are crawled from JOYO Amazon website and Resellerrating. com. Experimental re- sults show that the model can achieve better performance on the accuracy of review spammer detection and the identification of review spammer who had only one review can be solved in some extent.