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A combined approach based on fuzzy AHP and fuzzy inference system to rank reviewers in online communities

机译:基于模糊层次分析法和模糊推理系统的组合方法对网络社区审稿人的评价。

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Online product review communities allow users to share their ideas and opinions about various products and services. Although online reviews as user-generated content can be considered as an invaluable source of information for both consumers and firms, these reviews tend to be of very different quality. To tackle the problem of low quality reviews, we address reviewer credibility and propose an innovative framework. The framework comprises five critical phases for ranking reviewers in terms of credibility using a fuzzy analytic hierarchy process (AHP) and fuzzy inference system. To determine the weights of the features, a fuzzy AHP method was applied. In addition, according to the proposed framework, to compute a realistic credibility score based on trustworthiness and expertise, a cognitive approach was followed and a fuzzy inference system was designed. To illustrate an application of the proposed method, we conducted an experimental study using real data gathered from Epinions.
机译:在线产品评论社区使用户可以分享他们对各种产品和服务的想法和意见。尽管可以将在线评论作为用户生成的内容视为消费者和公司的宝贵信息来源,但是这些评论的质量往往相差很大。为了解决低质量评论的问题,我们提高了评论者的信誉并提出了创新的框架。该框架包含五个关键阶段,这些阶段使用模糊分析层次过程(AHP)和模糊推理系统对可信度进行排名。为了确定特征的权重,应用了模糊层次分析法。此外,根据提出的框架,为了计算基于可信度和专业知识的真实可信度分数,遵循一种认知方法并设计了一个模糊推理系统。为了说明所提出方法的应用,我们使用从Epinions收集的真实数据进行了实验研究。

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