A Survey on Different Techniques for Product Fake Review Detection and Product Rating

Adnan Telwala, Ayush Pratap, Ketan Gaikwad, Tushar Chaudhari, S. Bhingarkar
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Abstract

Numerous online business sites empower the customers to create a product reviews along with feedback in the shape of ratings. This gives the organization work force a sign about their items’ remaining on the lookout, while likewise empowering individual customer to frame an assessment and help buy an item. As of late, Sentiment Analysis (SA) has gotten quite possibly interesting due to the potential business advantages of text analysis. One of the most important problems in confronting SA is the manner by which to remove feelings in the assessment, as well as how to identify counterfeit good reviews and negative surveys derived from assessment surveys. Besides, the assessment surveys acquired from clients can divided into two categories: positive and negative, which can be utilized by a shopper to choose an item. In this survey, we have thoroughly discussed about fake review detection of products as well as product rating by different SA techniques. Further, we have discussed the research direction in fake review detection and product rating.
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产品虚假评论检测与产品评级技术综述
许多在线商业站点允许客户创建产品评论以及评级形式的反馈。这给了组织工作人员一个关于他们的物品仍在观察的信号,同时也使个人客户能够制定评估并帮助购买物品。最近,由于文本分析的潜在业务优势,情感分析(SA)可能变得非常有趣。面对SA最重要的问题之一是如何消除评估中的感受,以及如何识别虚假的好评和来自评估调查的负面调查。此外,从客户那里获得的评估调查可以分为积极和消极两类,购物者可以利用这些评估调查来选择商品。在本次调查中,我们深入讨论了不同SA技术对产品的虚假评论检测以及产品评级。进一步讨论了虚假评论检测和产品评级的研究方向。
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