A Real and Accurate Fake Product Detection System and Generate Original Reviews Using Data Mining Mechanism

Q3 Chemistry
Ch. V. Bhargavi, G. Mani, G. Jyothi, K. V. Rao, E. Lydia
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引用次数: 0

Abstract

Most of the people requires genuine information about the online product. Before spending their economy on particular product can analyze the various reviews in the website. In this scenario, they did not identify whether the product may be fake or genuine. In general, some reports in the websites are good, company technical people itself add these for making the product famous. These people belong to media and social organization teams, they give reviews with a good rating by their own firm. Online purchasers did not identify the fake product because of this falsification in the reviews of the website. In this research,the SVM classification mechanism has been used for detect the fake reviews by using IP address. This implementation helpful for users find out the correct review of online product. In this accuracy is improved by 98.79%, F1-Score increases by 10%.
基于数据挖掘机制的真实、准确的假货检测系统及原创评论生成
大多数人需要关于在线产品的真实信息。在将经济花费在特定产品上之前,可以分析网站上的各种评论。在这种情况下,他们没有确定产品是假的还是真的。总的来说,网站上的一些报道是好的,公司技术人员自己添加这些是为了让产品出名。这些人属于媒体和社会组织团队,他们在自己的公司给予好评。由于网站评论中的这种伪造行为,网上购买者没有识别出假冒产品。在本研究中,SVM分类机制被用于通过使用IP地址来检测虚假评论。此实现有助于用户找到正确的在线产品评论。在这个准确性提高了98.79%,F1分数提高了10%。
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来源期刊
Journal of Computational and Theoretical Nanoscience
Journal of Computational and Theoretical Nanoscience 工程技术-材料科学:综合
自引率
0.00%
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0
审稿时长
3.9 months
期刊介绍: Information not localized
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