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Research Paper | Computer Science & Engineering | India | Volume 7 Issue 10, October 2018

Fake Product Review Detection and Removal

Aditya Darak ^[2] | Akhil Chaudhary ^[3] | Prajwal Mogaveera ^[3]

Abstract: Online reviews are often the primary factor in a customers decision to purchase a product or service, and are a valuable source of information that can be used to determine public opinion on these products or services. Reliance on online reviews gives rise to the potential concern that wrongdoers may create false reviews to artificially promote or devalue products and services. This practice is known as Opinion (Review) Spam, where spammers manipulate and poison reviews (i. e. , making fake, untruthful, or deceptive reviews) for profit or gain. We propose to build a fraud risk management system based on data processing and intelligent risk-mitigation models. It captures fraudulent transactions based on user behaviors and network, analyses them in real-time using Data Mining, and accurately predicts the suspicious users and transactions. This system proposes behavioral approach using J48 CLASSIFIER to detect review spammers who try to manipulate the ratings on some target products.

Keywords: Fake Review detection, Review Removal, J48, classifier

Edition: Volume 7 Issue 10, October 2018,

Pages: 86 - 88

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