• DR.R.N.DEVENDRA KUMAR
• Vijaya Vikashini.G
• Shreejith S
• Nithish kumar V

The majority of individuals look for product reviews before spending their money on it. As a result, users come across many reviews on the website, but whether these reviews are legitimate or not is unknown to the customer. Some favorable reviews are added by product company people themselves to some review websites in order to create phony positive product reviews. They give positive feedback on a variety of products made by their own company. The user will be unable to determine whether the review is real or not. By recognizing the Detect fake review as well as review posting habits, this system will detect phone reviews created by submitting fake remarks about a product. The user will enter his user id and password to access the system and see numerous products before leaving a review. To determine if a review is false or genuine, the system will look up the user's Detect fake review . If the system notices a pattern of fake reviews being detect review using machine learning, it will alert the administrator to delete the review from the system. This approach assists the consumer in locating accurate product reviews. The suggested system will employ supervised machine learning. Based on simulation results, the Support Vector Machine algorithm was chosen (SVM). Future study should focus on implementing the system and testing its performance against various benchmark data sets. Another study topic could be to compare the performance of several classification algorithms in order to discover the best one for our suggested opinion fake review categorization approach

Fake Review , Classifications , Prediction ,Analysis ,Online products review

"FAKE REVIEW MONITORING USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.e759-e764, May-2022, Available :http://www.jetir.org/papers/JETIR2205590.pdf

"FAKE REVIEW MONITORING USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppe759-e764, May-2022, Available at : http://www.jetir.org/papers/JETIR2205590.pdf