Fake Product Review Monitoring And Removal For Genuine Online Product Reviews Using Opinion Mining

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FAKE PRODUCT REVIEW MONITORING AND REMOVAL FOR GENUINE ONLINE PRODUCT REVIEWS USING OPINION MINING

 

As most people require reviews of a product before spending their money on it,. So people come across various reviews on the website, but whether these reviews are genuine or fake is not identified by the user. On some review websites, some good reviews are added by the product company itself in order to produce falsely positive product reviews.

They give good reviews for many different products manufactured by their own firm. The user will not be able to find out whether the review is genuine or fake. To find out fake reviews on the website, this “Fake Product Review Monitoring and Removal for Genuine Online Product Reviews Using Opinion Mining” system is introduced.

This system will find out fake reviews made by posting fake comments about a product by identifying the IP address along with review posting patterns. The user will login to the system using his user ID and password and will view various products and give reviews about them. To find out if the review is fake or genuine, the system will find out the IP address of the user. If the system observes a fake review sent by the same IP address many times, it will inform the admin to remove that review from the system. This system uses a data mining methodology. This system helps the user find the correct review of the product.

system works as follows:

  • Admin will add products to the system.
  • Admin will delete the review that is fake.
  • User once access the system, user can view product and can post review about the product.
  • The system will track the IP address of the user.
  • If the system observes a fake review coming from the same IP address many times, this IP address will be tracked by the system, which will inform the admin to remove this review from the system.
FAKE PRODUCT REVIEW MONITORING AND REMOVAL FOR GENUINE ONLINE PRODUCT REVIEWS USING OPINION MINING,

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