Paper Key : IRJ************281
Author: Abhishek Upadhyaya H K,Dr. Girish
Date Published: 05 Aug 2022
Abstract
Detection and Removal of fake product from dataset using Natural Language Processing(NLP) is important techniques in an aspect. In this project we are using Machine Learning (ML) Algorithm to detect the fake product reviews in a dataset, which predict the accuracy of how genuine. When the product review is the major aspect to buy products in E-commerce, the rate to fake reviews in increasing day by day on website and applications. So this fake product reviews problem must be addressed by the large E-commerce company, before purchasing the product from the trusted company. By using this technique we can rectify the issue of fake product reviews and spammers are eliminated, which prevents the users to losing the trust on E-commerce. By using this project the Authority of the company can detect the fake reviews and take necessary actions towards them. This model is developed using the Nave Bayer Algorithms. By applying this algorithm can know the spam reviews and website or application. To count such spammers a dataset is required, we are using amazon academic dataset to train the model and can be scaled to get high accuracy and flexibility rate.