Combating fraud: dynamic and advanced Techniques for unveiling false reviews and deceiving text on e-commerce website
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E-commerce has widely grown among people in recent years and has been used for purchasing products and services on the Internet. E-commerce faces more challenges due to the growing amount of deceptive and fake products online. The purpose of this research is to combat this fraud using dynamic and advanced techniques for unveiling false reviews and deceiving product descriptions. This research employs the DistilBERT model for detecting fake reviews and the BERT base model for identifying misleading product descriptions. This research aims to bring down false information, stop defying products backed up by their false reviews and report them. In this study, we create a FRD Algorithm and DTD Algorithm that solve the problem of Combating fraud: dynamic and advanced Techniques for unveiling false reviews and deceiving text on e-commerce website. The model is achieving an accuracy of 95.6 %. It helps customers save more time and focus on purchasing the product rather than figuring out whether the reviews are true or false. Future research is focusing on a more accurate, more dynamic and efficient way to execute the AI models.
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