• Shreya Rukari
• Minal Thaokar
• Rutuja Nanaware
• Dhanashree Tekawade
• Prof.Dhanashri Patil

As the trend towards online shopping increases day by day, More people are interested in buying their goods and more people The online stores need it. Does not allow this sort of shopping It takes a lot of a client's time. Customers go to the shop online, Check for the item you need and put the order. But the, the, the, Stuff that make it impossible for individuals to purchase goods The low product quality is from an online retailer. User Place the order by looking only at the rating and reading Reviews were linked to the specific product. Comments of this nature Other individuals are the source of happiness for the new Material Purchaser. Here, it could be possible for the single negative to be negative Review shifts the client's angle of not buying the Product. Product. It is a specific quality of the method proposed that It works with the three websites for e-commerce and not only Analyze the English reviews, but also the reviews published in Urdu and Urdu Roman. Previous studies on counterfeit reviews does No function to evaluate feedback written in languages is supported. Like Urdu and Roman Urdu, and they are unable to manage the feedback of Different Websites for e-commerce. The planned job accomplished 87 percent accuracy in the identification of fake reviews published in Using intelligent learning methods, English Better than the precision of the preceding systems.

"Detecting Spammer Groups From Product Reviews.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.b589-b596, June-2021, Available :http://www.jetir.org/papers/JETIR2106223.pdf

"Detecting Spammer Groups From Product Reviews.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppb589-b596, June-2021, Available at : http://www.jetir.org/papers/JETIR2106223.pdf