Abstract
Without a doubt, online restaurant reviews are currently the most helpful resource for potential customers looking to make the best decision wherever in the globe. However, the issue at hand is rather significant: how to differentiate between impartial and truthful testimonies and fraudulent ones, as relying on evaluations and past experiences of a restaurant can be highly misleading when assessing their proficiency. Our objective is to address this issue by creating an application which uses machine learning model. The objective will be accomplished by consolidating the assessments of these esteemed sites, namely Google Reviews, TripAdvisor, Happy Cow, Open Table, and Yelp, into a single location. This is suitable for generating inputs from both the review text and the rating for each input. After the operation is over, a comprehensive report is generated that covers several aspects of restaurant issues, such as food quality, service standards, restaurant's ambience and location quality. This empowers users to make a wise decision in choosing the restaurant which they must spend time with their family or loved ones. Ultimately, the application aims to enhance the dining experience of users by providing user friendly platform for restaurant selection.