This new website provides a fast and easy way of searching up the most-ordered and highest-rated foods at a restaurant. Pulling from Yelp’s reviews, the team has developed an algorithm that uses natural language processing to find the item most ordered at the restaurant. Then, based on those reviews, sentiment analysis is used to determine how positive the reviews are for that specific item. For example, if a review covers both the item as well as service, the algorithm would be able to extract just the rating for the food.
The team is a group of UC Berkeley students who have run into this issue in the past, where they would go to a restaurant and spend a long time searching through Yelp reviews: looking through photos, scrolling through tons of reviews, and looking at blurry pictures of the menu. Hopefully this new web app will help people save time so that they can enjoy the food and the company that they are with!