Group Members

Elliot Boschwitz, Eric Jiang, Shayan Patel, Ella Polo


We all love food, and even more so, we love good food. Aurora was designed for anyone who wants to discover the best foods at any restaurant of their choice. We strive to enable our users to make informed decisions about their food purchases and hope that by using Aurora, they can fulfill all their food cravings with maximum satisfaction. At the most basic level, Aurora analyzes Yelp reviews to return ratings for any dish at any restaurant, as specified by the user. As Yelp currently only supports reviews for an entire restaurant, it is difficult for a user to determine the quality of a dish of interest in an efficient and practical way. With Aurora, we wanted to fill this gap and add an extra dimension to Yelp's review system. Using Aurora, a user can search for a specific food item within the Yelp reviews for a restaurant to obtain instant and relevant results. Aurora's magic is in its use of sentiment analysis to determine a food's favorability. It uses natural language processing on the reviews for a particular restaurant to determine if phrases which contain the name of the food embody a positive or negative attitude.