Analysis of Zomato Services using Recommender System Models

The aim of this project is to analyze and derive insightful information from data about restaurants in the city of Bangalore, India that are listed on the popular food reviewing and delivery service Zomato. Using these insights, as well as additional information about the ordering behavior of customers in India (with respect to specific food items), a recommender system approach is presented that aims to recommend restaurants to users based on their individual tastes and recommend food items to be ordered by users at those restaurants. A number of solutions are proposed and discussed with their performance and shortcomings.