Restaurant Recommendation System

In the present paper a restaurant recommendation system has been developed that a recommends a list of restaurants to the user based on his preference criteria. There are two kinds of data files that have been used: restaurant master and customer master. Restaurant master consists of restaurant specific data and customer master consists of customer specific data. We have used decision tree algorithm to classify the customers into high, medium and low budget buckets based on customer demographics and purchase behaviour variables. Similarly, restaurants are also classified based on price category. The rules given by the decision tree algorithm are fed into a dashboard designed using MS Excel. The user can use this dashboard to get a list of restaurants based on his individual preference. The restaurant list is sorted based on users location details with the closest restaurant coming at the top of the list.