Restaurant recommendation system by using data mining techniques

Abstract

Nowadays we can see many restaurants in different category in different locations. But do you know what the best restaurants there are? Is there a way to identify the best restaurants? With this proposed solution, we can identify the best restaurants around you that is called “Restaurant recommendation system”. It provides a good experience to the end user to find the best restaurant for their preferences. Based on previous user experience or feelings about the restaurant we can get some idea about the restaurant. If someone recommends a system, we can think of it as a good restaurant. In this system takes three user inputs on restaurant menu items. The first one is recommending or not recommending as direct input on a restaurant. The second input is rating on a restaurant menu item scaling one to five. The third input is analyzing users’ reviews about the restaurant menu item. So, we can apply data mining techniques like opinion mining and Apriori algorithm on the user inputs and get the output as recommended menu item along with the restaurant. Based on those three user inputs above mentioned we could decide what the best restaurant meals are by calculating average ratings and ranking them. Not only that. This system will also provide suggestions about restaurants or meals of a restaurant based on users’ preferences by using data mining techniques like collaboration filtering. The collaboration filtering is focused on users’ preferences. And, it uses opinion mining techniques to analyze reviews. This system is a web application with the REST service. For the front-end development used Angular to make it rich application and for back end uses Java with REST web service. In addition to that uses spring framework and hibernate for object relational mapping.