A Hybrid Framework for Restaurant Recommender System

Having healthy food and a regular diet are some of the most efficient mechanisms to control chronic diseases such as hypertension and diabetes. The existent systems do not provide mechanisms to allow people in such conditions to easily find restaurants providing suitable food for them. Under these circumstances, this study proposes a design of a conceptual framework for restaurant recommender system to improve people's decision-making process of choosing restaurants providing food according to their health conditions and preferences. The framework includes a user personal profile module, graphical user interface, database, knowledge base, and ontologies containing the restaurant menu items and their respective nutritional information. A prototype system has been developed to test the performance of the framework. The tests show that this framework can be used for the purpose that was conceived.