Towards a new healthy food decision-making system

Abstract

Latterly, food recommendation systems have received high attention due to their importance to healthy living. On the recommendation domain, most studies focus on recommendations that suggest healthy products for each user based on their profiles. These types of recommender systems offer additional functionality to persuade users to change their buying behavior profitably. However, these systems must highlight the health preferences of the users and their health problems must be adequately taken into account. In this work, healthy food products recommender systems (RS) are our interest study and more specifically using content-based filtering. We represented this content by the food product composition. Our goal was to provide a healthy recommendation to consumers or citizens around the world, especially at this time when disease abounds. Thus, we developed our new healthy recommendation system (HRS). In this paper, we present a new recommendation process for individuals in the area of healthy eating. Furthermore, we analyze the existing state of the art in recommender system techniques and implement an algorithm that responds to this new process with very satisfactory results from the beginning, to conclude we discuss the research challenges related to the development of this kind of HRS.