A Recommender System for Healthy Food Choices: Building a Hybrid Model for Recipe Recommendations using Big Data Sets

Advances in Big Data analytics and machine learning have offered intangible benefits across many areas of one’s health. One such area is a move towards healthier lifestyle choices as diet. Recommender systems apply techniques that can filter information narrow down based on user preferences or needs help users choose what relevant. Commonly adopted e-commerce sites, social networking entertainment industries, recommender also support nutrition-based health management, offering individuals more food options, not only preferred tastes but dietary restrictions. This research presents the design, implementation evaluation three using content-based, collaborative filtering hybrid recommendation models within nutrition domain.