SHARE: A Framework for Personalized and Healthy Recipe Recommendations

Abstract

This paper presents a personalized recommendation system that suggests recipes to users based on their health history and similar users' preferences. Specifically, the system utilizes collaborative filtering to determine other users with similar dietary preferences and exploits this information to identify suitable recipes for an individual. The system is able to handle a wide range of health constraints, preferences, and specific diet plans, such as low-carb or vegetarian. We demonstrate the usability of the system through a series of experiments on a large real-world data set of recipes. The results indicate that our system is able to provide highly personalized and accurate recommendations.