Recipe Recommendation for Balancing Ingredient Preference and Daily Nutrients

In this work, we propose a recipe recommendation system for daily eating habits based on user preference and nutrient balance. This method prompts user input and allows for the substitution or addition of ingredients while reflecting the user's preferences. The system also considers daily nutrient balance to fill dietary reference intakes such as carbohydrates, protein, and fat. While users select a day's worth of preferred recipes, the system updates the recommendation based on user selection and excess/deficiency predefined nutritional criteria. We run a simulation study to see the performance of the proposed algorithm. With our recipe planning application, we also performed a user study that participants chose a day's worth of recipes with preferred ingredients. The results show that the proposed system helps make better nutrient balance recipes than traditional ingredient-based search. In addition, the participants liked recommendations from the proposed system that improved satisfaction with recipe selection.