Meal Recommendation System Using Machine Learning

In this study, we propose a unified meal recommendation system designed to enhance the dining experience for hotel guests by suggesting meals that satisfy their daily calorie needs and dietary preferences. The findings indicate that this hybrid approach has significant potential to recommend meals accurately while aligning user preferences with their behavioral patterns. This solution provides a practical and scalable way for hotels to encourage healthier and more enjoyable dining experiences through personalized meal suggestions. By merging content-based and collaborative filtering techniques, the technology addresses the varied preferences of guests, ensuring an enriched culinary experience throughout their stay.