Food Recommender System: A Review on Techniques, Datasets and Evaluation Metrics
Yi-Ying Chow, Su-Cheng Haw, Palanichamy Naveen, Elham Abdulwahab Anaam, Hairulnizam Mahdin · Journal of System and Management Sciences · 2023
With the rise of digital platforms and the availability of large amounts of data, food recommender systems have become a powerful tool for helping people discover new and delicious meals.Today, these systems use algorithms and machine learning models to analyze ingredients and recommend meals based on factors such as cuisine, dietary restrictions, and ingredient compatibility.Hence, this paper aims to review the various recommendation techniques employed in the food recommender system.We also discuss the various algorithms that are used in meal recommender systems, including collaborative filtering, content-based filtering, and hybrid approaches.Overall, this paper provides a comprehensive overview of the current state-of-the-art meal recommender systems and to identify the opportunities for future enhancement and development in this field.