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A Systematic Literature Review of Food Recommender Systems

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Abstract

The enormous variations in food choices and lifestyle in today’s world have given rise to the demand of using recommender system as a suitable tool in making appropriate food choices. Need for choosing nutritious food items is becoming important in today’s modern lifestyle as people are getting indulged in eating unhealthy food and thus leading to miserable health status. Many lifestyle-related diseases, such as diabetes and obesity, can also be reversed by proper diet. Filtering techniques in recommender system use a dataset of items and user’s preferences as input to discover a list of well-judged items as suggestions. In light of the above said, this paper presents an exploratory study of the recommendation approaches and methods utilized for food and recipe recommendations in the past decade. For this purpose, several relevant papers published in the food domain from 2006 to 2023 have been extensively studied. Further, the research articles are categorized based on the filtering techniques, methods, functionalities and data sources used by the researchers. A comparative study of the recommendation approaches revealed the advantages and disadvantages of different approaches. Also, the paper emphasizes the importance of food recommendation techniques in health and nutrition management of an individual. The review highlights the need to further explore the implementation of recommender systems in the food industry. Furthermore, the findings of this survey provide researchers with insights and future directions on recommender systems in the domain.

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Mahajan, P., Kaur, P.D. A Systematic Literature Review of Food Recommender Systems. SN COMPUT. SCI. 5, 174 (2024). https://doi.org/10.1007/s42979-023-02537-y

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