Food Recommender Systems: Important Contributions, Challenges and Future Research Directions

TL;DR

This paper reviews the current state, challenges, and future directions of food recommender systems, emphasizing their role in promoting healthy eating and personalized food suggestions.

Contribution

It offers a comprehensive summary of seminal and recent approaches, highlighting specializations and outlining future research challenges in food recommender systems.

Findings

Food recommender systems help users find preferred foods and promote healthy eating.

Recent approaches include group-based and health-focused recommendations.

The paper identifies key challenges and open questions for future research.

Abstract

The recommendation of food items is important for many reasons. Attaining cooking inspiration via digital sources is becoming evermore popular; as are systems, which recommend other types of food, such as meals in restaurants or products in supermarkets. Researchers have been studying these kinds of systems for many years, suggesting not only that can they be a means to help people find food they might want to eat, but also help them nourish themselves more healthily. This paper provides a summary of the state-of-the-art of so-called food recommender systems, highlighting both seminal and most recent approaches to the problem, as well as important specializations, such as food recommendation systems for groups of users or systems which promote healthy eating. We moreover discuss the diverse challenges involved in designing recsys for food, summarise the lessons learned from past research and outline what we believe to be important future directions and open questions for the field. In providing these contributions we hope to provide a useful resource for researchers and practitioners alike.