A systematic review on food recommender systems

Jon Nicolas Bondevik (Corresponding author), Kwabena Ebo Bennin (Corresponding author), Önder Babur (Corresponding author), Carsten Ersch (Corresponding author)

Research output: Contribution to journalReview articlepeer-review

16 Citations (Scopus)
318 Downloads (Pure)

Abstract

The Internet has revolutionised the way information is retrieved, and the increase in the number of users has resulted in a surge in the volume and heterogeneity of available data. Recommender systems have become popular tools to help users retrieve relevant information quickly. Food Recommender Systems (FRS), in particular, have proven useful in overcoming the overload of information present in the food domain. However, the recommendation of food is a complex domain with specific characteristics causing many challenges. Additionally, very few systematic literature reviews have been conducted in the domain on FRS. This paper presents a systematic literature review that summarises the current state-of-the-art in FRS. Our systematic review examines the different methods and algorithms used for recommendation, the data and how it is processed, and evaluation methods. It also presents the advantages and disadvantages of FRS. To achieve this, a total of 67 high-quality studies were selected from a pool of 2,738 studies using strict quality criteria. The review reveals that the domain of food recommendation is very diverse, and most FRS are built using content-based filtering and ML approaches to provide non-personalised recommendations. The review provides valuable information to the research field, helping researchers in the domain to select a strategy to develop FRS. This review can help improve the efficiency of development, thus closing the gap between the development of FRS and other recommender systems.

Original languageEnglish
Article number122166
Number of pages22
JournalExpert Systems with Applications
Volume238
Issue numberPart E
DOIs
Publication statusPublished - 15 Mar 2024

Bibliographical note

Publisher Copyright:
© 2023 The Author(s)

Funding

We confirm that we have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. In so doing we confirm that we have followed the regulations of our institutions concerning intellectual property.

Keywords

  • Food recommendation
  • Food recommender system
  • Recommender system
  • SLR
  • Systematic literature review

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