The cholesterol factor: Balancing accuracy and health in recipe recommendation through a nutrient-specific metric

Alain Starke, Christoph Trattner, Hedda Bakken, Martin Johannessen, Vegard Solberg

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

Abstract

Whereas many food recommender systems optimize for users' preferences, health is another but often overlooked objective. This paper aims to recommend relevant recipes that avoid nutrients that contribute to high levels of cholesterol, such as saturated fat and sugar. We introduce a novel metric called 'The Cholesterol Factor', based on nutritional guidelines from the Norwegian Directorate of Health, that can balance accuracy and health through linear re-weighting in post-filtering. We tested popular recommender approaches by evaluating a recipe dataset from AllRecipes.com, in which a CF-based SVD method outperformed content-based and hybrid methods. Although we found that increasing the healthiness of a recommended recipe set came at the cost of Precision and Recall metrics, only putting little weight (10-15%) on our Cholesterol Factor can significantly improve the healthiness of a recommendation set with minimal accuracy losses.
Original languageEnglish
Title of host publicationProceedings of the 1st Workshop on Multi-Objective Recommender Systems (MORS 2021)
EditorsH. Abdollahpouri, M. Elahi, M. Mansoury, S. Sahebi, Z. Nazari, A. Chaney, B. Loni
Volume2959
Publication statusPublished - Sep 2021
Event1st Workshop on Multi-Objective Recommender Systems, MORS 2021 - Amsterdam, Netherlands
Duration: 25 Sep 2021 → …

Publication series

NameCEUR Workshop Proceedings
PublisherRheinisch-Westfaelische Technische Hochschule Aachen
ISSN (Print)1613-0073

Conference

Conference1st Workshop on Multi-Objective Recommender Systems, MORS 2021
Country/TerritoryNetherlands
CityAmsterdam
Period25/09/21 → …

Keywords

  • Health
  • Nutrients
  • Offline evaluation
  • Recipes
  • Recommender systems

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