A recommender system for healthy and personalized recipe recommendations

Florian Pecune, Lucile Callebert, Stacy Marsella

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)

Abstract

Unhealthy eating behavior is a serious public health issue with massive repercussions on an individual's health. One potential solution to this problem is to help people change their eating behavior by developing systems able to recommend healthy recipes that can influence eating behavior. One challenge for such systems is to deliver healthy recommendations that take into account users' needs and preferences, while also informing users about the healthiness of the recommended recipes. In this paper, we investigate whether introducing a healthy bias in a recipe recommendation algorithm, and displaying a healthy tag on recipe cards would have an influence on people's decision making. To that end, we build three different recipes recommender systems: one that recommends recipes matching users' preferences, another one that only recommends healthy recipes, and a third one that recommends recipes that are both healthy and match users' preferences. We evaluate these three systems through a user study in which we asked participants online to select from a list of recipes the ones they like the most.

Original languageEnglish
Pages (from-to)15-20
Number of pages6
JournalCEUR Workshop Proceedings
Volume2684
Publication statusPublished - 2020
Externally publishedYes
Event5th International Workshop on Health Recommender Systems, HealthRecSys 2020 - Virtual, Online
Duration: 2020 Sep 26 → …

Keywords

  • Collaborative filtering
  • Food recommender system
  • Healthcare

ASJC Scopus subject areas

  • Computer Science(all)

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