short-paper

Towards a Knowledge-aware Food Recommender System Exploiting Holistic User Models

Authors:

Christoph Trattner,

Giovanni SemeraroAuthors Info & Claims

UMAP '20: Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization

Pages 333 - 337

https://doi.org/10.1145/3340631.3394880

Published: 13 July 2020 Publication History

Abstract

Food recommender systems typically rely on popularity, as well as similarity between recipes to generate personalized suggestions. However, this leaves little room for users to explore new preferences, such as to adopt healthier eating habits.

In this short paper, we present a recommendation strategy based on knowledge about food and users' health-related characteristics to generate personalized recipes suggestions. By focusing on personal factors as a user's BMI and dietary constraints, we exploited a holistic user model to re-rank a basic recommendation list of 4,671 recipes, and investigated in a web-based experiment (N=200) to what extent it generated satisfactory food recommendations. We found that some of the information encoded in a users' holistic user profiles affected their preferences, thus providing us with interesting findings to continue this line of research.

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Cited By

Wang JZhou JAksoy MSharma NRahman MZain JAlenazi MAminzadeh A(2024)Improving healthy food recommender systems through heterogeneous hypergraph learningEgyptian Informatics Journal10.1016/j.eij.2024.10057028(100570)Online publication date: Dec-2024
https://doi.org/10.1016/j.eij.2024.100570
Starke AMusto CRapp ASemeraro GTrattner C(2024)“Tell Me Why”: using natural language justifications in a recipe recommender system to support healthier food choicesUser Modeling and User-Adapted Interaction10.1007/s11257-023-09377-834:2(407-440)Online publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1007/s11257-023-09377-8
Liu YAchananuparp PLim E(2024)Non-binary evaluation of next-basket food recommendationUser Modeling and User-Adapted Interaction10.1007/s11257-023-09369-834:1(183-227)Online publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1007/s11257-023-09369-8
Show More Cited By

Index Terms

Towards a Knowledge-aware Food Recommender System Exploiting Holistic User Models
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems
  2. World Wide Web
    1. Web searching and information discovery
      1. Personalization

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Published In

cover image ACM Conferences

UMAP '20: Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization

July 2020

426 pages

ISBN:9781450368612

DOI:10.1145/3340631

Editors:
Tsvi Kuflik
University of Haifa, Israel
,
Ilaria Torre
University of Genoa, Italy
,
Robin Burke
University of Colorado, Boulder, USA
,
Cristina Gena
University of Turin, Italy

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

Publication History

Published: 13 July 2020

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Short-paper

Funding Sources

'Niels Stensen Fellowship'

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UMAP '20

Sponsor:

UMAP '20: 28th ACM Conference on User Modeling, Adaptation and Personalization

July 14 - 17, 2020

Genoa, Italy

Acceptance Rates

Overall Acceptance Rate 162 of 633 submissions, 26%

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UMAP '25

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June 16 - 19, 2025

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Cited By

Wang JZhou JAksoy MSharma NRahman MZain JAlenazi MAminzadeh A(2024)Improving healthy food recommender systems through heterogeneous hypergraph learningEgyptian Informatics Journal10.1016/j.eij.2024.10057028(100570)Online publication date: Dec-2024
https://doi.org/10.1016/j.eij.2024.100570
Starke AMusto CRapp ASemeraro GTrattner C(2024)“Tell Me Why”: using natural language justifications in a recipe recommender system to support healthier food choicesUser Modeling and User-Adapted Interaction10.1007/s11257-023-09377-834:2(407-440)Online publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1007/s11257-023-09377-8
Liu YAchananuparp PLim E(2024)Non-binary evaluation of next-basket food recommendationUser Modeling and User-Adapted Interaction10.1007/s11257-023-09369-834:1(183-227)Online publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1007/s11257-023-09369-8
Pera MCena FLandoni MMusto CStarke A(2024)Human Factors in User Modeling for Intelligent SystemsA Human-Centered Perspective of Intelligent Personalized Environments and Systems10.1007/978-3-031-55109-3_1(3-42)Online publication date: 1-May-2024
https://doi.org/10.1007/978-3-031-55109-3_1
Toor RChana I(2024)Cloud menu: Cloud based network analysis for disease‐diet associations and recommendationsConcurrency and Computation: Practice and Experience10.1002/cpe.806536:14Online publication date: 8-Apr-2024
https://doi.org/10.1002/cpe.8065
Starke AAsotic ETrattner CVan Loo E(2023)Examining the User Evaluation of Multi-List Recommender Interfaces in the Context of Healthy Recipe ChoicesACM Transactions on Recommender Systems10.1145/35819301:4(1-31)Online publication date: 24-Feb-2023
https://dl.acm.org/doi/10.1145/3581930
Hors-Fraile SCandel MSchneider FMalwade SNunez-Benjumea FSyed-Abdul SFernandez-Luque Lde Vries H(2022)Applying Collective Intelligence in Health Recommender Systems for Smoking Cessation: A Comparison TrialElectronics10.3390/electronics1108121911:8(1219)Online publication date: 12-Apr-2022
https://doi.org/10.3390/electronics11081219
Tian YZhang CMetoyer RChawla N(2022)Recipe Recommendation With Hierarchical Graph Attention NetworkFrontiers in Big Data10.3389/fdata.2021.7784174Online publication date: 12-Jan-2022
https://doi.org/10.3389/fdata.2021.778417
Starke ALee M(2022)Unifying Recommender Systems and Conversational User InterfacesProceedings of the 4th Conference on Conversational User Interfaces10.1145/3543829.3544524(1-7)Online publication date: 26-Jul-2022
https://dl.acm.org/doi/10.1145/3543829.3544524
El Majjodi AStarke ATrattner CBellogin ABoratto LSantos OArdissono LKnijnenburg B(2022)Nudging Towards Health? Examining the Merits of Nutrition Labels and Personalization in a Recipe Recommender SystemProceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3503252.3531312(48-56)Online publication date: 4-Jul-2022
https://dl.acm.org/doi/10.1145/3503252.3531312
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