demonstration

Health-aware Food Recommender System

Authors:

Mouzhi Ge,

Francesco Ricci,

David MassimoAuthors Info & Claims

RecSys '15: Proceedings of the 9th ACM Conference on Recommender Systems

Pages 333 - 334

https://doi.org/10.1145/2792838.2796554

Published: 16 September 2015 Publication History

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Abstract

With the rapid changes in the food variety and lifestyles, many people are facing the problem of making healthier food decisions to reduce the risk of chronic diseases such as obesity and diabetes. To this end, our recommender system not only offers recipe recommendations that suit the user's preference but is also able to take the user's health into account. It is developed on a mobile platform by considering that our application may be directly used in the kitchen. This demo paper summarizes the complete human-computer interaction design, the implemented health-aware recommendation algorithm and preliminary user feedback.

References

[1]

J. Freyne and S. Berkovsky. Intelligent food planning: personalized recipe recommendation. In Proceedings of the 15th International Conference on Intelligent User Interfaces, pages 321--324. ACM, 2010.

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[2]

M. Ge, M. Elahi, I. Fernández-Tobías, F. Ricci, and D. Massimo. Using tags and latent factors in a food recommender system. In Proceedings of the 5th International Conference on Digital Health. ACM, 2015.

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Google Scholar

[3]

W. McArdle, F. Katch, and V. Katch. Exercise Physiology: Energy, Nutrition, and Human Performance. Lippincott Williams and Wilkins, 2001.

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J. Vig, S. Sen, and J. Riedl. The tag genome: Encoding community knowledge to support novel interaction. ACM Transactions on Interactive Intelligent Systems, 2(3):13:1--13:44, 2012.

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Cited By

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Petruzzelli AMusto CDi Carlo MTempesta GSemeraro G(2024)Recommending Healthy and Sustainable Meals exploiting Food Retrieval and Large Language ModelsProceedings of the 18th ACM Conference on Recommender Systems10.1145/3640457.3688193(1057-1061)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3640457.3688193
Ibrahim ZCaldeira CChung C(2024)Supporting Experiential Learning in People with Gestational Diabetes MellitusProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642674(1-16)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642674
Felfernig AWundara MTran TLe VLubos SPolat-Erdeniz S(2024)Sports recommender systems: overview and research directionsJournal of Intelligent Information Systems10.1007/s10844-024-00857-w62:4(1125-1164)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10844-024-00857-w
Show More Cited By

Index Terms

Health-aware Food Recommender System
1. Applied computing
  1. Operations research
    1. Decision analysis
2. Information systems
  1. Information systems applications
    1. Decision support systems

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Information & Contributors

Information

Published In

RecSys '15: Proceedings of the 9th ACM Conference on Recommender Systems

September 2015

414 pages

ISBN:9781450336925

DOI:10.1145/2792838

General Chairs:
Hannes Werthner
TU Wien, Austria
,
Markus Zanker
Alpen-Adria-Universität Klagenfurt, Austria
,
Program Chairs:
Jennifer Golbeck
University of Maryland, USA
,
Giovanni Semeraro
University of Bari Aldo Moro, Italy

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 September 2015

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Author Tags

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Demonstration

Funding Sources

Free University of Bozen-Bolzano

Conference

RecSys '15

Sponsor:

SIGCHI

RecSys '15: Ninth ACM Conference on Recommender Systems

September 16 - 20, 2015

Vienna, Austria

Acceptance Rates

RecSys '15 Paper Acceptance Rate 28 of 131 submissions, 21%;

Overall Acceptance Rate 254 of 1,295 submissions, 20%

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Citations

Cited By

View all

Petruzzelli AMusto CDi Carlo MTempesta GSemeraro G(2024)Recommending Healthy and Sustainable Meals exploiting Food Retrieval and Large Language ModelsProceedings of the 18th ACM Conference on Recommender Systems10.1145/3640457.3688193(1057-1061)Online publication date: 8-Oct-2024
https://dl.acm.org/doi/10.1145/3640457.3688193
Ibrahim ZCaldeira CChung C(2024)Supporting Experiential Learning in People with Gestational Diabetes MellitusProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642674(1-16)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642674
Felfernig AWundara MTran TLe VLubos SPolat-Erdeniz S(2024)Sports recommender systems: overview and research directionsJournal of Intelligent Information Systems10.1007/s10844-024-00857-w62:4(1125-1164)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10844-024-00857-w
Bölz FNurbakova DCalabretto SGerl ABrunie LKosch H(2023)HUMMUS: A Linked, Healthiness-Aware, User-centered and Argument-Enabling Recipe Data Set for RecommendationProceedings of the 17th ACM Conference on Recommender Systems10.1145/3604915.3609491(1-11)Online publication date: 14-Sep-2023
https://dl.acm.org/doi/10.1145/3604915.3609491
Shi JKomamizu TDoman KKyutoku HIde I(2023)RecipeMeta: Metapath-enhanced Recipe Recommendation on Heterogeneous Recipe NetworkProceedings of the 5th ACM International Conference on Multimedia in Asia10.1145/3595916.3626430(1-7)Online publication date: 6-Dec-2023
https://dl.acm.org/doi/10.1145/3595916.3626430
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
Nurbakova DSerna AOmiri ABoutet A(2023)Adaptive and Privacy-Aware Persuasive Strategies to Promote Healthy Eating Habits: Position PaperAdjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization10.1145/3563359.3596987(129-131)Online publication date: 26-Jun-2023
https://dl.acm.org/doi/10.1145/3563359.3596987
Song YYang XXu C(2023)Self-supervised Calorie-aware Heterogeneous Graph Networks for Food RecommendationACM Transactions on Multimedia Computing, Communications, and Applications10.1145/352461819:1s(1-23)Online publication date: 3-Feb-2023
https://dl.acm.org/doi/10.1145/3524618
Vandeputte JPelachaud CTaylor MFaliszewski PMascardi V(2022)The Coaching ScenarioProceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems10.5555/3535850.3536138(1881-1883)Online publication date: 9-May-2022
https://dl.acm.org/doi/10.5555/3535850.3536138
Ozeki SKotera MIshiguro KNishimura THiguchi KYamakata YHashimoto AChen J(2022)Recipe Recommendation for Balancing Ingredient Preference and Daily NutrientsProceedings of the 1st International Workshop on Multimedia for Cooking, Eating, and related APPlications10.1145/3552485.3554941(11-19)Online publication date: 10-Oct-2022
https://dl.acm.org/doi/10.1145/3552485.3554941
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Using Tags and Latent Factors in a Food Recommender System

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