skip to main content
10.1145/3463947.3469235acmconferencesArticle/Chapter ViewAbstractPublication PagesmmConference Proceedingsconference-collections
short-paper

World Food Atlas Project

Published: 21 August 2021 Publication History

Abstract

A coronavirus pandemic is forcing people to be "at home" all over the world. In a life of hardly ever going out, we would have realized how the food we eat affects our bodies. What can we do to know our food more and control it better? To give us a clue, we are trying to build a World Food Atlas (WFA) that collects all the knowledge about food in the world. In this paper, we present two of our trials. The first is the Food Knowledge Graph (FKG), which is a graphical representation of knowledge about food and ingredient relationships derived from recipes and food nutrition data. The second is the FoodLog Athl and the RecipeLog that are applications for collecting people's detailed records about food habit. We also discuss several problems that we try to solve to build the WFA by integrating these two ideas.

References

[1]
Kiyoharu Aizawa. 2019. FoodLog: Multimedia Food Recording Platform and its Application. 32--32. https://doi.org/10.1145/3347448.3352809
[2]
Damion M. Dooley, Emma J. Griffiths, Gurinder S. Gosal, Pier L. Buttigieg, Robert Hoehndorf, Matthew C. Lange, Lynn M. Schriml, Fiona S.L. Brinkman, and William W.L. Hsiao. 2018. Food on: A harmonized food ontology to increase global food traceability, quality control and data integration. npj Science of Food, Vol. 2, 1 (2018), 1--10. https://doi.org/10.1038/s41538-018-0032--6
[3]
Chloé Kiddon, Luke Zettlemoyer, and Yejin Choi. 2016. Globally Coherent Text Generation with Neural Checklist Models. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing. 329--339.
[4]
Bodhisattwa Prasad Majumder, Shuyang Li, Jianmo Ni, and Julian McAuley. 2019. Generating Personalized Recipes from Historical User Preferences. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 5976--5982. https://doi.org/10.18653/v1/D19--1613
[5]
Javier Marin, Aritro Biswas, Ferda Ofli, Nicholas Hynes, Amaia Salvador, Yusuf Aytar, Ingmar Weber, and Antonio Torralba. 2021. Recipe1M+: A Dataset for Learning Cross-Modal Embeddings for Cooking Recipes and Food Images. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 43, 1 (2021), 187--203. https://doi.org/10.1109/TPAMI.2019.2927476
[6]
Weiqing Min, Shuqiang Jiang, and Ramesh Jain. 2020. Food Recommendation: Framework, Existing Solutions, and Challenges . IEEE Transactions on Multimedia, Vol. 22, 10 (2020), 2659--2671. https://doi.org/10.1109/TMM.2019.2958761
[7]
Vaibhav Pandey, Ali Rostami, Nitish Nag, and Ramesh Jain. 2021. Event Mining Driven Context-Aware Personal Food Preference Modelling. 660--676. https://doi.org/10.1007/978--3-030--68821--9_52
[8]
Ali Rostami, Vaibhav Pandey, Nitish Nag, Vesper Wang, and Ramesh Jain. 2020 a. Personal Food Model. arXiv (2020). https://doi.org/10.1145/3394171.3414691
[9]
Ali Rostami, Bihao Xu, and Ramesh Jain. 2020 b. Multimedia Food Logger. In Proceedings of the 28th ACM International Conference on Multimedia.
[10]
Amaia Salvador, Michal Drozdzal, Xavier Giro-I-Nieto, and Adriana Romero. 2019. Inverse cooking: Recipe generation from food images. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2019-June. IEEE Computer Society, 10445--10454. https://doi.org/10.1109/CVPR.2019.01070

Cited By

View all
  • (2025)Food Recommendation Towards Personalized WellbeingTrends in Food Science & Technology10.1016/j.tifs.2025.104877(104877)Online publication date: Jan-2025
  • (2024)Food Recommendation as Language Processing (F-RLP): A Personalized and Contextual Paradigm2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)10.1109/EMBC53108.2024.10782762(1-4)Online publication date: 15-Jul-2024

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
CEA '21: Proceedings of the 13th International Workshop on Multimedia for Cooking and Eating Activities
August 2021
42 pages
ISBN:9781450385329
DOI:10.1145/3463947
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 the author(s) 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].

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 August 2021

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. food computing
  2. food record
  3. knowledge graph
  4. recipe

Qualifiers

  • Short-paper

Conference

ICMR '21
Sponsor:

Acceptance Rates

Overall Acceptance Rate 20 of 33 submissions, 61%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)22
  • Downloads (Last 6 weeks)2
Reflects downloads up to 12 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2025)Food Recommendation Towards Personalized WellbeingTrends in Food Science & Technology10.1016/j.tifs.2025.104877(104877)Online publication date: Jan-2025
  • (2024)Food Recommendation as Language Processing (F-RLP): A Personalized and Contextual Paradigm2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)10.1109/EMBC53108.2024.10782762(1-4)Online publication date: 15-Jul-2024

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media