# World Food Atlas Project

arXiv: https://arxiv.org/abs/2504.18727 · HTML: https://mlsanity.com/paper/2504.18727/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 10 references that are in the map.
- First posted on arXiv 25 Apr 2025.

## Builds on (most cited first, 4 of 4)

- [Generating Personalized Recipes from Historical User Preferences](https://mlsanity.com/paper/1909.00105/) (2019)
- [Inverse Cooking: Recipe Generation from Food Images](https://mlsanity.com/paper/1812.06164/) (2018)
- [Food Recommendation: Framework, Existing Solutions and Challenges](https://mlsanity.com/paper/1905.06269/) (2019)
- [Personal Food Model](https://mlsanity.com/paper/2008.12855/) (2020)

## Built on by (most cited first, 1 of 1)

- [Extending FKG.in: Towards a Food Claim Traceability Network](https://mlsanity.com/paper/2508.16117/) (2025)

## Abstract (arXiv)

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.