IRAIApr 25, 2025

World Food Atlas Project

arXiv:2504.18727v15 citationsh-index: 52CEA@ISMR
Originality Synthesis-oriented
AI Analysis

This project aims to help people better manage their food habits, especially during times like the coronavirus pandemic, but it appears incremental as it builds on existing data and applications without introducing major new methods.

The authors tackled the problem of understanding and controlling food consumption by proposing the World Food Atlas, which includes a Food Knowledge Graph derived from recipes and nutrition data, and applications for collecting detailed food habit records.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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