Summary of Knowledge-powered Recommendation For An Improved Diet Water Footprint, by Saurav Joshi et al.
Knowledge-Powered Recommendation for an Improved Diet Water Footprint
by Saurav Joshi, Filip Ilievski, Jay Pujara
First submitted to arxiv on: 26 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed recommendation engine uses knowledge graphs to facilitate sustainable and healthy food consumption by suggesting ingredient substitutes in user recipes that improve nutritional value and reduce environmental impact, specifically water footprint. Powered by knowledge graphs, the engine leverages information extraction, schema alignment, and construction of knowledge graphs to provide personalized recommendations. By promoting healthier eating habits and contributing to water conservation efforts, this system architecture offers a promising tool for managing water usage efficiently. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a special computer program that helps people make healthy food choices that also help the environment. The program suggests replacing certain ingredients in recipes with better alternatives that are good for you and the planet. It does this by using information from different sources, like websites and books, to create a big network of connected ideas (called a knowledge graph). This program can help people eat healthier and reduce water waste, which is very important because many people don’t have access to clean drinking water. |
Keywords
* Artificial intelligence * Alignment * Knowledge graph
