Abstract
With the increased use of AI methods to provide recommendations in the health, and specifically, food space, there is also an increased need for explainability of those recommendations. Such explanations would benefit users of recommendation systems by empowering them with a justification for following the system's suggestions. We present the Food Explanation Ontology (FEO) that provides a formalism for generating explanations to users for food-related recommendations. FEO creates a semantic modeling for food recommendations, using concepts from the explanation domain to create intelligent responses to user questions about food recommendations they receive from AI systems such as personalized knowledge base question answering systems. FEO uses a modular, extensible structure that lends itself to a variety of explanations while still preserving important semantic details to accurately represent food recommendations.
List of Resources
| Resources | Links |
|---|---|
| Ontology | Food Explanation Ontology |
| Competency Questions | SPARQL Queries |
| Tools Used | References to tools used |
Tools Used during Development
- Ontology Editor: Protege 5.5.0
- Ontology documentation tool, Widoco
- RDF Visualization and Conceptual Diagram generated with RDFViewer