A Knowledge Graph for Semantic-Driven Healthiness Evaluation of Online Recipes

The proliferation of recipes on the Web presents an opportunity for developing AI methods to promote healthy nutrition of people using the Internet as a source of food inspiration. Recent research endeavors have resulted in the development of ontologies related to food, and algorithmic solutions for ingredient substitution. However, there is a lack of a resource oriented towards promoting research in semantic-based algorithmic meal plan recommendation and/or individual ingredient substitution that explicitly incorporates healthiness into the recommendation process.

To address this gap, we present a knowledge graph comprising a large collection of recipes sourced from Allrecipes.com, their ingredients and corresponding nutritional information, social interactions metadata. The associated ontology allows healthiness information to be inferred using recommendations from two international nutritional standards.

For more details and access to the source code, please refer to the <a href="https://github.com/IDIASLab/RecipeKG">GitHub repository</a> associated with this dataset.