WineGraph: A Graph Representation For Food-Wine Pairing
This work addresses food-wine pairing for culinary applications, but it is incremental as it extends an existing graph with new data.
The authors tackled the problem of food-wine pairing by integrating wine data into an existing heterogeneous graph (FlavorGraph), using taste descriptors from over 500,000 food reviews and 130,000 wine reviews. The results demonstrated the potential of this approach for enhancing wine pairing recommendations.
We present WineGraph, an extended version of FlavorGraph, a heterogeneous graph incorporating wine data into its structure. This integration enables food-wine pairing based on taste and sommelier-defined rules. Leveraging a food dataset comprising 500,000 reviews and a wine reviews dataset with over 130,000 entries, we computed taste descriptors for both food and wine. This information was then utilised to pair food items with wine and augment FlavorGraph with additional data. The results demonstrate the potential of heterogeneous graphs to acquire supplementary information, proving beneficial for wine pairing.