WineGraph: A Graph Representation for Food-Wine Pairing

Zuzanna Gawrysiak; Agata Żywot; Agnieszka Ławrynowicz

doi:10.1007/978-3-031-71170-1_3

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Title

WineGraph: A Graph Representation for Food-Wine Pairing

Authors

Zuzanna Gawrysiak (WIiT) ^{[ 1 ][ S ]}
Agata Żywot (WIiT) ^{[ 1 ][ S ]}
Agnieszka Ławrynowicz (WIiT) ^{[ 2 ][ 2.3 ][ P ]}

^{[ 1 ]} Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | ^{[ 2 ]} Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | ^{[ S ]} student | ^{[ P ]} employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2024

Chapter type

chapter in monograph / paper

Publication language

english

Keywords

EN

heterogeneous graph
graph embeddings
rules
neuro- symbolic learning and reasoning
computational food

Abstract

EN 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.

Date of online publication

10.09.2024

Pages (from - to)

24 - 31

DOI

10.1007/978-3-031-71170-1_3

URL

https://link.springer.com/chapter/10.1007/978-3-031-71170-1_3

Book

Neural-Symbolic Learning and Reasoning : 18th International Conference, NeSy 2024, Barcelona, Spain, September 9–12, 2024, Proceedings, Part II

Presented on

18th International Conference on Neural-Symbolic Learning and Reasoning NeSy 2024, 9-12.09.2024, Barcelona, Spain