Data-driven investigations of culinary patterns in traditional recipes across the world

Navjot Singh; Ganesh Bagler

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arXiv · 1803.04343

Data-driven investigations of culinary patterns in traditional recipes across the world

Navjot Singh·Ganesh Bagler

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Abstract

Cultures around the world have acquired unique culinary practices reflected in traditional recipe compositions. Data-driven analysis has the potential to provide interesting insights into the structure of recipes and organizational principles of cuisines. We provide a curated compilation of 45772 traditional recipes from over 22 regions across the world. Using this resource in conjunction with data of flavor molecules from natural ingredients, we implement data-driven investigations for probing flavor pairing patterns in these recipes. Our analysis reveals non-random recipe compositions characterized with either 'uniform' or 'contrasting' flavor blending and identifies popularity of ingredients as a key contributing factor across all cuisines. Thus we provide a framework for data-driven investigations of culinary patterns in recipes which can be leveraged for applications aimed at food design, generating novel flavor pairings and tweaking recipes for better nutrition and health.

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Navjot Singh, Ganesh Bagler. 2018-03-12. Data-driven investigations of culinary patterns in traditional recipes across the world. https://arxiv.org/abs/1803.04343

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