Hierarchical Clustering of World Cuisines
April 26, 2020 Β· Declared Dead Β· π 2020 IEEE 36th International Conference on Data Engineering Workshops (ICDEW)
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Authors
Tript Sharma, Utkarsh Upadhyay, Jushaan Kalra, Sakshi Arora, Saad Ahmad, Bhavay Aggarwal, Ganesh Bagler
arXiv ID
2004.12283
Category
cs.SI: Social & Info Networks
Cross-listed
physics.soc-ph
Citations
3
Venue
2020 IEEE 36th International Conference on Data Engineering Workshops (ICDEW)
Last Checked
3 months ago
Abstract
Cultures across the world have evolved to have unique patterns despite shared ingredients and cooking techniques. Using data obtained from RecipeDB, an online resource for recipes, we extract patterns in 26 world cuisines and further probe for their inter-relatedness. By application of frequent itemset mining and ingredient authenticity we characterize the quintessential patterns in the cuisines and build a hierarchical tree of the world cuisines. This tree provides interesting insights into the evolution of cuisines and their geographical as well as historical relatedness.
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