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https://hdl.handle.net/2142/106022
Description
Title
Herb & Spice Network and Health Indications
Author(s)
Zhang, Shuchen
Contributor(s)
Varshney, Lav
Issue Date
2019-12
Keyword(s)
recipe-spices-disease multipartite network
minimum set cover
copy-mutate model
Abstract
Spices and herbs are essential culinary ingredients used in cuisines all over the world. They are
known to have medicinal values for large varieties of diseases. In this study, we explored the
relationship between cuisines, spices and diseases through a network analysis viewpoint. We
started with constructing an extensive dictionary between medicinal spices and herbs, and their
disease associations text mined from two handbooks. Centrality measures and various clustering
algorithms were applied to the resulting bipartite and projection graphs to identify the spices and
herbs that play the main roles in disease curing and spice groups that share similar therapeutic
values. Minimum set cover problem was established to find the minimum set of spices needed to
cover the target group of diseases. Then we specifically studied the spice usage patterns in Indian
cuisines, based on the recipes collected from the two main Indian culinary websites. The variations
of spice usages across different regions were learned. We further modeled the evolution of regional
cuisines by generating random recipes with copy-mutate algorithms and compared their disease
coverage capabilities with the real recipe data.
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