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Title:Herb & Spice Network and Health Indications
Author(s):Zhang, Shuchen
Contributor(s):Varshney, Lav
Degree:B.S. (bachelor's)
Genre:Thesis
Subject(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.
Issue Date:2019-12
Genre:Dissertation / Thesis
Type:Text
Language:English
URI:http://hdl.handle.net/2142/106022
Date Available in IDEALS:2020-01-09


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