INDoRI: Indian Dataset of Recipes and Ingredients and its Ingredient Network
Sandeep Khanna, Chiranjoy Chattopadhyay, Suman Kundu

TL;DR
This paper introduces INDoRI, a comprehensive Indian culinary dataset with recipes and ingredients, along with an ingredient network, enabling analysis of culinary structures and regional diversity.
Contribution
The paper presents a new Indian culinary dataset, a domain-specific stop words collection, and constructs an ingredient network for analyzing culinary relationships.
Findings
Ingredient network reveals regional ingredient connections
Community detection identifies ingredient clusters
Dataset supports diverse culinary research
Abstract
Exploring and comprehending the culinary heritage of a nation holds a captivating allure. It offers insights into the structure and qualities of its cuisine. The endeavor becomes more accessible with the availability of a well-organized dataset. In this paper, we present the introduction of INDoRI (Indian Dataset of Recipes and Ingredients), a compilation drawn from seven distinct online platforms, representing 18 regions within the Indian subcontinent. This comprehensive geographical span ensures a portrayal of the rich variety within culinary practices. Furthermore, we introduce a unique collection of stop words, referred to as ISW (Ingredient Stop Words), manually tuned for the culinary domain. We assess the validity of ISW in the context of global cuisines beyond Indian culinary tradition. Subsequently, an ingredient network (InN) is constructed, highlighting interconnections among…
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Taxonomy
TopicsCulinary Culture and Tourism · Identification and Quantification in Food
