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Exploring and comprehending the culinary heritage of a nation holds acaptivating allure. It offers insights into the structure and qualities of itscuisine. The endeavor becomes more accessible with the availability of awell-organized dataset. In this paper, we present the introduction of INDoRI(Indian Dataset of Recipes and Ingredients), a compilation drawn from sevendistinct online platforms, representing 18 regions within the Indiansubcontinent. This comprehensive geographical span ensures a portrayal of therich variety within culinary practices. Furthermore, we introduce a uniquecollection of stop words, referred to as ISW (Ingredient Stop Words), manuallytuned for the culinary domain. We assess the validity of ISW in the context ofglobal cuisines beyond Indian culinary tradition. Subsequently, an ingredientnetwork (InN) is constructed, highlighting interconnections among ingredientssourced from different recipes. We delve into both the defining attributes ofINDoRI and the communal dimensions of InN. Additionally, we outline thepotential applications that can be developed leveraging this dataset.Addressing one of the applications, we demonstrated a research problem on InNwith a simple weighted community detection algorithm. Furthermore, we provide acomparative analysis of the results obtained with this algorithm against thosegenerated by two baselines.

INDoRI: Indian Dataset of Recipes and Ingredients and its Ingredient Network