Indian Journal of Science and Technology

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Food recipes, from traditional recipes to fusion recipes, are easily uploaded and shared online. Recipes consist of a set of ingredients, the cooking procedure, cooking time, etc. It is not easy to classify recipes in terms of the taste of cooked foods, the cuisine styles, or the characteristics of foods. In this paper, we construct the recipe similarity network by adding edges if two different recipes share common ingredients. For this, we newly define the similarity measure among recipes using the probabilistic entropy measures over ingredients. And we construct the ingredient relation network that shows the correlations of ingredients in the recipes. We show these networks can be applied to show the hierarchical structure of 683 recipes and 375 ingredients and the similar recipes are well clustered according to the entropy measure.

Keywords

Complex Network, Ingredient, Ingredient Entropy, Recipe Entropy, Recipe, Recipe Similarity.
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