2011
DOI: 10.1038/srep00196
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Flavor network and the principles of food pairing

Abstract: The cultural diversity of culinary practice, as illustrated by the variety of regional cuisines, raises the question of whether there are any general patterns that determine the ingredient combinations used in food today or principles that transcend individual tastes and recipes. We introduce a flavor network that captures the flavor compounds shared by culinary ingredients. Western cuisines show a tendency to use ingredient pairs that share many flavor compounds, supporting the so-called food pairing hypothes… Show more

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Cited by 360 publications
(352 citation statements)
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References 26 publications
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“…Due to the challenges associated with analyzing large weighted networks, we reduced the number of edges in the weighted subreddit network using a backbone extraction algorithm (Serrano, Boguñá & Vespignani, 2009) that has previously been used to reduce bipartite projections (Ahn et al, 2011). This algorithm begins by replacing symmetric valued edges (S ij ) with asymmetric weighted edges (A ij and A ji ), where A ij = S ij /i's degree and A ji = S ij /j's degree.…”
Section: Methodsmentioning
confidence: 99%
“…Due to the challenges associated with analyzing large weighted networks, we reduced the number of edges in the weighted subreddit network using a backbone extraction algorithm (Serrano, Boguñá & Vespignani, 2009) that has previously been used to reduce bipartite projections (Ahn et al, 2011). This algorithm begins by replacing symmetric valued edges (S ij ) with asymmetric weighted edges (A ij and A ji ), where A ij = S ij /i's degree and A ji = S ij /j's degree.…”
Section: Methodsmentioning
confidence: 99%
“…Besides the approaches focused on flavor networks which consider cooking recipes as "bags of ingredients" such as (Ahn et al, 2011), the existing approaches to the recipe analysis concentrate on recipes taken as a sequence of instructions that can be mapped to a series of actions. Numerous publications concern the implementation of supervised learning methods.…”
Section: Cooking Instruction Analysismentioning
confidence: 99%
“…Indeed in bipartite, also referred as 2-mode networks, the set of nodes is composed of two disjoint parts, and ⊥ (for example movies and actors), such that edges only relate vertices of different sets. It has been shown that this fundamental object is reliable both for analysing [10], [11], [12] and modeling [13], [14] the structure of real-world networks.…”
Section: Introductionmentioning
confidence: 99%