Flavor Network & Umami Network show which ingredients go well together. The basic ideas behind these are “Flavor Pairing Theory” & “Umami Pairing Theory”.
"Flavor Pairing Theory" suggests that different ingredients are more likely to pair well in a recipe when they share key flavors, and "Umami Pairing Theory" suggests that when combining different ingredients containing different Umami compounds such as Glutamate and Inosinate, we can create a synergetic effect. For example, Flavor network shows you that “beer” and “coffee”, which seem completely different, make a great match because they share similar flavors. Actually it tastes like "black beer" to me.
Node : represents ingredient, and size shows prevalence in recipes
Link : thickness shows the number of shared (Flavor/Umami)compounds
Default Mode : switches Flavor and Umami data
Compare Mode : compares network, and views the connection details
Data Visualization: Sho Izumo
Data Science : Masahiro Kazama