Perfecting Dinner Through Data Mining

A team led by Lada Adamic, a computer scientist at the University of Michigan and Facebook, created an algorithm (pdf) to predict how successful a recipe will be. Michaeleen Doucleff is impressed:

It predicts with nearly 80 percent accuracy how many stars your mother's cranberry recipe will receive on Plus, it can recommend ingredient replacements to make your pie crust and potatoes more healthful. She and her team took nearly 50,000 recipes and 2 million reviews from and then hacked up an algorithm to extract out all the ingredients, cooking methods and nutritional profiles. With just these items, her algorithm could predict the recipe's rating with an accuracy of about 70 percent.

But the magic happened when Adamic built a "social network" for the ingredients. She looked at how often two ingredients appear in the same recipes. Those that frequently show up together — milk and butter, nutmeg and cinnamon, basil and rosemary — sit close to each other in the network, but those that rarely appear in the same dish, such as coconut and parsley, are far from each other. … Adamic's network analysis boosted the accuracy of her recipe recommendations by about 10 percent.