  The availability of an accurate nutrition profile of recipes is an important
feature for food databases with several applications including nutritional
assistance, recommendation systems, and dietary analytics. Often in online
databases, recipes are obtained from diverse sources in an attempt to maximize
the number of recipes and variety of the dataset. This leads to an incomplete
and often unreliable set of nutritional details. We propose a scalable method
for nutritional profile estimation of recipes from their ingredients section
using a standard reliable database for the nutritional values. Previous studies
have testified the efficiency of string-matching methods on small datasets. To
demonstrate the effectiveness of our procedure, we apply the proposed method on
a large dataset, RecipeDB, which contains recipes from multiple data sources,
using the United States Department of Agriculture Standard Reference (USDA-SR)
Database as a reference for computing nutritional profiles. We evaluate our
method by calculating the average error across our database of recipes (36
calories per serving) which is well within the range of errors attributable to
physical variations.
