Title :
Estimating nutrition values for internet recipes
Author :
Muller, Manuel ; Mika, Stefanie ; Harvey, Morgan ; Elsweiler, David
Author_Institution :
Artificial Intell., Univ. of Erlangen-Nuremberg, Erlangen, Germany
Abstract :
To utilise the vast recipe databases on the Internet in intelligent nutritional assistance or recommender systems, accurate nutritional data for recipes is needed. Unfortunately, most recipes have no such data or have data of suspect quality. In this demo we present a system that automatically calculates the nutritional value of recipes sourced from the Internet. This is a challenging problem for several reasons, including lack of formulaic structure in ingredient descriptions, ingredient synonymy, brand names, and unspecific quantities being assigned. Our results show that our system can generate nutritional values within a 10% error bound of human assessors for calorie, protein and carbohydrate values. Based on our findings this is smaller than the bound between multiple human assessors.
Keywords :
Internet; database management systems; health care; recommender systems; Internet recipes; brand names; calorie values; carbohydrate values; ingredient descriptions; ingredient synonymy; intelligent nutritional assistance; nutrition value estimation; nutritional data; protein values; recipe databases; recommender systems; Humans; Demo; Health; Lifestyle; Prevention; Recommender Systems;
Conference_Titel :
Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2012 6th International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-1483-1
Electronic_ISBN :
978-1-936968-43-5