Information Extraction from Unstructured Recipe Data

Abstract

Online food recipes are an important source of information for many individuals, who use these to learn how to cook new dishes and choose their meals. However, these often lack structured information, useful to improve search and recommendation systems of food recipe websites, as well as calculate accurate nutritional information, which brings additional value to users. To solve this problem, FRIES was developed. FRIES automatically extracts the names, quantities, units and cooking methods for each ingredient in a recipe. The system uses mainly rule-based methods and achieves an average F-measure of 0.89 for the extraction of the cooking methods present in a recipe and an average F-measure of 0.83 for the extraction of associations linking cooking methods to ingredients. FRIES' results show that it can accurately and automatically extract information from cooking recipes. This information can be used to estimate the nutritional information of food recipes and support recommendation systems.