Online Food Recipe Title Semantics: Combining Nutrient Facts and Topics

Abstract

Dietary pattern analysis is an important research area, and recently the availability of rich resources in food-focused social networks has enabled new opportunities in that field. However, there is a little understanding of how online textual content is related to actual health factors, e.g., nutritional values. To contribute to this lack of knowledge, we present a novel approach to mine and model online food content by combining text topics with related nutrient facts. Our empirical analysis reveals a strong correlation between them and our experiments show the extent to which it is possible to predict nutrient facts from meal name.