  In this paper, we explore the problem of identifying substitute relationship
between food pairs from real-world food consumption data as the first step
towards the healthier food recommendation. Our method is inspired by the
distributional hypothesis in linguistics. Specifically, we assume that foods
that are consumed in similar contexts are more likely to be similar dietarily.
For example, a turkey sandwich can be considered a suitable substitute for a
chicken sandwich if both tend to be consumed with french fries and salad. To
evaluate our method, we constructed a real-world food consumption dataset from
MyFitnessPal's public food diary entries and obtained ground-truth human
judgements of food substitutes from a crowdsourcing service. The experiment
results suggest the effectiveness of the method in identifying suitable
substitutes.
