Exploring Eating Behaviours Modelling for User Clustering

Food based dietary guidelines are not fully adopted by consumers. One of the principal explanations for this failure is that they are too general and do not take into account eating habits. Experts in nutrition believe that providing personalized dietary recommendations via nutrition recommender system can help people improve their eating behaviours. Understanding eating habits is a keystone in order to build a context aware recommender system that delivers personalized dietary recommendations. As a step towards this goal, we propose a method for representing food consumptions based on Doc2Vec for discovering clusters of eating behaviours. We compare our method to the state of the art methods used in the nutrition community.

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