Lifestyle-related illnesses such as diabetes and obesity are a major problem in the modern world but can be prevented and sometimes even reversed through good nutrition [3]. Food recommender systems have been touted as a potential means to assist people nourish themselves more healthily e.g. [2, 5]. Anecdotally it makes sense to utilise food recommenders as part of a strategy for behavioural change because if you can suggest a change that is less painful then it seems more likely that the user will accept that change and stick with it. If we are interested in recommending meals to provide a balanced diet, however, such systems have a major limitation: the way they work means they learn user preferences for ingredients and food styles, which, of course, leads to users who like and tend to eat fatand calorie-laden meals being recommended fatand calorie-laden meals an outcome not conducive to improving nutritional habits. In this position statement we briefly outline two ways in which the recommendation problem can be reformulated to also encompass nutritional aspects and not just user preferences.
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