User Nutrition Modelling and Recommendation: Balancing Simplicity and Complexity


In order to use and model nutritional knowledge in a food recommender system, uncertainties regarding the users nutritional state and thus the personal health value of food items, as well as conflicting nutritional theories need to be quantified, qualified and subsumed into falsifiable models. In this paper, we reflect on different error sources with respect to nutrition and consider how such issues can be tackled in future systems. We discuss the integration of general nutritional theories into information systems as well as user specific nutritional measures and different approaches to evaluating the utility of a given nutritional model.

DOI: 10.1145/3099023.3099108

Cite this paper

@inproceedings{Schfer2017UserNM, title={User Nutrition Modelling and Recommendation: Balancing Simplicity and Complexity}, author={Hanna Sch{\"a}fer and Mehdi Elahi and David Elsweiler and Georg Groh and Morgan Harvey and Bernd Ludwig and Francesco Ricci and Alan Said}, booktitle={UMAP}, year={2017} }