User nutrition modelling and recommendation - Balancing simplicity and complexity

Hanna Schäfer, Mehdi Elahi, David Elsweiler, Georg Groh, Morgan Harvey, Bernd Ludwig, Francesco Ricci, Alan Said

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationUMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization
PublisherAssociation for Computing Machinery, Inc
Pages93-96
Number of pages4
ISBN (Electronic)9781450350679
DOIs
StatePublished - 9 Jul 2017
Event25th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2017 - Bratislava, Slovakia
Duration: 9 Jul 201712 Jul 2017

Publication series

NameUMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization

Conference

Conference25th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2017
Country/TerritorySlovakia
CityBratislava
Period9/07/1712/07/17

Keywords

  • Health informatics
  • Nutrition modeling
  • Nutrition recommender systems
  • Online nutrition interventions
  • Patient modeling

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