An Adaptive Recipe Recommendation System for People with Diabetes Type 2
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Issue Date
2011-06-14
Language
en
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Abstract
Diabetes type 2 (DM2) is a common lifestyle disease caused by an insufficient amount of physical activity, bad eating habits and possibly some genetic factors.
Coaching people on their eating habits and physical activity can help
patients to reduce their dependence on medication. My MSc research project,
executed at Philips Research, was focused on helping people with DM2
to eat healthier. People are creatures of habit and it is difficult for them to
change their eating patterns. For this purpose, we have investigated the use
of a content-based recommender system that suggests recipes based on the
similarity to past choices of a user. We have taken a user-centered approach
in which we collected requirements in a qualitative and a quantitative study.
This has led to the development of an adaptive user representation. This
pro le is used to suggest recipes using a similarity measure. The approach is
evaluated in an experimental study. The results showed that personalizing
recommendations is effective, but that a simple, baseline personalization
is as effective as the more complex adaptive pro ling personalization in the
current study. An additional qualitative user study showed that people with
diabetes appreciated the recipe navigation options we presented them with,
and liked the insight in the healthfulness of their choices which the recipe
recommender gave them. Research in recipe recommendation by matching
recipes to users should be continued.
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Faculteit der Sociale Wetenschappen