A preference-based daily meal recommendation framework for patients with diabetes
In recent years, food recommendation systems have garnered significant attention from internet users seeking diets that are both appealing and health-promoting. For individuals managing chronic conditions such as diabetes, personalized food recommendations that consider both individual preferences a...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Graz University of Technology
2025-03-01
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| Series: | Journal of Universal Computer Science |
| Subjects: | |
| Online Access: | https://lib.jucs.org/article/150833/download/pdf/ |
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| Summary: | In recent years, food recommendation systems have garnered significant attention from internet users seeking diets that are both appealing and health-promoting. For individuals managing chronic conditions such as diabetes, personalized food recommendations that consider both individual preferences and nutritional requirements could potentially yield substantial benefits in maintaining an appropriate dietary regimen. Even though previous research works have been covered the problem of food recommendation for the diabetes domain, they suffer from an insufficient use of the corresponding domain knowledge, and from a deficient management of user preferences in this process. This study then presents a novel preference-based food recommendation framework specifically adapted for patients with diabetes, and that mitigates such previous gaps. Experimental findings suggest that within this context, a balance can be achieved between appealing and health promotion, resulting in nutritionally appropriate menus that simultaneously align with users’ preferences. |
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| ISSN: | 0948-6968 |