Towards Adaptive and Personalised Recommendation for Healthy Food Promotion - Université de Lorraine
Proceedings/Recueil Des Communications Année : 2023

Towards Adaptive and Personalised Recommendation for Healthy Food Promotion

Résumé

This paper presents ongoing work on an adaptive persuasive system to promote healthy eating habits. It exploits and extends the idea of a constrained question answering (QA) system over a knowledge graph proposed by Chen et al. [1]. In particular, we introduce the way to model personalised challenges, a key component of gamified behaviour change techniques, and additional constraints allowing to handle meal plans by keeping a track on the distribution of daily intakes across meals, repetitive recommendations, constraints related to nutritional labels of the recipes. To access rich nutrition and user-item interaction data, we use HUMMUS [2] instead of FoodKG [3].
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Dates et versions

hal-04261745 , version 1 (27-10-2023)

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  • HAL Id : hal-04261745 , version 1

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Diana Nurbakova, Felix Bölz, Audrey Serna, Jean Brignone. Towards Adaptive and Personalised Recommendation for Healthy Food Promotion. 2023. ⟨hal-04261745⟩
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