Abstract
Adaptation is one of the most important phases in the Case-based Reasoning cycle since it reuses solutions that have already proven to be successful in the past to new situations. The main challenge of the present work is to adapt these successful solutions to the individual characteristics of each person, in order to take into account all his/her limitations, and ensure their adherence to a diet and exercise plan to improve cardiovascular health. This paper aimed to implement a methodology for the adaptation phase of a system of diet and exercise recommendations, in order to propose options that present good results having enough variability for promoting the emergence of new solutions. The adopted methodology uses ontologies as a knowledge base and adapts the recommendations to the different constraints and preferences of each user, as well as to the climatic conditions of the day in which the recommendations are made. The integration of this methodology into the main application provides more personalized recommendations that improve the learning capabilities of the system.
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Notes
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Total caloric expenditure of a given activity.
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This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020.
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Duarte, A., Belo, O. (2023). Blending Case-Based Reasoning with Ontologies for Adapting Diet Menus and Physical Activities. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2022. Lecture Notes in Networks and Systems, vol 544. Springer, Cham. https://doi.org/10.1007/978-3-031-16075-2_60
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