A hybrid framework for a comprehensive physical activity and diet recommendation system

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Abstract

The quantified self-movement has gained a lot of traction, recently. In this regard, research in personalized wellness support systems has increased. Most of the recommender systems focus on either calorie-burn or calorie-in take objectives. The achievement of calorie-burn objective is through physical activity recommendations while diet recommendations geared towards calorie-in take objectives. A very limited research is performed which track and optimize objectives for both calorie-burn and calorie-in-take, simultaneously based on well-known wellness support guidelines. In this regard, we propose a hybrid recommendation framework, which provides recommendations for physical activity as well as diet recommendation in order to support wellness requirements of a user in a comprehensive manner.

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Ali, S. I., Amin, M. B., Kim, S., & Lee, S. (2018). A hybrid framework for a comprehensive physical activity and diet recommendation system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10898 LNCS, pp. 101–109). Springer Verlag. https://doi.org/10.1007/978-3-319-94523-1_9

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