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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Acknowledgement
This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2017-0-01629) supervised by the IITP (Institute for Information & communications Technology Promotion)” and by the Korea Research Fellowship Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2016H1D3A1938039).
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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: Mokhtari, M., Abdulrazak, B., Aloulou, H. (eds) Smart Homes and Health Telematics, Designing a Better Future: Urban Assisted Living. ICOST 2018. Lecture Notes in Computer Science(), vol 10898. Springer, Cham. https://doi.org/10.1007/978-3-319-94523-1_9
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DOI: https://doi.org/10.1007/978-3-319-94523-1_9
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