TY - GEN
T1 - F-EvoRecSys
T2 - 2021 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2021
AU - Palomares, Ivan
AU - Alcaraz-Herrera, Hugo
AU - Shen, Kao Yi
AU - Syed-Abdul, Shabbir
AU - Malwade, Shwetambara
N1 - Funding Information:
*This research was supported in part by Higher Education Sprout Project, Ministry of Education to the Headquarters of University Advancement at National Cheng Kung University(NCKU); CONACYT Mexico PhD Scholarship Programme; Taiwan Ministry of Science & Technology grant MOST-109-2410-H-034-037-MY2; and Taipei Medical University visiting scholarship. 1National Cheng Kung University (NCKU), Tainan, Taiwan. 2Andalusian Institute of Data Science and Computational Intelligence (DaSCI), University of Granada, Spain. 3School of Computer Science, Bristol University, United Kingdom. 4Dept. Banking & Finance, Chinese Culture University, Taipei, Taiwan. 5Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan. 6International Center for Health Information Technology, College of Medical Science & Technology, Taipei Medical University, Taipei, Taiwan. 7School of Gerontology Health Management, College of Nursing, Taipei Medical University, Taipei, Taiwan. Corresponding author e-mail: [email protected]
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Many citizens nowadays cope with busy and dynamic lifestyles. Adopting or maintaining a healthy lifestyle to prevent chronic diseases or mental disorders is a core societal challenge. The current global pandemic has evidenced more than ever before the critical importance of engaging citizens with healthy and tailored activities that they like, as a key driver for safeguarding good health from a preventive vantage point, aligned with the pursuance of SDG 3: "good health and well-being". This is why Recommender Systems for personalized health and well-being have lately become a research trend, particularly for food and physical activity recommendation. This paper presents F-EvoRecSys: an extension of an evolutionary algorithm-driven approach for "healthy bundle"well-being recommendations that incorporates a fuzzy inference engine aimed at improving physical activity recommendations based on users' exercising habits. An experimental study demonstrates how this can lead to more diversified recommendations. The paper also discusses challenges and future directions for personalized well-being recommender systems under different perspectives.
AB - Many citizens nowadays cope with busy and dynamic lifestyles. Adopting or maintaining a healthy lifestyle to prevent chronic diseases or mental disorders is a core societal challenge. The current global pandemic has evidenced more than ever before the critical importance of engaging citizens with healthy and tailored activities that they like, as a key driver for safeguarding good health from a preventive vantage point, aligned with the pursuance of SDG 3: "good health and well-being". This is why Recommender Systems for personalized health and well-being have lately become a research trend, particularly for food and physical activity recommendation. This paper presents F-EvoRecSys: an extension of an evolutionary algorithm-driven approach for "healthy bundle"well-being recommendations that incorporates a fuzzy inference engine aimed at improving physical activity recommendations based on users' exercising habits. An experimental study demonstrates how this can lead to more diversified recommendations. The paper also discusses challenges and future directions for personalized well-being recommender systems under different perspectives.
KW - Evolutionary algorithms
KW - Fuzzy inference
KW - Personalized health
KW - Recommender systems
UR - http://www.scopus.com/inward/record.url?scp=85123477715&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85123477715&partnerID=8YFLogxK
U2 - 10.1109/iFUZZY53132.2021.9605091
DO - 10.1109/iFUZZY53132.2021.9605091
M3 - Conference contribution
AN - SCOPUS:85123477715
T3 - 2021 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2021
BT - 2021 International Conference on Fuzzy Theory and Its Applications, iFUZZY 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 5 October 2021 through 8 October 2021
ER -
