@article{ART002727756},
author={Ha-Young Lee and Ok-Ran Jeong},
title={A personalized exercise recommendation system using dimension reduction algorithms},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2021},
volume={26},
number={6},
pages={19-28},
doi={10.9708/jksci.2021.26.06.019}
TY - JOUR
AU - Ha-Young Lee
AU - Ok-Ran Jeong
TI - A personalized exercise recommendation system using dimension reduction algorithms
JO - Journal of The Korea Society of Computer and Information
PY - 2021
VL - 26
IS - 6
PB - The Korean Society Of Computer And Information
SP - 19
EP - 28
SN - 1598-849X
AB - Nowadays, interest in health care is increasing due to Coronavirus (COVID-19), and a lot of people are doing home training as there are more difficulties in using fitness centers and public facilities that are used together. In this paper, we propose a personalized exercise recommendation algorithm using personalized propensity information to provide more accurate and meaningful exercise recommendation to home training users. Thus, we classify the data according to the criteria for obesity with a k-nearest neighbor algorithm using personal information that can represent individuals, such as eating habits information and physical conditions. Furthermore, we differentiate the exercise dataset by the level of exercise activities. Based on the neighborhood information of each dataset, we provide personalized exercise recommendations to users through a dimensionality reduction algorithm (SVD) among model-based collaborative filtering methods.
Therefore, we can solve the problem of data sparsity and scalability of memory-based collaborative filtering recommendation techniques and we verify the accuracy and performance of the proposed algorithms.
KW - Health-care;Classification;Recommendation System;Personalized Method;Dimensionality reduction model;SVD
DO - 10.9708/jksci.2021.26.06.019
ER -
Ha-Young Lee and Ok-Ran Jeong. (2021). A personalized exercise recommendation system using dimension reduction algorithms. Journal of The Korea Society of Computer and Information, 26(6), 19-28.
Ha-Young Lee and Ok-Ran Jeong. 2021, "A personalized exercise recommendation system using dimension reduction algorithms", Journal of The Korea Society of Computer and Information, vol.26, no.6 pp.19-28. Available from: doi:10.9708/jksci.2021.26.06.019
Ha-Young Lee, Ok-Ran Jeong "A personalized exercise recommendation system using dimension reduction algorithms" Journal of The Korea Society of Computer and Information 26.6 pp.19-28 (2021) : 19.
Ha-Young Lee, Ok-Ran Jeong. A personalized exercise recommendation system using dimension reduction algorithms. 2021; 26(6), 19-28. Available from: doi:10.9708/jksci.2021.26.06.019
Ha-Young Lee and Ok-Ran Jeong. "A personalized exercise recommendation system using dimension reduction algorithms" Journal of The Korea Society of Computer and Information 26, no.6 (2021) : 19-28.doi: 10.9708/jksci.2021.26.06.019
Ha-Young Lee; Ok-Ran Jeong. A personalized exercise recommendation system using dimension reduction algorithms. Journal of The Korea Society of Computer and Information, 26(6), 19-28. doi: 10.9708/jksci.2021.26.06.019
Ha-Young Lee; Ok-Ran Jeong. A personalized exercise recommendation system using dimension reduction algorithms. Journal of The Korea Society of Computer and Information. 2021; 26(6) 19-28. doi: 10.9708/jksci.2021.26.06.019
Ha-Young Lee, Ok-Ran Jeong. A personalized exercise recommendation system using dimension reduction algorithms. 2021; 26(6), 19-28. Available from: doi:10.9708/jksci.2021.26.06.019
Ha-Young Lee and Ok-Ran Jeong. "A personalized exercise recommendation system using dimension reduction algorithms" Journal of The Korea Society of Computer and Information 26, no.6 (2021) : 19-28.doi: 10.9708/jksci.2021.26.06.019
