Building a Personalized Fitness Recommendation Application based on Sequential Information

Nowadays sports plays a very important role in the life of the human being and it allows to keep him healthy and make him always active. Sport is essential for people to have a healthy mind. However, the practice of a sport can have negative effects on the body and human health if it is practiced incorrectly or if it is not adapted to the body or the human health. This is why, in this paper, we have proposed a recommendations system that allows the selection of the right person to practice the right sport according to several factors such as heart rate, speed and size. The implementation was applied to the FitRec dataset with the help of SPARK tool, and the results show that the proposed method is capable of generating the appropriate training for different groups according to their information, where each group gets the appropriate training. The grouping of this data was done by the k-means method.

@article{Abdulaziz2021,
  title     = {Building a Personalized Fitness Recommendation Application based on Sequential Information},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {1},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Manal Abdulaziz and Bodor Al-motairy and Mona Al-ghamdi and Norah Al-qahtani},
  doi       = {10.14569/IJACSA.2021.0120173},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120173}
}