Abstract
The aim of this study is to support track and field athletes to keep their motivation. Our approach is based on collection, extraction, and visualization of athlete’s activities by using blog articles. We collect blog articles written by track and field athletes. We extract menus, quantity, and the detail of training menus from these articles. We use the hidden Markov model (HMM) to extract these data. We then visualize the training and record data as graphs and tables. We provide athletes with various graphs and tables such as the distance graph.
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Sano, M., Masuda, H., Yamada, K., Fukuhara, T. (2017). Motivating Track and Field Athletes by Visualizing Training Drills and Records: Extraction and Visualization of Activities of Athletes from Blog Articles. In: Salmon, P., Macquet, AC. (eds) Advances in Human Factors in Sports and Outdoor Recreation. Advances in Intelligent Systems and Computing, vol 496. Springer, Cham. https://doi.org/10.1007/978-3-319-41953-4_8
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DOI: https://doi.org/10.1007/978-3-319-41953-4_8
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