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Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Mining Sport Activities

Mining Sport Activities
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Author(s): Iztok Fister Jr. (University of Maribor, Slovenia) and Iztok Fister (University of Maribor, Slovenia)
Copyright: 2018
Pages: 10
Source title: Encyclopedia of Information Science and Technology, Fourth Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-2255-3.ch639

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Abstract

For many people, sport is one of the stress relieving activity. People being involved with sport wish to achieve: attractive shape, healthy lifestyle, lose weights, and so on. However, there are also people who deal with sport because of competition goals. In order to fulfill their competition goals, they need to train properly. Even for professionals, it is very hard to perform a serious training. On the other hand, recent expansion of smart sport watches and even smart phones allow athletes to train smarter. During the months and years, they produce dozens of activity files. These files offer a thousands opportunities for data mining approaches, where athletes gained a deep insight in their training data. Data mining approaches are able to extract habits of athletes, help to prevent over-training syndrome and injuries, clustering similar activities together, and much more. In this chapter, we show opportunities for data mining, enumerate recent applications and outline future potentials for research and applications in real-world.

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