Computational Intelligence in Sports: A Systematic Literature Review
October 30, 2018 Β· Declared Dead Β· π Adv. Hum. Comput. Interact.
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Authors
Robson P. Bonidia, Luiz A. L. Rodrigues, Anderson P. Avila-Santos, Danilo S. Sanches, Jacques D. Brancher
arXiv ID
1810.12850
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.CY
Citations
23
Venue
Adv. Hum. Comput. Interact.
Last Checked
4 months ago
Abstract
Recently, data mining studies are being successfully conducted to estimate several parameters in a variety of domains. Data mining techniques have attracted the attention of the information industry and society as a whole, due to a large amount of data and the imminent need to turn it into useful knowledge. However, the effective use of data in some areas is still under development, as is the case in sports, which in recent years, has presented a slight growth; consequently, many sports organizations have begun to see that there is a wealth of unexplored knowledge in the data extracted by them. Therefore, this article presents a systematic review of sports data mining. Regarding years 2010 to 2018, 31 types of research were found in this topic. Based on these studies, we present the current panorama, themes, the database used, proposals, algorithms, and research opportunities. Our findings provide a better understanding of the sports data mining potentials, besides motivating the scientific community to explore this timely and interesting topic.
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