Computational Intelligence in Sports: A Systematic Literature Review

October 30, 2018 Β· Declared Dead Β· πŸ› 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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