Computational Intelligence in Sports: A Systematic Literature Review

被引:13
|
作者
Bonidia, Robson P. [1 ]
Rodrigues, Luiz A. L. [2 ]
Avila-Santos, Anderson P. [3 ]
Sanches, Danilo S. [1 ]
Brancher, Jacques D. [2 ]
机构
[1] Fed Univ Technol CP UTFPR, Bioinformat Grad Program, Curitiba, Parana, Brazil
[2] State Univ Londrina UEL, Comp Sci Dept, Londrina, Parana, Brazil
[3] Natl Serv Ind Learning Parana SENAI, Technol Coll, Londrina, Parana, Brazil
关键词
D O I
10.1155/2018/3426178
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Recently, datamining 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 datamining potentials, besides motivating the scientific community to explore this timely and interesting topic.
引用
收藏
页数:13
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