DISCUSSION CONCERNING THE APPLICATION OF DATA MINING TECHNOLOGY IN SPORTS PERFORMANCE MANAGEMENT
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista brasileira de medicina do esporte (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-86922022000500460 |
Resumo: | ABSTRACT Introduction: Finding the factors that contribute to success in student performance or failure is necessary for every teacher. Data mining, which is already used in companies for management processes, can be essential in this research. Objective: Discuss the data mining algorithms application in sports performance management. Method: A database was developed considering seasonal factors, health benefit index, and sports behavior characteristics. The data were entered under fuzzy logic, processed, and analyzed in IBM SPSS Modeler Software. Decision-making efficiency was improved with the target base interpolation analysis and the C spatial noise reduction methods. The fidelity of sports behavior was consolidated under Gauss time series analysis. Results: The relationship between the mining algorithm to find the existing problems and the association results in the mining rules provided valuable information for improving health guidelines to the physical activity students. Conclusion: The original data from the educational system can be transformed into useful information through the association rules algorithm, and the relationship between the performance can be obtained, providing the improvement in the decision making for the benefit of the physical level of the students. Evidence Level II; Therapeutic Studies – Investigating the results. |
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DISCUSSION CONCERNING THE APPLICATION OF DATA MINING TECHNOLOGY IN SPORTS PERFORMANCE MANAGEMENTAthletic PerformanceAssociation RulesData MiningABSTRACT Introduction: Finding the factors that contribute to success in student performance or failure is necessary for every teacher. Data mining, which is already used in companies for management processes, can be essential in this research. Objective: Discuss the data mining algorithms application in sports performance management. Method: A database was developed considering seasonal factors, health benefit index, and sports behavior characteristics. The data were entered under fuzzy logic, processed, and analyzed in IBM SPSS Modeler Software. Decision-making efficiency was improved with the target base interpolation analysis and the C spatial noise reduction methods. The fidelity of sports behavior was consolidated under Gauss time series analysis. Results: The relationship between the mining algorithm to find the existing problems and the association results in the mining rules provided valuable information for improving health guidelines to the physical activity students. Conclusion: The original data from the educational system can be transformed into useful information through the association rules algorithm, and the relationship between the performance can be obtained, providing the improvement in the decision making for the benefit of the physical level of the students. Evidence Level II; Therapeutic Studies – Investigating the results.Sociedade Brasileira de Medicina do Exercício e do Esporte2022-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-86922022000500460Revista Brasileira de Medicina do Esporte v.28 n.5 2022reponame:Revista brasileira de medicina do esporte (Online)instname:Sociedade Brasileira de Medicina do Exercício e do Esporte (SBMEE)instacron:SBMEE10.1590/1517-8692202228052021_0519info:eu-repo/semantics/openAccessSong,Xiaojingeng2022-05-16T00:00:00Zoai:scielo:S1517-86922022000500460Revistahttp://www.scielo.br/rbmeONGhttps://old.scielo.br/oai/scielo-oai.php||revista@medicinadoesporte.org.br1806-99401517-8692opendoar:2022-05-16T00:00Revista brasileira de medicina do esporte (Online) - Sociedade Brasileira de Medicina do Exercício e do Esporte (SBMEE)false |
dc.title.none.fl_str_mv |
DISCUSSION CONCERNING THE APPLICATION OF DATA MINING TECHNOLOGY IN SPORTS PERFORMANCE MANAGEMENT |
title |
DISCUSSION CONCERNING THE APPLICATION OF DATA MINING TECHNOLOGY IN SPORTS PERFORMANCE MANAGEMENT |
spellingShingle |
DISCUSSION CONCERNING THE APPLICATION OF DATA MINING TECHNOLOGY IN SPORTS PERFORMANCE MANAGEMENT Song,Xiaojing Athletic Performance Association Rules Data Mining |
title_short |
DISCUSSION CONCERNING THE APPLICATION OF DATA MINING TECHNOLOGY IN SPORTS PERFORMANCE MANAGEMENT |
title_full |
DISCUSSION CONCERNING THE APPLICATION OF DATA MINING TECHNOLOGY IN SPORTS PERFORMANCE MANAGEMENT |
title_fullStr |
DISCUSSION CONCERNING THE APPLICATION OF DATA MINING TECHNOLOGY IN SPORTS PERFORMANCE MANAGEMENT |
title_full_unstemmed |
DISCUSSION CONCERNING THE APPLICATION OF DATA MINING TECHNOLOGY IN SPORTS PERFORMANCE MANAGEMENT |
title_sort |
DISCUSSION CONCERNING THE APPLICATION OF DATA MINING TECHNOLOGY IN SPORTS PERFORMANCE MANAGEMENT |
author |
Song,Xiaojing |
author_facet |
Song,Xiaojing |
author_role |
author |
dc.contributor.author.fl_str_mv |
Song,Xiaojing |
dc.subject.por.fl_str_mv |
Athletic Performance Association Rules Data Mining |
topic |
Athletic Performance Association Rules Data Mining |
description |
ABSTRACT Introduction: Finding the factors that contribute to success in student performance or failure is necessary for every teacher. Data mining, which is already used in companies for management processes, can be essential in this research. Objective: Discuss the data mining algorithms application in sports performance management. Method: A database was developed considering seasonal factors, health benefit index, and sports behavior characteristics. The data were entered under fuzzy logic, processed, and analyzed in IBM SPSS Modeler Software. Decision-making efficiency was improved with the target base interpolation analysis and the C spatial noise reduction methods. The fidelity of sports behavior was consolidated under Gauss time series analysis. Results: The relationship between the mining algorithm to find the existing problems and the association results in the mining rules provided valuable information for improving health guidelines to the physical activity students. Conclusion: The original data from the educational system can be transformed into useful information through the association rules algorithm, and the relationship between the performance can be obtained, providing the improvement in the decision making for the benefit of the physical level of the students. Evidence Level II; Therapeutic Studies – Investigating the results. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-10-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-86922022000500460 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-86922022000500460 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1517-8692202228052021_0519 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Medicina do Exercício e do Esporte |
publisher.none.fl_str_mv |
Sociedade Brasileira de Medicina do Exercício e do Esporte |
dc.source.none.fl_str_mv |
Revista Brasileira de Medicina do Esporte v.28 n.5 2022 reponame:Revista brasileira de medicina do esporte (Online) instname:Sociedade Brasileira de Medicina do Exercício e do Esporte (SBMEE) instacron:SBMEE |
instname_str |
Sociedade Brasileira de Medicina do Exercício e do Esporte (SBMEE) |
instacron_str |
SBMEE |
institution |
SBMEE |
reponame_str |
Revista brasileira de medicina do esporte (Online) |
collection |
Revista brasileira de medicina do esporte (Online) |
repository.name.fl_str_mv |
Revista brasileira de medicina do esporte (Online) - Sociedade Brasileira de Medicina do Exercício e do Esporte (SBMEE) |
repository.mail.fl_str_mv |
||revista@medicinadoesporte.org.br |
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1752122238938644480 |