DISCUSSION CONCERNING THE APPLICATION OF DATA MINING TECHNOLOGY IN SPORTS PERFORMANCE MANAGEMENT

Detalhes bibliográficos
Autor(a) principal: Song,Xiaojing
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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spelling 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
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1517-8692202228052021_0519
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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)
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