Data Mining in Sports: A Systematic Review

Bonidia, Robson Parmezan; Brancher, Jacques Duílio; Busto, Rosângela Marques

doi:10.1109/tla.2018.8291478

Cited by 26 publications

(5 citation statements)

References 31 publications

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“…IoT is widely used in remote antitheft, highway nonstop charging, intelligent library, and remote power meter reading, which promote the application of IoT in other fields. Based on IoT, the intelligent development of transportation, security, monitoring, and logistics, and intelligent control of household appliances are realized through the huge network connected with different objects [ 16 ]. However, there are still many problems to be solved in expanding the application of IoT because it is a product that appeared in the development of information technology.…”

Section: Methodsmentioning

confidence: 99%

Physical Education Teaching Strategy under Internet of Things Data Computing Intelligence Analysis

Zhang

Hou

2022

Computational Intelligence and Neuroscience

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Racket sports such as tennis are amongst the most popular recreational sports activities. Optimizing tennis teaching methods and improving teaching modes can effectively improve the teaching quality of tennis. In this study, a video and image action recognition system based on image processing techniques and Internet of things is developed to overcome the shortcomings of the traditional tennis teaching methods. To validate its performance, the students of tennis courses are divided into experimental group and control group, respectively. The control group is taught by using the traditional tennis teaching method whereas the experimental group is taught by using the IoT video and image recognition teaching system. Three factors of students including service throwing height, arm elbow angle, and knee bending angles of both groups are measured and compared with those of world elite tennis players. The results show that the students’ serving abilities in the experimental group are significantly improved using the video and image recognition system based on IoT, and they are better than those of the students in the control group. The proposed video and image processing technique can be applied in students’ physical education and can be employed to provide the basis for the innovation of tennis teaching strategies in physical education.

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Section: Methodsmentioning

confidence: 99%

Physical Education Teaching Strategy under Internet of Things Data Computing Intelligence Analysis

Zhang

Hou

2022

Computational Intelligence and Neuroscience

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“…This sort of inspection provides the overview of evidence with the help of coherent systematic search techniques and the synthesis of elected records [ 18 ]. Furthermore, this method has been extensively used in [ 17 – 20 ]. However, our work is established on the ground of earlier literature, which describes that the process should be classified into three phases: First is planning, second is conducting and third is an analysis of results.…”

Section: Systematic Review Methodologymentioning

confidence: 99%

“…The planning phase discussed the scientific research questions definition, identification of databases, definition of keywords, searching techniques, standards for include & exclude, and quality of article [ 17 – 20 ]. Thus, the following research questions (RQn) were identified on the basis of challenges:…”

Section: Research Planningmentioning

confidence: 99%

A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection

Pervaiz

Ul-Qayyum

Bangyal

et al. 2021

Computational and Mathematical Methods in Medicine

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Artificial Intelligence (AI) is the domain of computer science that focuses on the development of machines that operate like humans. In the field of AI, medical disease detection is an instantly growing domain of research. In the past years, numerous endeavours have been made for the improvements of medical disease detection, because the errors and problems in medical disease detection cause serious wrong medical treatment. Meta-heuristic techniques have been frequently utilized for the detection of medical diseases and promise better accuracy of perception and prediction of diseases in the domain of biomedical. Particle Swarm Optimization (PSO) is a swarm-based intelligent stochastic search technique encouraged from the intrinsic manner of bee swarm during the searching of their food source. Consequently, for the versatility of numerical experimentation, PSO has been mostly applied to address the diverse kinds of optimization problems. However, the PSO techniques are frequently adopted for the detection of diseases but there is still a gap in the comparative survey. This paper presents an insight into the diagnosis of medical diseases in health care using various PSO approaches. This study presents to deliver a systematic literature review of current PSO approaches for knowledge discovery in the field of disease detection. The systematic analysis discloses the potential research areas of PSO strategies as well as the research gaps, although, the main goal is to provide the directions for future enhancement and development in this area. This paper gives a systematic survey of this conceptual model for the advanced research, which has been explored in the specified literature to date. This review comprehends the fundamental concepts, theoretical foundations, and conventional application fields. It is predicted that our study will be beneficial for the researchers to review the PSO algorithms in-depth for disease detection. Several challenges that can be undertaken to move the field forward are discussed according to the current state of the PSO strategies in health care.

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“…Cui and Yoon proposed a decision tree data extraction method that combines this algorithm with the SLIQ algorithm and applies it to a database of student grades to analyse various data and build a decision tree model through analysis [ 17 ]. Parmezan et al proposed a teacher teaching quality assessment questionnaire that includes nine dimensions such as teaching quality, value of learning, enthusiasm for teaching, teaching organization and clarity, group interaction, interpersonal harmony, breadth of knowledge, examinations and test scores, homework, and other reading materials [ 18 ]. Zhang et al conducted an in-depth study on mining techniques and proposed the ID3 algorithm to manage the university faculty-related data was extracted and analysed to discover correlations between various course environments with a view to providing data university decision reference [ 19 ].…”

Section: Related Workmentioning

confidence: 99%

Design of Teaching Quality Analysis and Management System for PE Courses Based on Data-Mining Algorithm

Luo

2022

Computational Intelligence and Neuroscience

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Advances in network technology have led to extensive information technology construction work in all walks of life; universities, as a key component of national development, cannot be overlooked in this regard. In today’s universities, the Web-based integrated academic management information system is widely used, promoting higher education management system innovation and improving the management level of education departments and teaching management. The traditional management mode is incapable of locating “knowledge” in the mountains of student transcripts, and the original management mode must be improved. In business, finance, insurance, marketing, and other fields, digital exploration technology is widely used. This article describes the design approach for a data mining-based analysis and management system for PE course teaching quality, as well as the application of information technology and data mining technology in PE by combining actual PE teaching in schools, with the goal of realizing a data mining-based PE performance management system to serve PE teaching in schools and improve PE teaching quality. The results show that the time required to find frequent itemsets using a traditional algorithm running on a single machine, as well as the time required to scan the database several times for frequent itemset search in a distributed cluster of 20 computing nodes, is significantly longer than that required by the data mining algorithm. As a result, the proposed sports performance management system is functional, simple, and scalable, with each functional module operating independently and cooperatively, reflecting the concept of “high cohesion and low coupling.”

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Data Mining in Sports: A Systematic Review

Cited by 26 publications

References 31 publications

Physical Education Teaching Strategy under Internet of Things Data Computing Intelligence Analysis

Physical Education Teaching Strategy under Internet of Things Data Computing Intelligence Analysis

A Systematic Literature Review on Particle Swarm Optimization Techniques for Medical Diseases Detection

Design of Teaching Quality Analysis and Management System for PE Courses Based on Data-Mining Algorithm

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