Sports Big Data: Management, Analysis, Applications, and Challenges

被引:25
|
作者
Bai, Zhongbo [1 ]
Bai, Xiaomei [2 ]
机构
[1] Anshan Normal Univ, Sch Sports Sci, Anshan, Peoples R China
[2] Anshan Normal Univ, Ctr Comp, Anshan, Peoples R China
关键词
SOCIAL NETWORK ANALYSIS; PARTICIPATION; TAXONOMY; TEAM; IOT;
D O I
10.1155/2021/6676297
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
With the rapid growth of information technology and sports, analyzing sports information has become an increasingly challenging issue. Sports big data come from the Internet and show a rapid growth trend. Sports big data contain rich information such as athletes, coaches, athletics, and swimming. Nowadays, various sports data can be easily accessed, and amazing data analysis technologies have been developed, which enable us to further explore the value behind these data. In this paper, we first introduce the background of sports big data. Secondly, we review sports big data management such as sports big data acquisition, sports big data labeling, and improvement of existing data. Thirdly, we show sports data analysis methods, including statistical analysis, sports social network analysis, and sports big data analysis service platform. Furthermore, we describe the sports big data applications such as evaluation and prediction. Finally, we investigate representative research issues in sports big data areas, including predicting the athletes' performance in the knowledge graph, finding a rising star of sports, unified sports big data platform, open sports big data, and privacy protections. This paper should help the researchers obtaining a broader understanding of sports big data and provide some potential research directions.
引用
收藏
页数:11
相关论文
共 50 条
  • [41] Challenges to Engineering Management in the Big Data Era
    Shi, Yong
    FRONTIERS OF ENGINEERING MANAGEMENT, 2015, 2 (03) : 293 - 303
  • [42] RETRACTED: Visual Management of Sports Based on Intelligent Analysis of Big Data (Retracted Article)
    Yang, Danya
    Wang, Jianfang
    Liu, Longlong
    MOBILE INFORMATION SYSTEMS, 2022, 2022
  • [43] Big Data Analysis: Issues and Challenges
    Bhardwaj, Vibha
    Johari, Rahul
    2015 INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS, SIGNALS, COMMUNICATION AND OPTIMIZATION (EESCO), 2015,
  • [44] A SURVEY ON BIG DATA ANALYSIS AND CHALLENGES
    Parikh, Harshil
    Liu, Jiangjiang
    ICERI2015: 8TH INTERNATIONAL CONFERENCE OF EDUCATION, RESEARCH AND INNOVATION, 2015, : 4451 - 4460
  • [45] Big Data Analysis: trends & challenges
    Bergamaschi, Sonia
    2014 INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING & SIMULATION (HPCS), 2014, : 303 - 304
  • [46] Multisource Analysis of Big Data Technology: Accessing Data Sources for Teacher Management of Sports Training Institutions
    Wang, Yiting
    Yu, Le
    MOBILE INFORMATION SYSTEMS, 2022, 2022
  • [47] Big Data analysis of demand side management for Industrial IOT applications
    Kodidala, Venkata Shiva Sai Jaswanth
    Akkala, Sowmya
    Madupoju, Sanjay Kumar
    Dasara, Venkata Satya Sai Teja
    Juvvadi, Mounish
    Thangadurai, N.
    MATERIALS TODAY-PROCEEDINGS, 2021, 46 : 8313 - 8319
  • [48] Applications of Big Data Analytics Tools for Data Management
    Jamshidi M.
    Tannahill B.
    Ezell M.
    Yetis Y.
    Kaplan H.
    Jamshidi, Mo (moj@wacong.org), 1600, Springer Science and Business Media Deutschland GmbH (18): : 177 - 199
  • [49] Deep learning applications and challenges in big data analytics
    Najafabadi M.M.
    Villanustre F.
    Khoshgoftaar T.M.
    Seliya N.
    Wald R.
    Muharemagic E.
    Journal of Big Data, 2 (1)
  • [50] Big Data in mechanical research: Potentials, applications and challenges
    Yang Q.
    Meng S.
    Zhong Z.
    Xie W.
    Guo Z.
    Jin H.
    Zhang X.
    Meng, Songhe (mengsh@hit.edu.cn), 1600, Chinese Academy of Mechanics (50):