Machine Learning and Data Mining for Sports Analytics: 7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings
Publikation: Bücher und Anthologien › Konferenzbände und -dokumentationen › Forschung
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Cham: Springer International Publishing, 2020. 146 S. (Communications in Computer and Information Science; Band 1324).
Publikation: Bücher und Anthologien › Konferenzbände und -dokumentationen › Forschung
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RIS
TY - BOOK
T1 - Machine Learning and Data Mining for Sports Analytics
T2 - 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020
A2 - Brefeld, Ulf
A2 - Davis, Jesse
A2 - van Haaren, Jan
A2 - Zimmermann, Albrecht
N1 - Conference code: 7
PY - 2020
Y1 - 2020
N2 - The Machine Learning and Data Mining for Sports Analytics (MLSA) workshop aims to bring people from outside of the Machine Learning and Data Mining community into contact with researchers from that community who are working on Sports Analytics.The 7th edition of the workshop was co-located with the European Conferenceon Machine Learning and Principles and Practice of Knowledge Discovery (ECMLPKDD 2020).Sports Analytics has been a steadily growing and rapidly evolving area over the last decade, both in US professional sports leagues and in European football leagues. The recent implementation of strict financial fair-play regulations in European football will definitely increase the importance of Sports Analytics in the coming years. In addition, there is the popularity of sports betting. The developed techniques are being used for decision support in all aspects of professional sports ...
AB - The Machine Learning and Data Mining for Sports Analytics (MLSA) workshop aims to bring people from outside of the Machine Learning and Data Mining community into contact with researchers from that community who are working on Sports Analytics.The 7th edition of the workshop was co-located with the European Conferenceon Machine Learning and Principles and Practice of Knowledge Discovery (ECMLPKDD 2020).Sports Analytics has been a steadily growing and rapidly evolving area over the last decade, both in US professional sports leagues and in European football leagues. The recent implementation of strict financial fair-play regulations in European football will definitely increase the importance of Sports Analytics in the coming years. In addition, there is the popularity of sports betting. The developed techniques are being used for decision support in all aspects of professional sports ...
KW - Business informatics
KW - artificial intelligence
KW - computer hardware
KW - computer systems
KW - Computer vision
KW - Correlation analysis
KW - data handling
KW - data integration
KW - databases
KW - Human-Computer Interaction (HCI)
KW - integrated data
KW - machine learning
KW - sensors
KW - user interfaces
UR - https://link.springer.com/book/10.1007%2F978-3-030-64912-8
UR - http://www.scopus.com/inward/record.url?scp=85098274957&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-64912-8
DO - 10.1007/978-3-030-64912-8
M3 - Conference proceedings
SN - 978-3-030-64911-1
T3 - Communications in Computer and Information Science
BT - Machine Learning and Data Mining for Sports Analytics
PB - Springer International Publishing
CY - Cham
Y2 - 14 September 2020 through 18 September 2020
ER -