Machine Learning and Data Mining for Sports Analytics: 5th International Workshop, MLSA 2018, colocated with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings

Ulf Brefeld; Jesse Davis; Jan Van Haaren; Albrecht Zimmermann

doi:10.1007/978-3-030-17274-9

Machine Learning and Data Mining for Sports Analytics: 5th International Workshop, MLSA 2018, colocated with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings

Ulf Brefeld (Herausgeber*in)
, Jesse Davis (Herausgeber*in)
, Jan Van Haaren (Herausgeber*in)
, Albrecht Zimmermann (Herausgeber*in)

Professur für Wirtschaftsinformatik, insbesondere Machine Learning

Publikation: Bücher und Anthologien › Sammelwerke und Anthologien › Forschung

Abstract

This book constitutes the refereed post-conference proceedings of the 5th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2018, colocated with ECML/PKDD 2018, in Dublin, Ireland, in September 2018.
The 12 full papers presented together with 4 challenge papers were carefully reviewed and selected from 24 submissions. The papers present a variety of topics, covering the team sports American football, basketball, ice hockey, and soccer, as well as the individual sports cycling and martial arts. In addition, four challenge papers are included, reporting on how to predict pass receivers in soccer.

Originalsprache	Englisch

Verlag	Springer Nature
Band	11330
Seitenumfang	179
ISBN (Print)	978-3-030-17273-2
ISBN (elektronisch)	978-3-030-17274-9
DOIs	https://doi.org/10.1007/978-3-030-17274-9
Publikationsstatus	Erschienen - 05.04.2019

Publikationsreihe

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band	11330 LNAI
ISSN (Druck)	0302-9743
ISSN (elektronisch)	1611-3349

Bibliographische Notiz

DOI 10.1007/978-3-030-17274-9
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG

Fachgebiete und Schlagwörter

Informatik
Wirtschaftsinformatik

Zugriff auf Dokument

10.1007/978-3-030-17274-9

Dieses zitieren

Brefeld, U., Davis, J., Van Haaren, J., & Zimmermann, A. (Hrsg.) (2019). Machine Learning and Data Mining for Sports Analytics: 5th International Workshop, MLSA 2018, colocated with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 11330 LNAI). Springer Nature. https://doi.org/10.1007/978-3-030-17274-9

Brefeld, Ulf (Herausgeber*in) ; Davis, Jesse (Herausgeber*in) ; Van Haaren, Jan (Herausgeber*in) et al. / Machine Learning and Data Mining for Sports Analytics : 5th International Workshop, MLSA 2018, colocated with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings. Springer Nature, 2019. 179 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@book{5fbf785cc3e449a6b7733972cc199bb8,

title = "Machine Learning and Data Mining for Sports Analytics: 5th International Workshop, MLSA 2018, colocated with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings",

abstract = "This book constitutes the refereed post-conference proceedings of the 5th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2018, colocated with ECML/PKDD 2018, in Dublin, Ireland, in September 2018. The 12 full papers presented together with 4 challenge papers were carefully reviewed and selected from 24 submissions. The papers present a variety of topics, covering the team sports American football, basketball, ice hockey, and soccer, as well as the individual sports cycling and martial arts. In addition, four challenge papers are included, reporting on how to predict pass receivers in soccer.",

keywords = "Informatics, artificial intelligence, classification accuracy, classification algorithm, data mining, learning algorithms, machine learning, neural networks, pattern recognition, regression analysis, reinforcement learning, Support Vector Machines (SVM), tree structures, Business informatics",

editor = "Ulf Brefeld and Jesse Davis and \{Van Haaren\}, Jan and Albrecht Zimmermann",

note = "DOI 10.1007/978-3-030-17274-9 Publisher Springer International Publishing Copyright Holder Springer Nature Switzerland AG",

year = "2019",

month = apr,

day = "5",

doi = "10.1007/978-3-030-17274-9",

language = "English",

isbn = "978-3-030-17273-2",

volume = "11330",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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}

Brefeld, U, Davis, J, Van Haaren, J & Zimmermann, A (Hrsg.) 2019, Machine Learning and Data Mining for Sports Analytics: 5th International Workshop, MLSA 2018, colocated with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Bd. 11330 LNAI, Bd. 11330, Springer Nature. https://doi.org/10.1007/978-3-030-17274-9

Machine Learning and Data Mining for Sports Analytics: 5th International Workshop, MLSA 2018, colocated with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings. / Brefeld, Ulf (Herausgeber*in); Davis, Jesse (Herausgeber*in); Van Haaren, Jan (Herausgeber*in) et al.
Springer Nature, 2019. 179 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 11330 LNAI).

Publikation: Bücher und Anthologien › Sammelwerke und Anthologien › Forschung

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T2 - 5th International Workshop, MLSA 2018, colocated with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings

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AB - This book constitutes the refereed post-conference proceedings of the 5th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2018, colocated with ECML/PKDD 2018, in Dublin, Ireland, in September 2018. The 12 full papers presented together with 4 challenge papers were carefully reviewed and selected from 24 submissions. The papers present a variety of topics, covering the team sports American football, basketball, ice hockey, and soccer, as well as the individual sports cycling and martial arts. In addition, four challenge papers are included, reporting on how to predict pass receivers in soccer.

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KW - artificial intelligence

KW - classification accuracy

KW - classification algorithm

KW - data mining

KW - learning algorithms

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KW - neural networks

KW - pattern recognition

KW - regression analysis

KW - reinforcement learning

KW - Support Vector Machines (SVM)

KW - tree structures

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Brefeld U, (ed.), Davis J, (ed.), Van Haaren J, (ed.), Zimmermann A, (ed.). Machine Learning and Data Mining for Sports Analytics: 5th International Workshop, MLSA 2018, colocated with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings. Springer Nature, 2019. 179 S. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-17274-9

Machine Learning and Data Mining for Sports Analytics: 5th International Workshop, MLSA 2018, colocated with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings

Abstract

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