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Situation Modeling and Visual Analytics for Decision Support in Sports
Högskolan i Skövde, Forskningscentrum för Informationsteknologi. Högskolan i Skövde, Institutionen för informationsteknologi. (Skövde Artificial Intelligence Lab (SAIL))
Högskolan i Skövde, Forskningscentrum för Informationsteknologi. Högskolan i Skövde, Institutionen för informationsteknologi. (Skövde Artificial Intelligence Lab (SAIL))ORCID-id: 0000-0003-2900-9335
2014 (engelsk)Inngår i: Proceedings of the 16th International Conference on Enterprise Information Systems: Volume 1 / [ed] Slimane Hammoudi, Leszek Maciaszek, José Cordeiro, SciTePress, 2014, s. 539-544Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

High performance is a goal in most sporting activities, for elite athletes as well as for recreational practitioners, and the process of measuring, evaluating and improving performance is one fundamental aspect to why people engage in sports. This is a complex process which possibly involves analyzing large amounts of heterogeneous data in order to apply actions that change important properties for improved outcome. The number of computer based decision support systems in the context of data analysis for performance improvement is scarce. In this position paper we briefly review the literature, and we propose the use of information fusion, situation modeling and visual analytics as suitable tools for supporting decision makers, ranging from recreational to elite, in the process of performance evaluation.

sted, utgiver, år, opplag, sider
SciTePress, 2014. s. 539-544
Emneord [en]
Sports, Decision Support, Situation Modeling, Visual Analytics, Information Fusion
HSV kategori
Forskningsprogram
Teknik; Skövde Artificial Intelligence Lab (SAIL)
Identifikatorer
URN: urn:nbn:se:his:diva-9101DOI: 10.5220/0004973105390544Scopus ID: 2-s2.0-84902355936ISBN: 978-989-758-027-7 (tryckt)OAI: oai:DiVA.org:his-9101DiVA, id: diva2:721124
Konferanse
16th International Conference on Enterprise Information Systems, Lisbon, Portugal, April 27-30, 2014
Prosjekter
Golf data analysis (GOATS)Tilgjengelig fra: 2014-06-03 Laget: 2014-05-22 Sist oppdatert: 2018-12-27bibliografisk kontrollert

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