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Autor*innen: Haase, Jens; Brefeld, Ulf
Titel: Finding similar movements in positional data streams
Aus: ECML/PKDD (Hrsg.): Proceedings of the ECML/PKDD Workshop on Machine Learning and Data Mining for Sports Analytics (ECML/PKDD 2013), Prag: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2013 , S. 1-9
URL: http://www.kma.informatik.tu-darmstadt.de/fileadmin/user_upload/Group_KMA/kma_publications/paper_01.pdf
Dokumenttyp: 4. Beiträge in Sammelwerken; Tagungsband/Konferenzbeitrag/Proceedings
Sprache: Englisch
Schlagwörter: Algorithmus; Computerspiel; Computerunterstütztes Verfahren; Daten; Datenanalyse; Evaluation; Informatik
Abstract: In this paper, we study the problem of efficiently finding similar movements in positional data streams, given a query trajectory. Our approach is based on a translation-, rotation-, and scale-invariant representation of movements. Near- neighbours given a query trajectory are then efficiently computed using dynamic time warping and locality sensitive hashing. Empirically, we show the efficiency and accuracy of our approach on positional data streams recorded from a real soccer game.
DIPF-Abteilung: Informationszentrum Bildung