Algorithms for time series comparison

Authors:
Jiří Fejfar;Arnošt Motyčka;Štěpán Filípek
Affiliations:
Faculty of Business and Economics, Mendel University in Brno, Department of Informatics, Brno, Czech Republic;Faculty of Business and Economics, Mendel University in Brno, Department of Informatics, Brno, Czech Republic;Faculty of Music, Janáček Academy of Music and Performing Arts, Brno, Czech Republic
Venue:
AICT'11 Proceedings of the 2nd international conference on Applied informatics and computing theory
Year:
2011

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Abstract

In this paper we compare results of four chosen algorithms suitable for the time series clustering. The comparison is made in sense of agreement between clustering results represented in a special form of confusion matrix (matching matrix). We use a musical data, specifically music excerpts volume development, as a time series instances. This musical characteristic is used in computer-aided tool for musical analysis developed by our group.