Visualizing music similarity: clustering and mapping 500 classical music composers

Patrick Georges and Ngoc Nguyen ()
Additional contact information
Ngoc Nguyen: Western Kentucky University

Scientometrics, 2019, vol. 120, issue 3, No 3, 975-1003

Abstract: Abstract This paper applies clustering techniques and multi-dimensional scaling (MDS) analysis to a 500 × 500 composers’ similarity/distance matrix. The objective is to visualize or translate the similarity matrix into dendrograms and maps of classical (European art) music composers. We construct dendrograms and maps for the Baroque, Classical, and Romantic periods, and a map that represents seven centuries of European art music in one single graph. Finally, we also use linear and non-linear canonical correlation analyses to identify variables underlying the dimensions generated by the MDS methodology.

Keywords: Mapping classical music composers; Similarity measures; Dendrograms; Hierarchical clustering; Multidimensional scaling; Canonical correlation; Music information retrieval (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s11192-019-03166-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:scient:v:120:y:2019:i:3:d:10.1007_s11192-019-03166-0

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-019-03166-0

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().