Paper Info
Title
Musical Track Popularity Mining Dataset
Abstract
Music Information Research requires access to real musical content in order to test efficiency and effectiveness of its methods as well as to compare developed methodologies on common data. Existing datasets do not address the research direction of musical track popularity that has recently received considerate attention. Existing sources of musical popularity do not provide easily manageable data and no standardised dataset exists. Accordingly, in this paper we present the Track Popularity Dataset (TPD) that provides different sources of popularity definition ranging from 2004 to 2014, a mapping between different track/author/album identification spaces that allows use of all different sources, information on the remaining, non popular, tracks of an album with a popular track, contextual similarity between tracks and ready for MIR use extracted features for both popular and non-popular audio tracks.
Year
DOI
Venue
2016
10.1007/978-3-319-44944-9_50
ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS, AIAI 2016
Field
DocType
Volume
World Wide Web,Information retrieval,Musical,Computer science,Popularity,Ranging,Test efficiency,Artificial intelligence,Application programming interface,Machine learning
Conference
475
ISSN
Citations 
PageRank 
1868-4238
1
0.36
References 
Authors
7
3
Name
Order
Citations
PageRank
Ioannis Karydis111518.95
Aggelos Gkiokas2354.64
Vassilios Katsouros37310.63