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Conference Papers Year : 2016

Musical Track Popularity Mining Dataset

Ioannis Karydis
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Aggelos Gkiokas
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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.
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Dates and versions

hal-01557622 , version 1 (06-07-2017)





Ioannis Karydis, Aggelos Gkiokas, Vassilis Katsouros. Musical Track Popularity Mining Dataset. 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2016, Thessaloniki, Greece. pp.562-572, ⟨10.1007/978-3-319-44944-9_50⟩. ⟨hal-01557622⟩
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