%0 Conference Proceedings
%T Musical Track Popularity Mining Dataset
%+ Ionian University [Corfu]
%+ Institute for Language and Speech Processing (ILSP)
%A Karydis, Ioannis
%A Gkiokas, Aggelos
%A Katsouros, Vassilis
%Z Part 10: Mining Humanistic Data Workshop (MHDW)
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 12th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI)
%C Thessaloniki, Greece
%Y Lazaros Iliadis
%Y Ilias Maglogiannis
%3 Artificial Intelligence Applications and Innovations
%V AICT-475
%P 562-572
%8 2016-09-16
%D 2016
%R 10.1007/978-3-319-44944-9_50
%Z Computer Science [cs]Conference papers
%X 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.
%G English
%Z TC 12
%Z WG 12.5
%2 https://inria.hal.science/hal-01557622/document
%2 https://inria.hal.science/hal-01557622/file/430537_1_En_50_Chapter.pdf
%L hal-01557622
%U https://inria.hal.science/hal-01557622
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC12
%~ IFIP-AIAI
%~ IFIP-WG12-5
%~ IFIP-AICT-475