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dc.contributor.authorAbdallah, S
dc.contributor.authorBenetos, E
dc.contributor.authorGold, N
dc.contributor.authorHargreaves, S
dc.contributor.authorWeyde, T
dc.contributor.authorWolff, D
dc.date.accessioned2016-10-04T09:27:50Z
dc.date.issued2016-10-04
dc.date.issued2017-01-01
dc.date.submitted2016-08-25T12:33:13.440Z
dc.identifier.issn1556-4673
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/15701
dc.description.sponsorshipThis work was supported by the UK Arts and Humanities Research Council-funded projects ‘Digital Music Lab - Analysing Big Music Data’ (grant no. AH/L01016X/1) and ‘An Integrated AudioSymbolic Model of Music Similarity’ (grant no. AH/M002454/1). EB is supported by a UK Royal Academy of Engineering Research Fellowship (grant no. RF/128). SH is supported by an Engineering and Physical Sciences Research Council Platform Grant (grant no. EP/K009559/1)en_US
dc.publisherACM
dc.relation.ispartofACM Journal on Computing and Cultural Heritage
dc.rightsThis is a pre-copyedited, author-produced PDF of an article accepted for publication in Journal on Computing and Cultural Heritage following peer review.
dc.titleThe Digital Music Lab: A Big Data Infrastructure for Digital Musicology
dc.typeJournal Article
dc.rights.holder© 2016 ACM
dc.identifier.doi10.1145/2983918
dc.relation.isPartOfACM Journal on Computing and Cultural Heritage
dc.relation.isPartOfACM Journal on Computing and Cultural Heritage
pubs.issue1
pubs.organisational-group/Queen Mary University of London
pubs.organisational-group/Queen Mary University of London/Faculty of Science & Engineering
pubs.organisational-group/Queen Mary University of London/Faculty of Science & Engineering/Electronic Engineering and Computer Science - Staff
pubs.publication-statusPublished
pubs.publisher-urlhttp://jocch.acm.org/
pubs.volume10


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