Show simple item record

dc.contributor.authorAbdallah, Sen_US
dc.contributor.authorBenetos, Een_US
dc.contributor.authorGold, Nen_US
dc.contributor.authorHargreaves, Sen_US
dc.contributor.authorWeyde, Ten_US
dc.contributor.authorWolff, Den_US
dc.date.accessioned2016-10-04T09:27:50Z
dc.date.available2016-08-05en_US
dc.date.issued2017-04en_US
dc.date.submitted2016-08-25T12:33:13.440Z
dc.identifier.issn1556-4673en_US
dc.identifier.otherARTN 2en_US
dc.identifier.otherARTN 2en_US
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.relation.ispartofACM JOURNAL ON COMPUTING AND CULTURAL HERITAGEen_US
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.subjectDigital musicologyen_US
dc.subjectmusic information retrievalen_US
dc.subjectbig dataen_US
dc.subjectsemantic weben_US
dc.titleThe Digital Music Lab: A Big Data Infrastructure for Digital Musicologyen_US
dc.typeArticle
dc.rights.holder© 2016 ACM
dc.identifier.doi10.1145/2983918en_US
pubs.author-urlhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000399736000004&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=612ae0d773dcbdba3046f6df545e9f6aen_US
pubs.issue1en_US
pubs.notesNo embargoen_US
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.organisational-group/Queen Mary University of London/REF
pubs.organisational-group/Queen Mary University of London/REF/REF - UoA 11
pubs.publication-statusPublisheden_US
pubs.volume10en_US
qmul.funderA Machine Learning Framework for Audio Analysis and Retrieval::Royal Academy of Engineeringen_US
qmul.funderA Machine Learning Framework for Audio Analysis and Retrieval::Royal Academy of Engineeringen_US
qmul.funderA Machine Learning Framework for Audio Analysis and Retrieval::Royal Academy of Engineeringen_US
qmul.funderA Machine Learning Framework for Audio Analysis and Retrieval::Royal Academy of Engineeringen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record