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dc.contributor.authorJacobson, Kurt
dc.date.accessioned2014-08-07T14:46:05Z
dc.date.available2014-08-07T14:46:05Z
dc.date.issued2011
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/6020
dc.descriptionPhD
dc.descriptionThis work is copyright (c) 2010 Kurt Jacobson, and is licensed under the Creative Commons Attribution-Share Alike 3.0 Unported Licence. To view a copy of this licence, visit http://creativecommons.org/licenses/by-sa/3.0/ or send a letter to Creative Commons, 171 Second Street, Suite 300, San Francisco, California, 94105, USA.
dc.description.abstractConnections between music artists or songs provide a context and lineage for music and form the basis for recommendation, playlist generation, and general navigation of the musical universe. We examine the structure of the connections between music artists found on the web. It is shown that different methods of finding associations between artists yeild different net- work structures - the details of associations and how these associations are discovered impact the global structure of the artist network. This realization informs our associations framework - based on seman- tic web technologies and centered around a small RDF/OWL ontology that emphasizes the provenance and transparency of association statements. We develop the MuSim Similarity Ontology and show how, combined with the concepts of linked data, it can be used to create a distributed web-scale ecosystem for music similarity. The Similarity Ontology is evaluated against psychological models for similarity and shown to be flexible enough to accommodate each model examined. Several applications are developed based on the visualization of music artist network structures and the utilization of our associations framework along with other music-related linked data.en_US
dc.subjectElectronic Engineering
dc.titleConnections in Musicen_US
dc.typeThesisen_US
dc.rights.holderThe copyright of this thesis rests with the author and no quotation from it or information derived from it may be published without the prior written consent of the author.


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    Theses Awarded by Queen Mary University of London

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