<div class="csl-bib-body">
<div class="csl-entry">Ferraro, A., Porcaro, L., Knees, P., & Bauer, C. (2024). MuRS 2024: 2nd Music Recommender Systems Workshop. In T. Di Noia, P. Lops, T. Joachims, K. Verbert, P. Castells, Z. Dong, & B. London (Eds.), <i>RecSys ’24: Proceedings of the 18th ACM Conference on Recommender Systems</i> (pp. 1202–1205). Association for Computing Machinery. https://doi.org/10.1145/3640457.3687097</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/210045
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dc.description.abstract
Music recommendation has been relevant to the Recommender Systems (RecSys) community since the early days. With the growth of music streaming platforms, algorithmic recommendations have become critical in the music industry. However, many challenges are still wide open in the area of music recommender systems. Such challenges are currently being addressed in several research communities, including and beyond the RecSys and the Music Information Retrieval (MIR) communities. The RecSys conference has traditionally not focused very much on music content understanding. In contrast, while music content understanding is central to the MIR community, research on recommender systems is not prominent in MIR research. The Music Recommender Systems Workshop (MuRS) aims at bridging the existing gap between the diverse research communities focused on the specific challenges of music recommender systems. The workshop provides a space for researchers and practitioners from multiple disciplines to jointly discuss and exchange perspectives and solutions, and to promote discussion from both academia and industry upon future research directions in the area of music recommender systems.
en
dc.description.sponsorship
FWF - Österr. Wissenschaftsfonds
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dc.language.iso
en
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dc.subject
music information retrieval
en
dc.subject
music recommender systems
en
dc.subject
music streaming
en
dc.title
MuRS 2024: 2nd Music Recommender Systems Workshop
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.relation.isbn
979-8-4007-0505-2
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dc.description.startpage
1202
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dc.description.endpage
1205
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dc.relation.grantno
P 33526-N
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
RecSys '24: Proceedings of the 18th ACM Conference on Recommender Systems
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tuw.peerreviewed
true
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tuw.relation.publisher
Association for Computing Machinery
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tuw.relation.publisherplace
New York
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tuw.project.title
Empfehlungssystem & Nutzer: Hin zu gegenseitigem Verständnis
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tuw.researchTopic.id
I4
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tuw.researchTopic.name
Information Systems Engineering
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E194-04 - Forschungsbereich Data Science
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tuw.publisher.doi
10.1145/3640457.3687097
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dc.description.numberOfPages
4
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tuw.author.orcid
0000-0003-1236-2503
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tuw.author.orcid
0000-0003-0218-5187
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tuw.author.orcid
0000-0003-3906-1292
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tuw.author.orcid
0000-0001-5724-1137
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tuw.editor.orcid
0000-0002-0939-5462
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tuw.editor.orcid
0000-0002-6866-9451
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tuw.editor.orcid
0000-0003-3654-3683
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tuw.editor.orcid
0000-0001-6699-7710
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tuw.editor.orcid
0000-0003-0668-6317
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tuw.editor.orcid
0009-0001-9515-5456
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tuw.event.name
RecSys '24: 18th ACM Conference on Recommender Systems
en
tuw.event.startdate
14-10-2024
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tuw.event.enddate
18-10-2024
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tuw.event.online
Hybrid
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tuw.event.type
Event for scientific audience
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tuw.event.place
Bari
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tuw.event.country
IT
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tuw.event.presenter
Ferraro, Andres
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tuw.event.presenter
Porcaro, Lorenzo
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tuw.event.presenter
Knees, Peter
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tuw.event.presenter
Bauer, Christine
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tuw.event.track
Single Track
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wb.sciencebranch
Informatik
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wb.sciencebranch
Wirtschaftswissenschaften
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
5020
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wb.sciencebranch.value
90
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10
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http://purl.org/coar/resource_type/c_5794
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Publications
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en
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no Fulltext
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conference paper
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crisitem.author.dept
E194-04 - Forschungsbereich Data Science
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crisitem.author.orcid
0000-0003-1236-2503
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0000-0003-0218-5187
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E194 - Institut für Information Systems Engineering