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dc.contributor.author Porter, Alastair
dc.contributor.author Bogdanov, Dmitry
dc.contributor.author Serra, Xavier
dc.date.accessioned 2017-11-06T09:38:34Z
dc.date.available 2017-11-06T09:38:34Z
dc.date.issued 2016
dc.identifier.citation Porter A, Bogdanov D, Serra X. Mining metadata from the web for AcousticBrainz. In: 3rd International Workshop on Digital Libraries for Musicology; 2016 Aug 12; New York (NY). New York, NY: ACM; 2016. p. 53-6. DOI: 10.1145/2970044.2970048
dc.identifier.uri http://hdl.handle.net/10230/33142
dc.description Comunicació presentada al 3rd International Workshop on Digital Libraries for Musicology, celebrat el dia 12 d'agost de 2016 a Nova York.
dc.description.abstract Semantic annotations of music collections in digital libraries are important for organization and navigation of the collection. These annotations and their associated metadata are useful in many Music Information Retrieval tasks, and related fields in musicology. Music collections used in research are growing in size, and therefore it is useful to use semi-automatic means to obtain such annotations. We present software tools for mining metadata from the web for the purpose of annotating music collections. These tools expand on data present in the AcousticBrainz database, which contains software-generated analysis of music audio files. Using this tool we gather metadata and semantic information from a variety of sources including both community-based services such as MusicBrainz, Last.fm, and Discogs, and commercial databases including Itunes and AllMusic. The tool can be easily expanded to collect data from a new source, and is automatically updated when new items are added to AcousticBrainz. We extract genre annotations for recordings in AcousticBrainz using our tool and study the agreement between folksonomies and expert sources. We discuss the results and explore possibilities for future work.
dc.description.sponsorship This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688382.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher ACM Association for Computer Machinery
dc.relation.ispartof 3rd International Workshop on Digital Libraries for Musicology; 2016 Aug 12; New York (NY). New York, NY: ACM; 2016. p. 53-6.
dc.rights © 2016 Association for Computing Machinery
dc.title Mining metadata from the web for AcousticBrainz
dc.type info:eu-repo/semantics/conferenceObject
dc.identifier.doi http://dx.doi.org/10.1145/2970044.2970048
dc.subject.keyword Music information retrieval
dc.subject.keyword Databases
dc.subject.keyword Genre
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/688382
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/acceptedVersion


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