Music retagging using label propagation and robust principal component analysis

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• dc.contributor.author Yang, Yi-Hsuan
• dc.contributor.author Bogdanov, Dmitry
• dc.contributor.author Herrera Boyer, Perfecto, 1964-
• dc.contributor.author Sordo, Mohamed
• dc.date.accessioned 2021-04-01T06:25:52Z
• dc.date.available 2021-04-01T06:25:52Z
• dc.date.issued 2012
• dc.description Comunicació presentada a: WWW'12 Companion: The 21st International Conference on World Wide Web celebrat del 16 al 20 d'abril de 2012 a Lió, França.
• dc.description.abstract The emergence of social tagging websites such as Last.fm has provided new opportunities for learning computational models that automatically tag music. Researchers typically obtain music tags from the Internet and use them to construct machine learning models. Nevertheless, such tags are usually noisy and sparse. In this paper, we present a preliminary study that aims at refining (retagging) social tags by exploiting the content similarity between tracks and the semantic redundancy of the track-tag matrix. The evaluated algorithms include a graph-based label propagation method that is often used in semi-supervised learning and a robust principal component analysis (PCA) algorithm that has led to state-of-the-art results in matrix completion. The results indicate that robust PCA with content similarity constraint is particularly effective; it improves the robustness of tagging against three types of synthetic errors and boosts the recall rate of music auto-tagging by 7% in a real-world setting.en
• dc.description.sponsorship This work was supported by a grant from the National Science Council of Taiwan under contract NSC 100-2218-E001-009 and partially supported by the following projects: Classical Planet: TSI-070100-2009-407 (MITYC), DRIMS: TIN2009-14247-C02-01 (MICINN) and MIRES: EC-FP7 ICT2011.1.5 Networked Media and Search Systems, grant agreement No. 287711.
• dc.format.mimetype application/pdf
• dc.identifier.citation Yang YH, Bogdanov D, Herrera P, Sordo M. Music retagging using label propagation and robust principal component analysis. In: WWW'12 Companion: Proceedings of the 21st International Conference on World Wide Web; 2012 Apr 16-20; Lyon, France. New York: Association for Computing Machinery; 2012. p. 869-76. DOI: 10.1145/2187980.2188217
• dc.identifier.doi http://dx.doi.org/10.1145/2187980.2188217
• dc.identifier.uri http://hdl.handle.net/10230/47007
• dc.language.iso eng
• dc.publisher ACM Association for Computer Machinery
• dc.relation.ispartof WWW'12 Companion: Proceedings of the 21st International Conference on World Wide Web; 2012 Apr 16-20; Lyon, France. New York: Association for Computing Machinery; 2012. p. 869-76
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/TIN2009-14247-C02-01
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/287711
• dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/TSI-070100-2009-407
• dc.rights © 2012 Association for Computing Machinery
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.title Music retagging using label propagation and robust principal component analysisen
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/acceptedVersion