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Class-based tag recommendation and user-based evaluation in online audio clip sharing

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dc.contributor.author Font Corbera, Frederic
dc.contributor.author Serrà Julià, Joan
dc.contributor.author Serra, Xavier
dc.date.accessioned 2018-07-17T10:31:15Z
dc.date.available 2018-07-17T10:31:15Z
dc.date.issued 2014
dc.identifier.citation Font F, Serrà J, Serra X. Class-based tag recommendation and user-based evaluation in online audio clip sharing. Knowl Based Syst. 2014;67:131-42. DOI: 10.1016/j.knosys.2014.06.003
dc.identifier.issn 0950-7051
dc.identifier.uri http://hdl.handle.net/10230/35179
dc.description.abstract Online sharing platforms often rely on collaborative tagging systems for annotating content. In this way, users themselves annotate and describe the shared contents using textual labels, commonly called tags. These annotations typically suffer from a number of issues such as tag scarcity or ambiguous labelling. Hence, to minimise some of these issues, tag recommendation systems can be employed to suggest potentially relevant tags during the annotation process. In this work, we present a tag recommendation system and evaluate it in the context of an online platform for audio clip sharing. By exploiting domain-specific knowledge, the system we present is able to classify an audio clip among a number of predefined audio classes and to produce specific tag recommendations for the different classes. We perform an in-depth user-based evaluation of the recommendation method along with two baselines and a former version that we described in previous work. This user-based evaluation is further complemented with a prediction-based evaluation following standard information retrieval methodologies. Results show that the proposed tag recommendation method brings a statistically significant improvement over the previous method and the baselines. In addition, we report a number of findings based on the detailed analysis of user feedback provided during the evaluation process. The considered methods, when applied to real-world collaborative tagging systems, should serve the purpose of consolidating the tagging vocabulary and improving the quality of content annotations.
dc.description.sponsorship This work has been supported by BES-2010-037309 FPI from the Spanish Ministry of Science and Innovation (TIN2009-14247-C02-01; F.F.), 2009-SGR-1434 from Generalitat de Catalunya (J.S.), JAEDOC069/2010 from CSIC (J.S.), ICT-2011-8-318770 from the European Commission (J.S.), and FP7-2007-2013/ERC Grant Agreement 267583 (CompMusic; F.F., X.S.).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Elsevier
dc.relation.ispartof Knowledge Based Systems. 2014;67:131-42.
dc.rights © Elsevier http://dx.doi.org/10.1016/j.knosys.2014.06.003
dc.title Class-based tag recommendation and user-based evaluation in online audio clip sharing
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1016/j.knosys.2014.06.003
dc.subject.keyword Collaborative tagging
dc.subject.keyword Tag recommendation
dc.subject.keyword User study
dc.subject.keyword Folksonomy
dc.subject.keyword Freesound
dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/267583
dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/TIN2009-14247-C02-01
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/submittedVersion

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