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

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 ambiguou...

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Detalles Bibliográficos
Autores: Font Corbera, Frederic, Serrà Julià, Joan, Serra, Xavier
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2014
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/35179
Acceso en línea:http://hdl.handle.net/10230/35179
http://dx.doi.org/10.1016/j.knosys.2014.06.003
Access Level:acceso abierto
Palabra clave:Collaborative tagging
Tag recommendation
User study
Folksonomy
Freesound
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spelling Class-based tag recommendation and user-based evaluation in online audio clip sharingFont Corbera, FredericSerrà Julià, JoanSerra, XavierCollaborative taggingTag recommendationUser studyFolksonomyFreesoundOnline 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.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.).Elsevier201820182014info:eu-repo/semantics/articleinfo:eu-repo/semantics/submittedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/35179http://dx.doi.org/10.1016/j.knosys.2014.06.003reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésKnowledge Based Systems. 2014;67:131-42.info:eu-repo/grantAgreement/EC/FP7/267583info:eu-repo/grantAgreement/ES/3PN/TIN2009-14247-C02-01© Elsevier http://dx.doi.org/10.1016/j.knosys.2014.06.003info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/351792026-06-12T07:21:37Z
dc.title.none.fl_str_mv Class-based tag recommendation and user-based evaluation in online audio clip sharing
title Class-based tag recommendation and user-based evaluation in online audio clip sharing
spellingShingle Class-based tag recommendation and user-based evaluation in online audio clip sharing
Font Corbera, Frederic
Collaborative tagging
Tag recommendation
User study
Folksonomy
Freesound
title_short Class-based tag recommendation and user-based evaluation in online audio clip sharing
title_full Class-based tag recommendation and user-based evaluation in online audio clip sharing
title_fullStr Class-based tag recommendation and user-based evaluation in online audio clip sharing
title_full_unstemmed Class-based tag recommendation and user-based evaluation in online audio clip sharing
title_sort Class-based tag recommendation and user-based evaluation in online audio clip sharing
dc.creator.none.fl_str_mv Font Corbera, Frederic
Serrà Julià, Joan
Serra, Xavier
author Font Corbera, Frederic
author_facet Font Corbera, Frederic
Serrà Julià, Joan
Serra, Xavier
author_role author
author2 Serrà Julià, Joan
Serra, Xavier
author2_role author
author
dc.subject.none.fl_str_mv Collaborative tagging
Tag recommendation
User study
Folksonomy
Freesound
topic Collaborative tagging
Tag recommendation
User study
Folksonomy
Freesound
description 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.
publishDate 2014
dc.date.none.fl_str_mv 2014
2018
2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/submittedVersion
format article
status_str submittedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/35179
http://dx.doi.org/10.1016/j.knosys.2014.06.003
url http://hdl.handle.net/10230/35179
http://dx.doi.org/10.1016/j.knosys.2014.06.003
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Knowledge Based Systems. 2014;67:131-42.
info:eu-repo/grantAgreement/EC/FP7/267583
info:eu-repo/grantAgreement/ES/3PN/TIN2009-14247-C02-01
dc.rights.none.fl_str_mv © Elsevier http://dx.doi.org/10.1016/j.knosys.2014.06.003
info:eu-repo/semantics/openAccess
rights_invalid_str_mv © Elsevier http://dx.doi.org/10.1016/j.knosys.2014.06.003
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositorio Digital de la UPF
instname:Universitat Pompeu Fabra
instname_str Universitat Pompeu Fabra
reponame_str Repositorio Digital de la UPF
collection Repositorio Digital de la UPF
repository.name.fl_str_mv
repository.mail.fl_str_mv
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