Content-based music recommendation based on user preference examples
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- dc.contributor.author Bogdanov, Dmitry
- dc.contributor.author Haro Berois, Martín
- dc.contributor.author Fuhrmann, Ferdinand
- dc.contributor.author Gómez Gutiérrez, Emilia, 1975-
- dc.contributor.author Herrera Boyer, Perfecto, 1964-
- dc.date.accessioned 2021-04-01T06:25:39Z
- dc.date.available 2021-04-01T06:25:39Z
- dc.date.issued 2010
- dc.description Comunicació presentada a: Workshop on Music Recommendation and Discovery 2010 (WOMRAD 2010) celebrat el 26 de setembre de 2010 a Barcelona, Espanya.
- dc.description.abstract Recommending relevant and novel music to a user is one of the central applied problems in music information research. In the present work we propose three content-based approaches to this task. Starting from an explicit set of music tracks provided by the user as evidence of his/her music preferences, we infer high-level semantic descriptors, covering different musical facets, such as genre, culture, moods, instruments, rhythm, and tempo. On this basis, two of the proposed approaches employ a semantic music similarity measure to generate recommendations. The third approach creates a probabilistic model of the user’s preference in the semantic domain. We evaluate these approaches against two recommenders using state-of-the-art timbral features, and two contextual baselines, one exploiting simple genre categories, the other using similarity information obtained from collaborative filtering. We conduct a listening experiment to assess familiarity, liking and further listening intentions for the provided recommendations. According to the obtained results, we found our semantic approaches to outperform the low-level timbral baselines together with the genre-based recommender. Though the proposed approaches could not reach a performance comparable to the involved collaborative filtering system, they yielded acceptable results in terms of successful novel recommendations. We conclude that the proposed semantic approaches are suitable for music discovery especially in the long tail.en
- dc.description.sponsorship This research has been partially funded by the FI Grant of Generalitat de Catalunya (AGAUR).
- dc.format.mimetype application/pdf
- dc.identifier.citation Bogdanov D, Haro M, Fuhrmann F, Gómez E, Herrera P. Content-based music recommendation based on user preference examples. In: Anglade A, Baccigalupo C, Casagrande N, Celma Ò, Lamere P, editors. Workshop on Music Recommendation and Discovery 2010 (WOMRAD 2010); 2010 Sep 26; Barcelona, Spain. Aachen: CEUR Workshop Proceedings; 2010. p. 33-8.
- dc.identifier.issn 1613-0073
- dc.identifier.uri http://hdl.handle.net/10230/47004
- dc.language.iso eng
- dc.publisher CEUR Workshop Proceedings
- dc.relation.ispartof Anglade A, Baccigalupo C, Casagrande N, Celma Ò, Lamere P, editors. Workshop on Music Recommendation and Discovery 2010 (WOMRAD 2010); 2010 Sep 26; Barcelona, Spain. Aachen: CEUR Workshop Proceedings; 2010. p. 33-8
- dc.rights This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 Unported (https://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri https://creativecommons.org/licenses/by/3.0/
- dc.subject.keyword Recommender systemsen
- dc.subject.keyword User modelingen
- dc.subject.keyword Evaluationen
- dc.subject.keyword Music recommendationen
- dc.subject.keyword Content-baseden
- dc.subject.keyword Collaborative filteringen
- dc.title Content-based music recommendation based on user preference examplesen
- dc.type info:eu-repo/semantics/conferenceObject
- dc.type.version info:eu-repo/semantics/publishedVersion