Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Òscar Celma"'
Publikováno v:
Recercat. Dipósit de la Recerca de Catalunya
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Music folksonomies include both general and detailed descriptions of music, and are usually continuously updated. These are significant advantages over music taxonomies, which tend to be incomplete and inconsistent. However, music folksonomies have a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::58bd0d86f257c18709e0429223a7f7ac
https://doi.org/10.1080/09298215.2013.848904
https://doi.org/10.1080/09298215.2013.848904
Autor:
Òscar Celma
Publikováno v:
RecSys
Were The Rolling Stones right when they said, "You can't always get what you want; but if you try sometime you get what you need"? Recommendation systems are the crystal ball of the Internet: predicting user intentions, making sense of big data, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a848264f5bee66b575b2e24a2f957aed
https://doi.org/10.1145/2959100.2959122
https://doi.org/10.1145/2959100.2959122
Publikováno v:
International Journal of Bifurcation and Chaos. 19:755-763
In the present work, algorithms based on complex network theory are applied to Recommendation Systems in order to improve their quality of predictions. We show how some networks are grown under the influence of trendy forces, and how this can be used
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba8777f80f2b039424c8837a6df56349
https://doi.org/10.1142/s0218127409023123
https://doi.org/10.1142/s0218127409023123
Autor:
Prockup, Matthew, Ehmann, Andreas F., Gouyon, Fabien, Schmidt, Erik M., Òscar Celma, Youngmoo E. Kim
[TODO] Add abstract here.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd538057c19b91cc4f73b51da1bb534a
Publikováno v:
Proceedings of the 21st International Conference on World Wide Web.
Music information research (MIR) has been a fast growing field of research during the past decade. In traditional MIR, music-related information were extracted from the audio signal using signal processing techniques. These methods, however, cannot c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::53fa872c9abb4ac244d6e89ad718c633
https://doi.org/10.1145/3259172
https://doi.org/10.1145/3259172
Publikováno v:
RecSys
The world of music is changing rapidly. We are now just a few clicks away from being able to listen to nearly any song that has ever been recorded. This easy access to a nearly endless supply of music is changing how we explore, discover, share and e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fdcf325fd46f1451fb89a88a849f699e
https://doi.org/10.1145/2043932.2044013
https://doi.org/10.1145/2043932.2044013
Autor:
Paul Lamere, Òscar Celma
Publikováno v:
RecSys
The world of music is changing rapidly. We are now just a few clicks away from being able to listen to nearly any song that has ever been recorded. This easy access to a nearly endless supply of music is changing how we explore, discover, share and e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60c6a13b1ec9c117140e5accf5a36dd6
https://doi.org/10.1145/2043932.2043936
https://doi.org/10.1145/2043932.2043936
Publikováno v:
Multimedia Semantics
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f840de101e3ddb368513ffb4512eabab
https://doi.org/10.1002/9781119970231.ch2
https://doi.org/10.1002/9781119970231.ch2
Publikováno v:
RecSys
This is the workshop report for WOMRAD 2010, the Workshop on Music Recommendation and Discovery held on 26th September 2010 in conjunction with ACM RecSys in Barcelona Spain.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::693c10ef0834aab269967c78433e894f
https://doi.org/10.1145/1864708.1864799
https://doi.org/10.1145/1864708.1864799
Autor:
Òscar Celma
Publikováno v:
Music Recommendation and Discovery ISBN: 9783642132865
Up to now, we have presented a user agnostic network-based analysis of the recommendations. In this chapter we present a user-centric evaluation of the recommender algorithms. This user-based approach focuses on evaluating the user’s perceived qual
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a975d577edb38e3dcdeefb898a19be76
https://doi.org/10.1007/978-3-642-13287-2_7
https://doi.org/10.1007/978-3-642-13287-2_7