Mañana, JUEVES, 24 DE ABRIL, el sistema se apagará debido a tareas habituales de mantenimiento a partir de las 9 de la mañana. Lamentamos las molestias.
Knowledge-based identification of music suited for places of interest
Entity
UAM. Departamento de Ingeniería InformáticaPublisher
Springer Berlin HeidelbergDate
2014-03Citation
10.1007/s40558-014-0004-x
Information Technology & Tourism 14.1 (2014): 73-95
ISSN
1098-3058 (print); 1943-4294 (online)DOI
10.1007/s40558-014-0004-xFunded by
This work was supported by the Spanish Government (TIN201128538C02) and the Regional Government of Madrid (S2009TIC1542).Project
Comunidad de Madrid. S2009/TIC-1542/MA2VICMREditor's Version
http://dx.doi.org/10.1007/s40558-014-0004-xSubjects
Linked data; Meaning of a place; Music recommendation; Semantic networks; InformáticaNote
The final publication is available at Springer via http://dx.doi.org/10.1007/s40558-014-0004-xRights
© Springer-Verlag Berlin Heidelberg 2014Abstract
Place is a notion closely linked with the wealth of human experience, and invested by values, attitudes, and cultural influences. In particular, many places are strongly related to music, which contributes to shaping the perception and meaning of a place. In this paper we propose a computational approach to identify musicians and music suited for a place of interest (POI)––which is based on a knowledge-based framework built upon the DBpedia ontology––and a graph-based algorithm that scores musicians with respect to their semantic relatedness with a POI and suggests the top scoring ones. Through empirical experiments we show that users appreciate and judge the musician recommendations generated by the proposed approach as valuable, and perceive compositions of the suggested musicians as suited for the POIs.
Files in this item
Google Scholar:Kaminskas, Marius
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Fernández-Tobías, Ignacio
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Ricci, Francesco
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Cantador Gutiérrez, Iván
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