Knowledge-based identification of music suited for places of interest
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 app...
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| Published in | Information technology & tourism Vol. 14; no. 1; pp. 73 - 95 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.03.2014
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1098-3058 1943-4294 |
| DOI | 10.1007/s40558-014-0004-x |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Fernández-Tobías, Ignacio Cantador, Iván Ricci, Francesco Kaminskas, Marius |
| Author_xml | – sequence: 1 givenname: Marius surname: Kaminskas fullname: Kaminskas, Marius organization: Faculty of Computer Science, Free University of Bozen-Bolzano – sequence: 2 givenname: Ignacio surname: Fernández-Tobías fullname: Fernández-Tobías, Ignacio organization: Escuela Politécnica Superior, Universidad Autónoma de Madrid – sequence: 3 givenname: Francesco surname: Ricci fullname: Ricci, Francesco organization: Faculty of Computer Science, Free University of Bozen-Bolzano – sequence: 4 givenname: Iván surname: Cantador fullname: Cantador, Iván email: ivan.cantador@uam.es organization: Escuela Politécnica Superior, Universidad Autónoma de Madrid |
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| CitedBy_id | crossref_primary_10_1007_s11257_016_9172_z crossref_primary_10_1016_j_eswa_2019_06_020 crossref_primary_10_1108_DTA_12_2019_0225 crossref_primary_10_1007_s10844_016_0400_0 crossref_primary_10_3390_electronics10131555 |
| Cites_doi | 10.1145/1035134.1035141 10.1007/s13735-012-0032-2 10.1037/1528-3542.8.4.494 10.1007/s007790170019 10.1023/A:1006569829653 10.1109/21.24528 10.1017/CBO9780511809071 10.4018/jswis.2009081901 10.1016/j.cosrev.2012.04.002 10.1023/A:1019194325861 10.1017/CBO9780511763113 10.1016/S0261-5177(02)00005-5 10.1145/159544.159617 10.3115/1614025.1614037 10.1007/978-3-642-38844-6_36 10.1007/978-3-642-17749-1_14 10.1613/jair.2308 10.1007/978-0-387-85820-3 10.1145/2009916.2010012 10.1007/978-3-642-23014-1_8 10.1007/978-3-642-36309-2_37 10.3115/981732.981751 10.1145/2039320.2039324 10.1609/aimag.v32i3.2364 10.1145/2019335.2019341 10.1145/2390848.2390854 10.1007/978-3-642-10543-2_21 |
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| Keywords | Semantic networks Music recommendation Linked data Meaning of a place |
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| Title | Knowledge-based identification of music suited for places of interest |
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