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Location-Adapted Music Recommendation Using Tags

  • Marius Kaminskas
  • Francesco Ricci
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6787)

Abstract

Context-aware music recommender systems are capable to suggest music items taking into consideration contextual conditions, such as the user mood or location, that may influence the user preferences at a particular moment. In this paper we consider a particular kind of context aware recommendation task — selecting music content that fits a place of interest (POI). To address this problem we have used emotional tags attached by a users’ population to both music and POIs. Moreover, we have considered a set of similarity metrics for tagged resources to establish a match between music tracks and POIs. In order to test our hypothesis, i.e., that the users will reckon that a music track suits a POI when this track is selected by our approach, we have designed a live user experiment where subjects are repeatedly presented with POIs and a selection of music tracks, some of them matching the presented POI and some not. The results of the experiment show that there is a strong overlap between the users’ selections and the best matching music that is recommended by the system for a POI.

Keywords

recommender systems location-aware context music social tagging emotions 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Marius Kaminskas
    • 1
  • Francesco Ricci
    • 1
  1. 1.Free University of BolzanoBolzanoItaly

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