Hey! Ho! Let’s Go! Explanatory Music Recommendations with dbrec

  • Alexandre Passant
  • Stefan Decker
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6089)


In this demo paper, we present dbrec ( ), a music recommendation system using Linked Data, where recommendation are computed from DBpedia using an algorithm for Linked Data Semantic Distance (LDSD). We describe how the system can be used to get recommendations for approximately 40,000 artists and bands, and in particular how it provides explanatory recommendations to the end-user. In addition, we discuss the research background of dbrec, including the LDSD algorithm and its related ontology.


Link Data SPARQL Query Research Background Related Ontology Link Open Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Alexandre Passant
    • 1
  • Stefan Decker
    • 1
  1. 1.Digital Enterprise Research InstituteNational University of IrelandGalway

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