Computing the Semantic Relatedness of Music Genres using Semantic Web Data

Dennis Diefenbach (1) , Pierre-René Lherisson (1) , Fabrice Muhlenbach (1) , Pierre Maret (1)

1 LHC - Laboratoire Hubert Curien

Computing the semantic relatedness between two entities has many applications domains. In this paper, we show a new way to compute the semantic relatedness between two resources using semantic web data. Moreover, we show how this measure can be used to compute the semantic relat-edness between music genres which can be used for music recommendation systems. We first describe how to build a vector representations for resources in an ontology. Subsequently we show how these vector representations can be used to compute the semantic relatedness of two resources. Finally, as an application, we show that our measure can be used to compute the semantic relatedness of music genres.

Mots clés: Language models; Vector Representations; Semantic Relatedness; Music Genres; Recommendation Systems

Domaines: Informatique [cs]

Dennis Diefenbach, Pierre-René Lherisson, Fabrice Muhlenbach, Pierre Maret. Computing the Semantic Relatedness of Music Genres using Semantic Web Data. Semantics 2016, Sep 2016, Leipzig, Germany. ⟨hal-01637065⟩