Ontology-Based Music Recommender System

  • Miguel Ángel Rodríguez-GarcíaEmail author
  • Luis Omar Colombo-Mendoza
  • Rafael Valencia-García
  • Antonio A. Lopez-Lorca
  • Ghassan Beydoun
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 373)


Recommender systems are modern applications that make suggestions to their users on a variety of items taking into account their preferences in many domains. These systems use people’s opinions to recommend to their end users items that are likely to be of their interest. They are designed to help users to decide on appropriate items and facilitate finding them in a very large collection of items. Traditional syntactic-based recommender systems suffer from several disadvantages, such as polysemy or synonymy, that limit its effectiveness. Semantic technologies provide a consistent and reliable basis for dealing with data at knowledge level. Adding semantically empowered techniques to recommender systems can significantly improve the overall quality of recom-mendations. In this work, a recommender system based on a Music ontology is presented. A preliminary evaluation of the system shows promising results.


Recommender systems music ontologies Semantic Web Knowledgebased systems 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Miguel Ángel Rodríguez-García
    • 1
    Email author
  • Luis Omar Colombo-Mendoza
    • 1
  • Rafael Valencia-García
    • 1
  • Antonio A. Lopez-Lorca
    • 2
  • Ghassan Beydoun
    • 3
  1. 1.Departamento de Informática y SistemasUniversidad de MurciaMurciaSpain
  2. 2.Faculty of Information and Communication TechnologiesSwinburne University of TechnologyHawthornAustralia
  3. 3.Faculty of Engineering and Information ScienceUniversity of WollongongWollongongAustralia

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