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Distributed Computing and Artificial Intelligence, 12th International Conference pp 39–46Cite as

Ontology-Based Music Recommender System

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 373))

Abstract

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.

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Author information

Authors and Affiliations

  1. Departamento de Informática y Sistemas, Universidad de Murcia, 30100, Murcia, Spain

    Miguel Ángel Rodríguez-García, Luis Omar Colombo-Mendoza & Rafael Valencia-García

  2. Faculty of Information and Communication Technologies, Swinburne University of Technology, Hawthorn, Victoria, 3122, Australia

    Antonio A. Lopez-Lorca

  3. Faculty of Engineering and Information Science, University of Wollongong, Wollongong, NSW, Australia

    Ghassan Beydoun

Authors
  1. Miguel Ángel Rodríguez-García
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  2. Luis Omar Colombo-Mendoza
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  3. Rafael Valencia-García
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  4. Antonio A. Lopez-Lorca
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  5. Ghassan Beydoun
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Corresponding author

Correspondence to Miguel Ángel Rodríguez-García .

Editor information

Editors and Affiliations

  1. Department of Electronics, Information and Communication Engineering, Osaka Institute of Technology, Osaka, Osaka, Japan

    Sigeru Omatu

  2. College of Engineering, Qatar University, Doha, Qatar

    Qutaibah M. Malluhi

  3. Department of Computing Science Faculty of Science, University of Salamanca, Salamanca, Spain

    Sara Rodríguez Gonzalez

  4. Department of Electronics and Computers Division of Computer Science and Managem, Koszalin University of Technology, Koszalin, Poland

    Grzegorz Bocewicz

  5. Department of Philosophical, Pedagogical and Economic-Quantitative Sciences, University of Chieti-Pescara, Pescara, Italy

    Edgardo Bucciarelli

  6. Department of Philosophical, Pedagogical and Economic-Quantitative Sciences, University of Chieti-Pescara, Pescara, Italy

    Gianfranco Giulioni

  7. Zayed University, Abu Dhabi Campus, Abu Dhabi, Utd.Arab.Emir.

    Farkhund Iqba

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© 2015 Springer International Publishing Switzerland

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Rodríguez-García, M.Á., Colombo-Mendoza, L.O., Valencia-García, R., Lopez-Lorca, A.A., Beydoun, G. (2015). Ontology-Based Music Recommender System. In: Omatu, S., et al. Distributed Computing and Artificial Intelligence, 12th International Conference. Advances in Intelligent Systems and Computing, vol 373. Springer, Cham. https://doi.org/10.1007/978-3-319-19638-1_5

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  • DOI: https://doi.org/10.1007/978-3-319-19638-1_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19637-4

  • Online ISBN: 978-3-319-19638-1

  • eBook Packages: EngineeringEngineering (R0)

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