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Diversity in a Semantic Recommender System

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Book cover New Trends in Databases and Information Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 241))

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Abstract

In this paper, we introduce the notion of diversity in the recommender systems (RS). The aim is to provide the user with not only all the most relevant contents, but also the most diversified. To do this, we have developed a diversification algorithm that we have implemented on a semantic RS. This last performs the matching between the description of the contents and the user profile. A comparison of our algorithm to the diversity algorithm Swap, in terms of relevance and diversity, has revealed better results.

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Author information

Authors and Affiliations

  1. RIIR Laboratory, Computer Science Department, University of Oran, Oran, Algeria

    Latifa Baba-Hamed & Magloire Namber

Authors
  1. Latifa Baba-Hamed
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  2. Magloire Namber
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Corresponding author

Correspondence to Latifa Baba-Hamed .

Editor information

Editors and Affiliations

  1. Dipartimento di Informatica Bioingegneria, Robotica e, Università di Genova, Genova, Italy

    Barbara Catania

  2. Dipartimento di Automatica e Informatica, Politecnico di Torino, Torino, Italy

    Tania Cerquitelli

  3. Dipartimento di Automatica e Informatica, Politecnico di Torino, Torino, Italy

    Silvia Chiusano

  4. Dipartimento di Informatica, Bioingegneria, Robotica e, Università di Genova, Genova, Italy

    Giovanna Guerrini

  5. Cloudera, Inc., California,, California, USA

    Mirko Kämpf

  6. Faculty of Informatics, Technische Universität München, Garching, Germany

    Alfons Kemper

  7. Dept. of Analytical Information Systems, Saint Petersburg University, Saint Petersburg, Russia

    Boris Novikov

  8. Dipartimento di Ingegneria e Scienza, dell’Informazione, ItalyUniversità di Trento, Povo, TN,, Italy

    Themis Palpanas

  9. Department of Software Engineering, Faculty of Mathematics and Physics, Charles University, Praha, Praha, Czech Republic

    Jaroslav Pokorný

  10. Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece

    Athena Vakali

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© 2014 Springer International Publishing Switzerland

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Baba-Hamed, L., Namber, M. (2014). Diversity in a Semantic Recommender System. In: Catania, B., et al. New Trends in Databases and Information Systems. Advances in Intelligent Systems and Computing, vol 241. Springer, Cham. https://doi.org/10.1007/978-3-319-01863-8_32

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  • DOI: https://doi.org/10.1007/978-3-319-01863-8_32

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01862-1

  • Online ISBN: 978-3-319-01863-8

  • eBook Packages: EngineeringEngineering (R0)

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