Motivating Serendipitous Encounters in Museum Recommendations

  • Leo Iaquinta
  • Marco de Gemmis
  • Pasquale Lops
  • Giovanni Semeraro
  • Piero Molino
Part of the Studies in Computational Intelligence book series (SCI, volume 361)

Abstract

Recommender Systems try to assist users to access complex information spaces regarding their long term needs and preferences. Various recommendation techniques have been investigated and each one has its own strengths and weaknesses. Especially, content-based techniques suffer of overspecialization problem. We propose to inject diversity in the recommendation task by exploiting the content-based user profile to spot potential surprising suggestions. In addition, the actual selection of serendipitous items is motivated by an applicative scenario. Thus, the reference scenario concerns personalized tours in a museum and serendipitous items are introduced by slight diversions on the context-aware tours.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Leo Iaquinta
    • 1
  • Marco de Gemmis
    • 1
  • Pasquale Lops
    • 1
  • Giovanni Semeraro
    • 1
  • Piero Molino
    • 1
  1. 1.Dipartimento di InformaticaUniversità degli Studi di Bari “Aldo Moro”BariItaly

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