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Grasping the Long Tail: Personalized Search for Cultural Heritage Annotators

  • Chris Dijkshoorn
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7899)

Abstract

Online collections of museums are often hard to access, because the artworks lack appropriate annotations. We develop a framework that supports niches of experts in the crowd in adding annotation of high quality. This thesis focuses on search strategies that match experts with artworks to annotate. Our approach uses explicit semantics for modeling the relations between the properties of the collection items, content-based filtering aimed at diversification, and trust-aware ranking of the results.

Keywords

Cultural Heritage Link Open Data Content Pattern Answer Research Question Link Open Data Cloud 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Chris Dijkshoorn
    • 1
  1. 1.Department of Computer ScienceVU University AmsterdamThe Netherlands

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