Activity based metadata for semantic desktop search

  • Authors:

  • Paul Alexandru Chirita;Rita Gavriloaie;Stefania Ghita;Wolfgang Nejdl;Raluca Paiu

  • Affiliations:

  • L3S Research Center, University of Hanover, Hanover, Germany;L3S Research Center, University of Hanover, Hanover, Germany;L3S Research Center, University of Hanover, Hanover, Germany;L3S Research Center, University of Hanover, Hanover, Germany;L3S Research Center, University of Hanover, Hanover, Germany

  • Venue:
  • ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
  • Year:
  • 2005

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Abstract

With increasing storage capacities on current PCs, searching the World Wide Web has ironically become more efficient than searching one's own personal computer. The recently introduced desktop search engines are a first step towards coping with this problem, but not yet a satisfying solution. The reason for that is that desktop search is actually quite different from its web counterpart. Documents on the desktop are not linked to each other in a way comparable to the web, which means that result ranking is poor or even inexistent, because algorithms like PageRank cannot be used for desktop search. On the other hand, desktop search could potentially profit from a lot of implicit and explicit semantic information available in emails, folder hierarchies, browser cache contexts and others. This paper investigates how to extract and store these activity based context information explicitly as RDF metadata and how to use them, as well as additional background information and ontologies, to enhance desktop search.