Monolingual Document Retrieval for European Languages

  • Authors:
  • Vera Hollink;Jaap Kamps;Christof Monz;Maarten De Rijke

  • Affiliations:
  • Language & Inference Technology Group, ILLC, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV, Amsterdam, The Netherlands. vhollink@science.uva.nl;Language & Inference Technology Group, ILLC, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV, Amsterdam, The Netherlands. kamps@science.uva.nl;Language & Inference Technology Group, ILLC, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV, Amsterdam, The Netherlands. christof@science.uva.nl;Language & Inference Technology Group, ILLC, University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV, Amsterdam, The Netherlands. mdr@science.uva.nl

  • Venue:
  • Information Retrieval
  • Year:
  • 2004

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Abstract

Recent years have witnessed considerable advances in information retrieval for European languages other than English. We give an overview of commonly used techniques and we analyze them with respect to their impact on retrieval effectiveness. The techniques considered range from linguistically motivated techniques, such as morphological normalization and compound splitting, to knowledge-free approaches, such as n-gram indexing. Evaluations are carried out against data from the CLEF campaign, covering eight European languages. Our results show that for many of these languages a modicum of linguistic techniques may lead to improvements in retrieval effectiveness, as can the use of language independent techniques.