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Language-Dependent and Language-Independent Approaches to Cross-Lingual Text Retrieval

  • Jaap Kamps
  • Christof Monz
  • Maarten de Rijke
  • Börkur Sigurbjörnsson
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3237)

Abstract

We investigate the effectiveness of language-dependent approaches to document retrieval, such as stemming and decompounding, and constrast them with language-independent approaches, such as character n-gramming. In order to reap the benefits of more than one type of approach, we also consider the effectiveness of the combination of both types of approaches. We focus on document retrieval in nine European languages: Dutch, English, Finnish, French, German, Italian, Russian, Spanish and Swedish. We look at four different information retrieval tasks: monolingual, bilingual, multilingual, and domain-specific retrieval. The experimental evidence is obtained using the 2003 test suite of the cross-language evaluation forum (CLEF).

Keywords

Information Retrieval Machine Translation Retrieval Model European Language Information Retrieval Task 
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 2004

Authors and Affiliations

  • Jaap Kamps
    • 1
  • Christof Monz
    • 1
  • Maarten de Rijke
    • 1
  • Börkur Sigurbjörnsson
    • 1
  1. 1.Language & Inference Technology GroupUniversity of AmsterdamAmsterdamThe Netherlands

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