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Comparing Weighting Models for Monolingual Information Retrieval

  • Gianni Amati
  • Claudio Carpineto
  • Giovanni Romano
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3237)

Abstract

Motivated by the hypothesis that the retrieval performance of a weighting model is independent of the language in which queries and collection are expressed, we compared the retrieval performance of three weighting models, i.e., Okapi, statistical language modeling (SLM), and deviation from randomness (DFR), on three monolingual test collections, i.e., French, Italian, and Spanish. The DFR model was found to consistently achieve better results than both Okapi and SLM, whose performance was comparable. We also evaluated whether the use of retrieval feedback improved retrieval performance; retrieval feedback was beneficial for DFR and Okapi and detrimental for SLM. Besides relative performance, DFR with retrieval feedback achieved excellent absolute results: best run for Italian and Spanish, third run for French.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Gianni Amati
    • 1
  • Claudio Carpineto
    • 1
  • Giovanni Romano
    • 1
  1. 1.Fondazione Ugo BordoniRomeItaly

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