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Statistical vs. Rule-Based Stemming for Monolingual French Retrieval

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Evaluation of Multilingual and Multi-modal Information Retrieval (CLEF 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4730))

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Abstract

This paper describes our approach to the 2006 Adhoc Mo-nolingual Information Retrieval run for French. The goal of our experiment was to compare the performance of a proposed statistical stemmer with that of a rule-based stemmer, specifically the French version of Porter’s stemmer. The statistical stemming approach is based on lexicon clustering, using a novel string distance measure. We submitted three official runs, besides a baseline run that uses no stemming. The results show that stemming significantly improves retrieval performance (as expected) by about 9-10%, and the performance of the statistical stemmer is comparable with that of the rule-based stemmer.

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References

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Author information

Authors and Affiliations

  1. CVPR Unit, Indian Statistical Institute, Kolkata,  

    Prasenjit Majumder & Mandar Mitra

  2. Dept. of EE, Jadavpur University, Kolkata,  

    Kalyankumar Datta

Authors
  1. Prasenjit Majumder
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  2. Mandar Mitra
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  3. Kalyankumar Datta
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Editor information

Carol Peters Paul Clough Fredric C. Gey Jussi Karlgren Bernardo Magnini Douglas W. Oard Maarten de Rijke Maximilian Stempfhuber

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© 2007 Springer-Verlag Berlin Heidelberg

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Majumder, P., Mitra, M., Datta, K. (2007). Statistical vs. Rule-Based Stemming for Monolingual French Retrieval. In: Peters, C., et al. Evaluation of Multilingual and Multi-modal Information Retrieval. CLEF 2006. Lecture Notes in Computer Science, vol 4730. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74999-8_14

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  • DOI: https://doi.org/10.1007/978-3-540-74999-8_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74998-1

  • Online ISBN: 978-3-540-74999-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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