Advertisement

Report on CLEF-2003 Monolingual Tracks: Fusion of Probabilistic Models for Effective Monolingual Retrieval

  • Jacques Savoy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3237)

Abstract

For our third participation in the CLEF evaluation campaign, our first objective was to propose more effective and general stopword lists for the Swedish, Finnish and Russian languages, along with an improved, more efficient and simpler stemming procedure for these three languages. Our second goal was to suggest a combined search approach based on a data fusion strategy that would work with various European languages. Included in this combined approach is a decompounding strategy for the German, Dutch, Swedish and Finnish languages.

Keywords

Average Precision Retrieval Model Mean Average Precision Compound Word Indexing Scheme 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Amati, G., Carpineto, C., Romano, G.: Italian Monolingual Information Retrieval with PROSIT. In: Peters, C., Braschler, M., Gonzalo, J. (eds.) CLEF 2002. LNCS, vol. 2785, pp. 257–264. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  2. 2.
    Amati, G., van Rijsbergen, C.J.: Probabilistic Models of Information Retrieval Based on Measuring the Divergence from Randomness. ACM Transactions on Information Systems 20, 357–389 (2002)CrossRefGoogle Scholar
  3. 3.
    Braschler, M., Ripplinger, B.: Stemming and Decompounding for German Text Retrieval. In: Sebastiani, F. (ed.) ECIR 2003. LNCS, vol. 2633, pp. 177–192. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  4. 4.
    Buckley, C., Singhal, A., Mitra, M., Salton, G.: New Retrieval Approaches Using SMART. In: Proceedings TREC-4, pp. 25–48. NIST Publication #500-236, Gaithersburg (1996)Google Scholar
  5. 5.
    Chen, A.: Cross-Language Retrieval Experiments at CLEF 2002. In: Peters, C., Braschler, M., Gonzalo, J., Kluck, M. (eds.) Advances in Cross-Language Information Retrieval. LNCS, vol. 2785, pp. 28–48. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  6. 6.
    Fox, E.A., Shaw, J.A.: Combination of Multiple Searches. In: Proceedings TREC-2, pp. 243–249. NIST Publication #500-215, Gaithersburg (1994)Google Scholar
  7. 7.
    Kraaij, W., Pohlmann, R.: Viewing Stemming as Recall Enhancement. In: Proceedings of the ACM-SIGIR 1996, pp. 40–48. The ACM Press, New York (1996)Google Scholar
  8. 8.
    Lovins, J.B.: Development of a Stemming Algorithm. Mechanical Translation and Computational Linguistics 11, 22–31 (1968)Google Scholar
  9. 9.
    Porter, M.F.: An Algorithm for Suffix Stripping. Program 14, 130–137 (1980)Google Scholar
  10. 10.
    Robertson, S.E., Walker, S., Beaulieu, M.: Experimentation as a Way of Life: Okapi at TREC. Information Processing & Management 36, 95–108 (2000)CrossRefGoogle Scholar
  11. 11.
    Savoy, J.: Report on CLEF 2002 Experiments: Combining Multiple Sources of Evidence. In: Peters, C., Braschler, M., Gonzalo, J., Kluck, M. (eds.) Advances in Cross-Language Information Retrieval. LNCS, vol. 2785, pp. 66–90. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  12. 12.
    Singhal, A., Choi, J., Hindle, D., Lewis, D.D., Pereira, F.: AT&T at TREC-7. In: Proceedings TREC-7, pp. 239–251. NIST, Publication #500-242, Gaithersburg (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Jacques Savoy
    • 1
  1. 1.Institut interfacultaire d’informatiqueUniversité de NeuchâtelNeuchâtelSwitzerland

Personalised recommendations