Advertisement

Fusion of Retrieval Models at CLEF 2008 Ad Hoc Persian Track

  • Zahra Aghazade
  • Nazanin Dehghani
  • Leili Farzinvash
  • Razieh Rahimi
  • Abolfazl AleAhmad
  • Hadi Amiri
  • Farhad Oroumchian
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5706)

Abstract

Metasearch engines submit the user query to several underlying search engines and then merge their retrieved results to generate a single list that is more effective to the users’ information needs. According to the idea behind metasearch engines, it seems that merging the results retrieved from different retrieval models will improve the search coverage and precision. In this study, we have investigated the effect of fusion of different retrieval techniques on the performance of Persian retrieval. We use an extension of Ordered Weighted Average (OWA) operator called IOWA and a weighting schema, NOWA for merging the results. Our experimental results show that merging by OWA operators produces better MAP.

Keywords

Information Retrieval Information Fusion Persian Text Retrieval 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Agirre, E., Di Nunzio, G.M., Ferro, N., Mandl, T., Peters, C.: Multilingual Textual Document Retrieval (Ad Hoc). In: Evaluating Systems for Multilingual and Multimodal Information Access 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Aarhus, Denmark (2008)Google Scholar
  2. 2.
    Oroumchian, F., Darrudi, E., Taghiyareh, F., Angoshtari, N.: Experiments with Persian Text Compression for Web. In: 13th international World Wide Web conference on Alternate track papers & posters, pp. 478–479. ACM, New York (2004)CrossRefGoogle Scholar
  3. 3.
  4. 4.
    Terrier Information Retrieval Platform, http://ir.dcs.gla.ac.uk/terrier
  5. 5.
    Amati, G., van Rijsbergen, C.J.: Probabilistic models of information retrieval based on measuring the divergence from randomness. ACM Transactions on Information Systems 20(4), 357–389 (2002)CrossRefGoogle Scholar
  6. 6.
    Yager, R.R.: On ordered weighted averaging aggregation operators in multicriteria decision making. IEEE Transactions on Systems, Man and Cybernetics 18, 183–190 (1988)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Yager, R.R., Filev, D.P.: Induced ordered weighted averaging operators. IEEE Transactions on Systems, Man and Cybernetics–Part B 29, 141–150 (1999)CrossRefGoogle Scholar
  8. 8.
    Min, D., Xu-rui, Z., Yun-xiang, C.: A Note on OWA Operator Based on the Normal Distribution. In: International Conference on Management Science and Engineering, pp. 537–542 (2007)Google Scholar
  9. 9.
    Amiri, H., AleAhmad, A., Oroumchian, F., Lucas, C., Rahgozar, M.: Using OWA Fuzzy Operator to Merge Retrieval System Results. In: The Second Workshop on Computational Approaches to Arabic Script-based Languages, Stanford University, USA (2007)Google Scholar
  10. 10.
    INDRI - Language modeling meets inference networks, http://www.lemurproject.org/indri

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Zahra Aghazade
    • 1
  • Nazanin Dehghani
    • 1
  • Leili Farzinvash
    • 1
  • Razieh Rahimi
    • 1
  • Abolfazl AleAhmad
    • 1
  • Hadi Amiri
    • 1
  • Farhad Oroumchian
    • 2
  1. 1.School of Electrical and Computer EngineeringUniversity of TehranTehranIran
  2. 2.University of Wollongong in DubaiDubaiUAE

Personalised recommendations