Towards Flexible Information Retrieval Based on CP-Nets

  • Fatiha Boubekeur
  • Mohand Boughanem
  • Lynda Tamine-Lechani
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4027)


This paper describes a flexible information retrieval approach based on CP-Nets (Conditional Preferences Networks). The CP-Net formalism is used for both representing qualitative queries (expressing user preferences) and representing documents in order to carry out the retrieval process. Our contribution focuses on the difficult task of term weighting in the case of qualitative queries. In this context, we propose an accurate algorithm based on UCP-Net features to automatically weight Boolean queries. Furthermore, we also propose a flexible approach for query evaluation based on a flexible aggregation operator adapted to the CP-Net semantics.


Query Term Information Retrieval System Query Evaluation Utility Factor Boolean Model 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bordogna, G., Carrara, P., Pasi, G.: Query term weights as constraints in fuzzy information retrieval. Information Processing and Management 27(1), 15–26 (1991)CrossRefGoogle Scholar
  2. 2.
    Bordogna, G., Pasi, G.: A fuzzy linguistic approach generalizing Boolean information retrieval: A model and its evaluation. Journal of the American Society for Information Science 44(2), 70–82 (1993)CrossRefGoogle Scholar
  3. 3.
    Bordogna, G., Pasi, G.: Linguistic aggregation operators of selection criteria in fuzzy information retrieval. International Journal of Intelligent Systems (10), 233–248 (1995)Google Scholar
  4. 4.
    Boutilier, C., Brafman, R., Hoos, H., Poole, D.: Reasoning with Conditional Ceteris Paribus Preference Statements. In: Proc. of UAI, pp. 71–80 (1999)Google Scholar
  5. 5.
    Boutilier, C., Bacchus, F., Brafman, R.: UCP-networks: A directed graphical representation of conditional utilities. In: Proc. of UAI, pp. 56–64 (2001)Google Scholar
  6. 6.
    Boutilier, C., Brafman, R., Domshlak, C., Hoos, H., Poole, D.: CP-Nets A tool for representing and reasoning about conditional ceteris paribus preference statements. Journal of Artificial Research Intelligence (21), 135–191 (2004)Google Scholar
  7. 7.
    Buell, D.A., Kraft, D.H.: A model for a weighted retrieval system. Journal of the American Society for Information Science 32(3), 211–216 (1981)CrossRefGoogle Scholar
  8. 8.
    Crestani, F., Pasi, G.: Soft information retrieval: Applications of fuzzy Set Theory and Neural Networks. In: Kasabov, N., Kozmz, R. (eds.) Neuro Fuzzy Techniques For Intelligent Information Systems, pp. 287–313. Physica –Verlag, Springer-Verlag Group (1999)Google Scholar
  9. 9.
    Dubois, D., Prade, H.: Weighted minimum and maximum operations in fuzzy set theory. Information Sciences (39), 205–210 (1986)Google Scholar
  10. 10.
    Kraft, D.H., Buell, D.: Fuzzy sets and generalized Boolean retrieval systems. International Journal of Man-Machine Studies 19(1), 45–56 (1983)CrossRefGoogle Scholar
  11. 11.
    Pasi, G.: A logical formulation of the Boolean model and of weighted Boolean model. In: Proceedings of the Workshop on Logical and Uncertainty Models for Information Systems, London, U.K, pp. 1–11 (1999)Google Scholar
  12. 12.
    Yager, R.: A note on weighted queries in information retrieval systems. Journal of American Society for Information Science 38(1), 23–24 (1987)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Fatiha Boubekeur
    • 1
    • 2
  • Mohand Boughanem
    • 1
  • Lynda Tamine-Lechani
    • 1
  1. 1.IRIT-SIGPaul Sabatier UniversityToulouseFrance
  2. 2.Mouloud Mammeri UniversityTizi-OuzouAlgeria

Personalised recommendations