Application of Fuzzy Set Theory to Extend Boolean Information Retrieval

  • Gloria Bordogna
  • Gabriella Pasi
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 50)


Abstract. The primary objective of the extensions of Boolean information re-trieval within fuzzy set theory is to model the graduality of the concept of relevance of documents to a user’s query. The result of a query evaluation is represented as a fuzzy subset of the archived documents. Several fuzzy extensions of the Boolean model have been defined which share the characteristics of adopting a weighted document representation and a weighted query language: while these extensions retain the same semantics for the index term weights, named significance degrees, nevertheless, they differ in the semantics associated with the query weights. Query weights are introduced as attributes of the search terms to provide for a greater expressiveness in the formulation of the information needs. The aim of this con-tribution is to show how the fuzzy Boolean information retrieval models are more flexible in representing both document contents and information needs; this char-acteristics is provided by their ability to represent and manage linguistic concepts having a gradual nature.


Query Language Soft Constraint Fuzzy Subset Aggregation Operator Information Retrieval System 
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.


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  1. 1.
    Berrut C, Chiaramella Y. (1986) Indexing medical reports in a multimedia environment: the RIME experimental approach, ACM-SIGIR 89, Boston, USA, 187–197.Google Scholar
  2. 2.
    Bookstein A. (1980) Fuzzy requests: an approach to weighted Boolean searches. J. of the American Society for Information Science31, 240–247.CrossRefGoogle Scholar
  3. 3.
    Bordogna G., Carrara P., Pasi G. (1991) Query term weights as constraints in fuzzy information retrieval. Information Processing & Management27, 15–26.CrossRefGoogle Scholar
  4. 4.
    Bordogna, G., Pasi, G. A. (1993) Fuzzy linguistic approach generalizing Boolean IR: a model and its evaluation. J. of the American Society for Information Science, 44(2), 70–82.CrossRefGoogle Scholar
  5. 5.
    Bordogna G., Pasi G. (1993) Multi criteria decision making in information retrieval. In Proc. of the 3rd International Conference on Current Issues in Fuzzy Technologies, Roncegno, Trento, 3–4 June 1993.Google Scholar
  6. 6.
    Bordogna G., Pasi G. (1995) Controlling retrieval through a user adaptive representation of documents. Int. J. of approximate reasoning12, 317–339.MathSciNetMATHCrossRefGoogle Scholar
  7. 7.
    Bordogna G., and Pasi G. (1995) Linguistic Aggregation Operators of selection Criteria in fuzzy information retrieval. International Journal of Intelligent Systems, 10, 233–248.CrossRefGoogle Scholar
  8. 8.
    Bordogna G. and Pasi G., (1996) A User Adaptive Neural Network Supporting Rule Based Relevance Feedback. Fuzzy Sets and Systems, 82(2), 201–211.MathSciNetCrossRefGoogle Scholar
  9. 9.
    Bordogna G., Bosc P., and Pasi G. (1996) Fuzzy inclusion and extended Boolean information retrieval models, in Proceedings of IPMU’96, 2, Granada , 1–5 June, 1171–1176.Google Scholar
  10. 10.
    Bosc P. (1995) Some views of the division of fuzzy relations.In Proceedings of the 5th International Workshop on Current Issues on Fuzzy Technologies (CIFT’95), Trento (Italy), June 1995, 14–22.Google Scholar
  11. 11.
    Buell D.A., and Kraft D.H. (1981) Threshold values and Boolean retrieval Systems. Information Processing & Management17, 127–136.MATHCrossRefGoogle Scholar
  12. 12.
    Buell D.A. (1982) An analysis of some fuzzy subset applications to information retrieval Systems. Fuzzy Sets and Systems7, 35–42.MathSciNetMATHCrossRefGoogle Scholar
  13. 13.
    Cater S.C., and Kraft D.H. (1989) A generalization and clarification of the Waller-Kraft wish-list. Information Processing & Management25, 15–25.CrossRefGoogle Scholar
  14. 14.
    Chen S.J., Hwang C.L., Hwang F. (1992) Fuzzy Multiple Attribute Decision Making: Methods and Applications. Lecture Notes in Economics and mathematical Systems series 375, Springer-Verlag.MATHCrossRefGoogle Scholar
  15. 15.
    Dubois, D., Prade, H. (1985) A review of fuzzy sets aggregation connectives. Information Sciences, 3, 85–121.MathSciNetCrossRefGoogle Scholar
  16. 16.
    Klir G.J., Folger T.A. (1988) Fuzzy Sets, Uncertainty and Information. Prentice Hall PTR Englewood Cliffs.MATHGoogle Scholar
  17. 17.
    Kraft, D. H., Bordogna, G. and Pasi, G. (1995) An extended fuzzy linguistic approach to generalize Boolean information retrieval. Journal of Information Sciences, Applications, 2(3), 119–134.CrossRefGoogle Scholar
  18. 18.
    Molinari, A. G., Pasi G. (1996) A Fuzzy Representation of HTML Documents for Information Retrieval Systems, in Proc. of IEEE International Conference on Fuzzy Systems, New Orleans, 8–12 September, 1996.Google Scholar
  19. 19.
    Negoita, C. V. (1973) On the notion of relevance in information retrieval. Kybernetes, 2(3), 161–165.MathSciNetMATHCrossRefGoogle Scholar
  20. 20.
    Paice, CD. (1984) Soft evaluation of Boolean search queries in information retrieval Systems. Information Technology: Research Development Applications, 3(1), 33–41.Google Scholar
  21. 21.
    Radecki, T. (1979) Fuzzy set theoretical approach to document retrieval. Information Processing & Management, 15(5), 247–260.MATHCrossRefGoogle Scholar
  22. 22.
    Salton, G., Fox, E., Wu, H. (1983) Extended Boolean Information retrieval. Communications of the ACM, 26(12), 1022–1036.MathSciNetMATHCrossRefGoogle Scholar
  23. 23.
    Salton G., and McGill M.J. (1984) Introduction to modern information retrieval. McGraw-Hill Int. Book Co.Google Scholar
  24. 24.
    Salton, G. and Buckley, C. (1988) Term weighting approaches in automatic text retrieval. Information Processing & Management, 24(5), 513–523.CrossRefGoogle Scholar
  25. 25.
    Sanchez, E. (1989) Importance in knowledge Systems. Information Systems, 14(6), 455–464.CrossRefGoogle Scholar
  26. 26.
    Sparck Jones, K. A. (1971) Automatic keyword Classification for information retrieval. London, England: Butterworths.Google Scholar
  27. 27.
    Sparck Jones, K. A. (1972) A Statistical interpretation of term specificity and its application in retrieval. Journal of Documentation, 28(1), 11–20.CrossRefGoogle Scholar
  28. 28.
    van Rijsbergen, C. J. (1979) Information Retrieval. London, England, Butterworths & Co., Ltd.Google Scholar
  29. 29.
    Waller W.G., and Kraft D.H. (1979) A mathematical model of a weighted Boolean retrieval system. Information Processing & Management15, 235–245.MATHCrossRefGoogle Scholar
  30. 30.
    Yager R. R. (1987) A note on weighted queries in information retrieval Systems. J. of the American Society for Information Science38, 23–24.CrossRefGoogle Scholar
  31. 31.
    Yager R. R. (1988) On Ordered Weighted Averaging aggregation Operators in Multi Criteria Decision Making. IEEE Trans, on Systems, Man and Cybernetics18(1), 183–190.MathSciNetMATHCrossRefGoogle Scholar
  32. 32.
    R.R Yager and J. Kacprzyk eds. (1997) The Ordered Weighted Averaging Operators: Theory and Applications. Kluwer Academic Publishers.Google Scholar
  33. 33.
    Zadeh, L.A. (1965) Fuzzy sets. Information and control, 8, 338–353.MathSciNetMATHCrossRefGoogle Scholar
  34. 34.
    Zadeh L.A. (1975) The concept of a Linguistic Variable and its application to Approximate Reasoning I–II, Information Science 8, 199–249, 301–357.MathSciNetCrossRefGoogle Scholar
  35. 35.
    Zadeh L.A. (1983) A computational Approach to Fuzzy Quantifiers in Natural Languages. Computing and Mathematics with Applications. 9, 149–184.MathSciNetMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Gloria Bordogna
    • 1
  • Gabriella Pasi
    • 1
  1. 1.Consiglio Nazionale delle RicercheIstituto per le Tecnologie Informatiche MultimedialiMilanoItaly

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