Soft querying, a new feature for database management systems

  • Patrick Bosc
  • Ludovic Lietard
  • Olivier Pivert
Advanced Querying Concepts
Part of the Lecture Notes in Computer Science book series (LNCS, volume 856)


This paper deals with imprecise querying of regular relational databases which is intended to make database management systems more powerful. A special emphasis is put on flexible queries addressed to regular databases. We first show that when comparing various attempts made to deal with such queries, the fuzzy set approach turns out to generalize the other solutions. Secondly, we present some key features of SQLf, an extension of the SQL query language. SQLf allows the expression of a wide range of flexible queries whose interpretation is based on fuzzy set theory.


Relational databases Fuzzy sets Flexible queries SQL query language 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Bernstein P. & Chiu D., “Using semi-joins to solve relational queries”, Journal of the ACM, 28(1), 25–40, (1981).Google Scholar
  2. [2]
    Bosc P., Galibourg M. & Hamon G., “Fuzzy querying with SQL: extensions and implementation aspects”, Fuzzy Sets and Systems, 28, 333–349, (1988); also in Readings in Fuzzy Sets for Intelligent Systems, D. Dubois, H. Prade, R.R. Yager eds, Morgan-Kaufmann publishers, 686–694, (1993).MathSciNetGoogle Scholar
  3. [3]
    Bosc P. & Pivert O., “Algorithms for flexible selections in relational databases”, Proc. ASLIB Conference, York (GB), 211–225, (1989).Google Scholar
  4. [4]
    Bosc P. & Pivert O., “About equivalences in SQLf, a relational language supporting imprecise querying”, Proc. Int. Fuzzy Engineering Symposium, Yokohama (Japan), 309–320, (1991).Google Scholar
  5. [5]
    Bosc P.& Pivert O., “On the evaluation of simple fuzzy relational queries: principles and measures”, in Fuzzy Logic: State of the Art (R. Lowen ed.), Kluwer Academic Publishers, 355–364, (1993).Google Scholar
  6. [6]
    Bosc P. & Pivert O., “SQLf: A relational database language for fuzzy querying”, to appear in IEEE Transactions on Fuzzy Systems.Google Scholar
  7. [7]
    Bosc P., Lietard L. & Pivert O., “Quantifications and database fuzzy querying”, to appear in Fuzzy Sets and Possibility Theory in Database Management Systems (Bosc P. and Kacprzyk J. eds.), Physica-Verlag, Heidelberg.Google Scholar
  8. [8]
    Chamberlin et al., “SEQUEL2: a unified approach to data definition, manipulation and control”, IBM Journal of Research and Development, 20(6), 560–575, (1976).Google Scholar
  9. [9]
    Cuppens F. & Demolombe R., “How to regognize interesting topics to provide cooperative answering”, Information Systems, 14(2), 163–173, (1989).Google Scholar
  10. [10]
    Dubois D. & Prade H., “A review of Fuzzy Set Aggregation Connectives”, Information Sciences, 36, 85–121, (1985).Google Scholar
  11. [11]
    Ichikawa T. & Hirakawa M., “ARES: a relational database with the capability of performing flexible interpretation of queries”, IEEE Trans. on Software Engineering, 12(5), 624–634, (1986).Google Scholar
  12. [12]
    Lacroix M. & Lavency P., “Preferences: putting more knowledge into queries”, Proc. 13th VLDB Conference, Brighton (GB), 217–225, (1987).Google Scholar
  13. [13]
    Motro A., “VAGUE: a user interface to relational databases that permits vague queries”, ACM Trans. on Office Information Systems, 6(3), 187–214, (1988).Google Scholar
  14. [14]
    Motro A., “A trio of database user interfaces for handling vague retrieval requests”, Data Engineering Bulletin, 12(2), 54–63, (1989).Google Scholar
  15. [15]
    Prade H., “A two-layer fuzzy pattern matching procedure for the evaluation of conditions involving vague quantifiers”, Journal of Intelligent and Robotic Systems, 3, 93–101, (1990).Google Scholar
  16. [16]
    Rabitti F., “Retrieval of multimedia documents by imprecise query specification”, Lecture Notes on Computer Science, 416, (1990).Google Scholar
  17. [17]
    Yager R.R., “On ordered weighted averaging aggregation operators in multicriteria decisionmaking”, IEEE Transactions on Systems, Man and Cybernetics, 8, 183–190, (1988).Google Scholar
  18. [18]
    Yager R.R., “Non-monotonic set theoretic operations”, Fuzzy Sets and Systems, 42, 173–190, (1991).Google Scholar
  19. [19]
    Zadeh L.A., “ Fuzzy sets”, in Information and Control, 8, (Academic Press, New York), 338–353, (1965).Google Scholar
  20. [20]
    Zadeh L.A., “A computational approach to fuzzy quantifiers in natural languages”, Computer Mathematics with Applications, 9, 149–183, (1983).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Patrick Bosc
    • 1
  • Ludovic Lietard
    • 1
  • Olivier Pivert
    • 1
  1. 1.IRISA/ENSSATLannion CédexFrance

Personalised recommendations