Advertisement

A Flexible Querying Framework (FQF): Some Implementation Issues

  • Bert Callens
  • Guy de Tré
  • Jörg Verstraete
  • Axel Hallez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2869)

Abstract

Fuzzy data are a common concept in today’s information society. Some data can be unknown, other data may be inaccurate or uncertain. Still, this fuzzy data must be accounted for in modern businesses and therefore must be stored. Fuzzy relational databases have been studied extensively over time, which resulted in numerous models and representation techniques, some of which have been implemented as software layers on top of database systems. Different query languages and end-user interfaces have been extended to perform flexible queries on both regular and fuzzy databases. In this paper, a framework is presented that not only enables flexible querying on the relational model, but on other database models as well, of which the most important are object-oriented database models. This framework, called FQF or Flexible Querying Framework, is built on the recently developed Java Data Objects (JDO) standard.

Keywords

Query Language Aggregation Operator Fuzzy Data Simple Proposition Java Object 
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.
    Bosc, P., Prade, H.: An Introduction to Fuzzy Set and Possibility Theory Based Approaches to the Treatment of Uncertainty and Imprecision in Database Management Systems. In: Proc. of the 2nd Workshop on Uncertainty Management in Information Systems: From Needs to Solutions, Catalina, California (1993)Google Scholar
  2. 2.
    De Caluwe, R.: Fuzzy and Uncertain Object-oriented Databases: Concepts and Models. World Scientific, Singapore (1997)zbMATHGoogle Scholar
  3. 3.
    Sicilia, M.-A., García, E., Díaz, P., Aedo, I.: Extending Relational Data Access Programming Libraries for Fuzziness: The fJDBC Framework. In: Andreasen, T., Motro, A., Christiansen, H., Larsen, H.L. (eds.) FQAS 2002. LNCS (LNAI), vol. 2522, pp. 314–328. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  4. 4.
    De Tré, G.: Extended Possibilistic Truth Values. International Journal of Intelligent Systems 17, 427–446 (2002)zbMATHCrossRefGoogle Scholar
  5. 5.
    Zadeh, L.A.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems 1(1), 3–28 (1978)zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    De Tré, G., De Caluwe, R., Verstraete, J., Hallez, A.: Conjunctive Aggregation of Extended Possibilistic Truth Values and Flexible Database Querying. In: Andreasen, T., Motro, A., Christiansen, H., Larsen, H.L. (eds.) FQAS 2002. LNCS (LNAI), vol. 2522, pp. 344–355. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  7. 7.
    Dubois, D., Fargier, H., Prade, H.: Beyond min aggregation in multicriteria decision (ordered) weighted min, discri-min, leximin. In: Yager, R., Kacprzyk, J. (eds.) The ordered weighted averaging operators, pp. 181–192. Kluwer Academic Publishers, Dordrecht (1997)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Bert Callens
    • 1
  • Guy de Tré
    • 1
  • Jörg Verstraete
    • 1
  • Axel Hallez
    • 1
  1. 1.Computer Science Laboratory, Department of Telecommunications and Information ProcessingGhent UniversityGentBelgium

Personalised recommendations