Fuzzy Querying in Intelligent Information Systems

  • Murat Koyuncu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5822)


Many new database applications require intelligent information management to satisfy different users’ query demands. One way to convert conventional database systems to intelligent information systems is to enhance them with a rule-based system. On the other hand, fuzziness becomes unavoidable for some applications and therefore both the database and rule- based systems should handle fuzziness existing in data and queries. This study explains how a fuzzy rule-based system integrated to a fuzzy spatial, temporal or multimedia database improves the query capabilities of the database system intelligently. Fuzzy query types that can be supported by the rule-based system to improve querying power are discussed.


Database rule-based system fuzziness fuzzy querying 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Li, Q., Lochovsky, F.H.: ADOME: An Advanced Object Modeling Environment. IEEE Trans. Knowledge and Data Engineering 10, 255–276 (1998)CrossRefGoogle Scholar
  2. 2.
    Barja, M.L., Fernandes, A.A., Paton, N.W., Willams, M.H., Dinn, A., Abdelmoty, A.I.: Design and Implementation of Rock & Roll: A Deductive Object Oriented Database System. Information Systems 20, 185–211 (1995)CrossRefGoogle Scholar
  3. 3.
    Kifer, M.: Forword: Deductive Object-Oriented Databases. J. Intell. Inf. Syst. 4, 119–121 (1995)CrossRefGoogle Scholar
  4. 4.
    Liu, M.: Deductive Database Languages: Problems and Solutions. ACM Computing Surveys 31, 27–62 (1999)CrossRefGoogle Scholar
  5. 5.
    Urban, S.D., Karadimce, A.P., Dietrich, S.W., Abdellatif, T.B., Rene Chan, H.W.: CDOL: A Comprehensive Declarative Object Language. Data &Knowledge Engineering 22, 67–111 (1997)zbMATHCrossRefGoogle Scholar
  6. 6.
    Koyuncu, M., Yazici, A.: IFOOD: An Intelligent Fuzzy Object-Oriented Database Architecture. IEEE Trans.on Knowledge and Data Engineering 15, 1137–1154 (2003)CrossRefGoogle Scholar
  7. 7.
  8. 8.
  9. 9.
    Fikes, R., Hayes, P., Horrocks, I.: OWL-QL-a Language for Deductive Query Answering on the Semantic Web. In: Web Semantics: Science, Services and Agents on the World Wide Web, vol. 2, pp. 19–29 (2004)Google Scholar
  10. 10.
    Zhang, W., Ling, T.-W., Chen, Z., Dobbie, G.: XDO2: A deductive object-oriented query language for XML. In: Zhou, L.-z., Ooi, B.-C., Meng, X. (eds.) DASFAA 2005. LNCS, vol. 3453, pp. 311–322. Springer, Heidelberg (2005)Google Scholar
  11. 11.
    Zadeh, L.A.: Fuzzy Sets. Information and Control 8, 338–353 (1965)zbMATHCrossRefMathSciNetGoogle Scholar
  12. 12.
    Zadeh, L.A.: Similarity Relations and Fuzzy Orderings. Inf. Sciences 3, 177–200 (1971)zbMATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    George, R., Srikanth, R., Petry, F.E., Buckles, B.P.: Uncertainty Management Issues in the Object-Oriented Data Model. IEEE Trans. on Fuzzy Systems 4, 179–192 (1996)CrossRefGoogle Scholar
  14. 14.
    Galindo, J., Urrutia, A., Piattini, M.: Fuzzy Databases: Modeling, Design and Implementation. Idea Group Publishing, Hershey (2006)zbMATHGoogle Scholar
  15. 15.
    Bosc, P., Pivert, O.: Fuzzy Querying in Conventional Databases. In: Zadeh, L.A., Kacprzyk, J. (eds.) Fuzzy Logic for Management of Uncertainty, pp. 645–671. John Wiley and Sons Inc., Chichester (1992)Google Scholar
  16. 16.
    Kacprzyk, J., Zadrozny, S.: FQUERY for access: fuzzy querying for a windows-based DBMS. In: Bosc, P., Kacprzyk, J. (eds.) Fuzziness in Database Management Systems, pp. 415–433. Physica-Verlag, Heidelberg (1995)Google Scholar
  17. 17.
    De Caluwe, R., De Tré, G.: Preface to the Special Issue on Advances in Fuzzy Database Technology. Int.J.of Intelligent Systems 22, 661–663 (2007)CrossRefGoogle Scholar
  18. 18.
    Koyuncu, M., Yazici, A.: A Fuzzy Knowledge-Based System for Intelligent Retrieval. IEEE Transactions on Fuzzy Systems 13, 317–330 (2005)CrossRefGoogle Scholar
  19. 19.
    Yen, J., Langari, R.: Fuzzy Logic: Intelligence, Control, and Information. Prentice Hall, New Jersey (1999)Google Scholar
  20. 20.
    Allen, J.F.: Maintaining Knowledge About Temporal Intervals. Communications of the ACM 26, 832–843 (1983)zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Murat Koyuncu
    • 1
  1. 1.Department of Information Systems EngineeringAtilim UniversityAnkaraTurkey

Personalised recommendations