Measuring uncertainty given imprecise attribute values

  • J. M. Morrissey
6. Information
Part of the Lecture Notes in Computer Science book series (LNCS, volume 521)


A consistent and useful treatment of missing and imprecise data is required for database systems. One problem is that when imprecise data are present then the semantics of query evaluation are no longer obvious and uncertainty is introduced. It is proposed that the query result consist of two sets of objects: those where there is complete certainty and those where there is some uncertainty. Furthermore, the uncertainty should be measured and used to rank the objects for presentation. Self-information and entropy are examined as possible measures of uncertainty.


databases imprecise data uncertainty self-information entropy 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Codd, E.F. Understanding relations. ACM SIGMOD 7, (1975), 23–28.Google Scholar
  2. [2]
    Codd, E.F. Extending the database relational model to capture more meaning. ACM TODS 4,4 (Dec. 1979), 394–434.CrossRefGoogle Scholar
  3. [3]
    Codd, E.F. Missing information (applicable and inapplicable) in relational systems. SIGMOD Record 15,4 (Dec. 1986).Google Scholar
  4. [4]
    Date, C.J. Null values in databases. Proceedings of the 2nd British National Conference on Databases, (1982).Google Scholar
  5. [5]
    Lipski, W. On semantic issues connected with incomplete information databases. ACM TODS 4,3 (Sept. 1979) 262–296.CrossRefGoogle Scholar
  6. [6]
    Morrissey, J.M. A treatment of Imprecise Data and Uncertainty in Information Systems. Ph.D. Thesis. National University of Ireland. 1987.Google Scholar
  7. [7]
    Shafer, G. A Mathematical Theory of Evidence. Princeton University Press, Princeton, New Jersey, (1976).Google Scholar
  8. [8]
    Shortliffe, E.H.; Buchanan, B.G. A model of inexact reasoning in medicine. Mathematical Biosciences, 23, (1975), 351–379.CrossRefGoogle Scholar
  9. [9]
    Vassiliou, Y. Null values in database management: a denotational semantics approach. Proceedings of the 1979 ACM SIGMOD international conference on management of data. Boston, (1979).Google Scholar
  10. [10]
    Vassiliou, Y. A formal treatment of imperfect information in database management. Ph.D. Thesis. University of Toronto, (Sept. 1980).Google Scholar
  11. [11]
    Zadeh, L. Fuzzy sets. Information and Control, 8, (1965), 338–353.CrossRefGoogle Scholar
  12. [12]
    Zadeh, L. Fuzzy sets as a basis for a theory of possibility. In: Fuzzy Sets and Systems, North Holland, Amsterdam, (1978).Google Scholar
  13. [13]
    Zadeh, L. Commonsense knowledge representation based on fuzzy logic. Computer, 16, 10, (1983), 61–65.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • J. M. Morrissey
    • 1
  1. 1.University of WindsorWindsorCanada

Personalised recommendations