Combining databases with prioritized information

  • Shekhar Pradhan
  • Jack Minker
  • V. S. Subrahmanian

Abstract

To solve a problem one may need to combine the knowledge of several different experts. It can happen that some of the claims of one or more experts may be in conflict with the claims of other experts. There may be several such points of conflict and any claim may be involved in several different such points of conflict. In that case, the user of the knowledge of experts may prefer a certain claim to another in one conflict-point without necessarily preferring that statement in another conflict-point.

Our work constructs a framework within which the consequences of a set of such preferences (expressed as priorities among sets of statements) can be computed. We give four types of semantics for priorities, three of which are shown to be equivalent to one another. The fourth type of semantics for priorities is shown to be more cautious than the other three. In terms of these semantics for priorities, we give a function for combining knowledge from different sources such that the combined knowledge is conflict-free and satisfies all the priorities.

Keywords

combining databases databases prioritized data 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Baral, C., Kraus, S., and Minker, J. (1991). Combining multiple knowledge bases.IEEE Transactions on Data and Knowledge Engineering, 3, 208–220.Google Scholar
  2. Baral, C., Kraus, S., Minker, J., and Subrahmanian, V.S. (1992). Combining knowledge bases consisting of first order theories.Computational Intelligence, 8, 45–71.Google Scholar
  3. Fagin, R., Ullman, J.D., and Vardi, M.Y. (1983). On the semantics of updates in databases. InProc. 7th ACM SIGACT/SIGMOD Symposium on Principles of Database Systems (pp. 352–365).Google Scholar
  4. Gelfond, M. and Lifschitz, V. (1988). The Stable Model Semantics for Logic Programming. In R.A. Kowalski and K.A. Bowen, (eds.).Proc. 5th International Conference and Symposium on Logic Programming (pp. 1070–1080). Seattle, Washington.Google Scholar
  5. Ryan, M. (1991). Belief revision and ordered theory presentation. In P. Dekker and M. Stokhof, (eds.)Proc. Eighth Amsterdam Colloquium on Logic.Google Scholar
  6. Ryan, M. (1992).Ordered Presentation of Theories: Default Reasoning and Belief Revision. PhD thesis, Department of Computing, Imperial College.Google Scholar
  7. Ryan, M. (1992). Representing defaults as sentences with reduced priority. In B. Nebel and W. Swartout, (eds.)Proc. KR'92. Morgan Kaufmann.Google Scholar
  8. Subrahmanian, V.S. (1992). Amalgamating knowledge bases, Technical Report Univ. of Maryland CS-TR-2949, Department of Computer Science, University of Maryland, College Park, Md 20742. Currently being revised for publication inACM Trans. on Database Systems.Google Scholar
  9. Tversky, A. and Kahneman, D. (1981). The framing of decisions and the psychology of choice.Science, 211, 453–458.Google Scholar
  10. Van Gelder, A. ross, K., and Schlipf, J.S. (1988). Unfounded Sets and Well-founded Semantics for General Logic Programs. InProc. 7th Symposium on Principles of Database Systems (pp. 221–230).Google Scholar

Copyright information

© Kluwer Academic Publishers 1995

Authors and Affiliations

  • Shekhar Pradhan
    • 1
    • 2
  • Jack Minker
    • 3
    • 1
  • V. S. Subrahmanian
    • 3
    • 1
  1. 1.Department of Computer ScienceUniversity of MarylandCollege ParkUSA
  2. 2.Department of PhilosophyCentral Missouri State UniversityWarrensburgUSA
  3. 3.Institute for Advanced Computer StudiesUniversity of MarylandCollege ParkUSA

Personalised recommendations