A Knowledge Representation Scheme and a Knowledge Derivation Mechanism for Achieving Rule Sharing among Heterogeneous Expert Systems

  • Stanley Y. W. Su
  • Jong H. Park


This paper presents a framework for integrating heterogeneous expert systems (ESs) on a complex domain, each of which has only partial knowledge with respect to the entire problem domain. It focuses on the types of knowledge that is expressed in the forms of intensional data such as rules and constraints. An integration approach by which the component ESs may exchange their expertises in an intertwined manner is presented. One advantage of this approach is that rules can in effect be shared among heterogeneous ESs. The knowledge representation scheme using both static and dynamic knowledge representation models, the query language, and the knowledge derivation mechanism for achieving such integration are described. This approach can be used as a basis for developing distributed database systems with explicit constraint management or heterogeneous distributed expert database systems, and for integrating multiple expert systems. A prototype system has been developed to verify the ideas presented in this paper. The implementation effort is briefly described.


Data Item Global Knowledge Transaction Manager Query Processor Cyclic Path 
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.


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Copyright information

© Springer-Verlag/Wien 1990

Authors and Affiliations

  • Stanley Y. W. Su
    • 1
  • Jong H. Park
    • 1
  1. 1.Database Systems Research and Development Center Department of Computer Information Sciences Department of Electrical EngineeringUniversity of FloridaUSA

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