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Knowledge Base Decomposition to Facilitate Verification

Author

Listed:
  • Sumit Sarkar

    (PO Box 830688, MS JO44, School of Management, University of Texas at Dallas, Richardson, Texas 75083)

  • Mysore Ramaswamy

    (Department of Management and Marketing, Southern University, Baton Rouge, Louisiana 70813)

Abstract

We examine the verification of large knowledge-based systems. When knowledge bases are large, the verification process poses several problems that are usually not significant for small systems. We focus on decompositions that allow verification of such systems to be performed in a modular fashion. We identify a graphical framework, that we call an ordered polytree, for decomposing systems in a manner that enables modular verification. We also determine the nature of information that needs to be available for performing local checks to ensure accurate detection of anomalies. We illustrate the modular verification process using examples, and provide a formal proof of its accuracy. Next, we discuss a meta-verification procedure that enables us to check if decompositions under consideration do indeed satisfy the requirements for an ordered polytree structure. Finally, we show how the modular verification algorithm leads to considerable improvements in the computational effort required for verification as compared to the traditional approach.

Suggested Citation

  • Sumit Sarkar & Mysore Ramaswamy, 2000. "Knowledge Base Decomposition to Facilitate Verification," Information Systems Research, INFORMS, vol. 11(3), pages 260-283, September.
    • Handle: RePEc:inm:orisre:v:11:y:2000:i:3:p:260-283
    DOI: 10.1287/isre.11.3.260.12207
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    References listed on IDEAS

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    1. Arie Segev & J. Leon Zhao, 1994. "Rule Management in Expert Database Systems," Management Science, INFORMS, vol. 40(6), pages 685-707, June.
    2. Andrew Trice & Randall Davis, 1993. "Heuristics for Reconciling Independent Knowledge Bases," Information Systems Research, INFORMS, vol. 4(3), pages 262-288, September.
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