Mechanisms for structuring knowledge-based systems

  • Dieter Landes
  • Rudi Studer
Knowledge Engineering
Part of the Lecture Notes in Computer Science book series (LNCS, volume 856)


In order to reduce the complexity of large knowledge-based systems and promote reusability, means for decomposing them to smaller chunks are required. MIKE, our knowledge engineering framework, provides three basic means for structuring which are described in this paper: different kinds of knowledge are separated at different knowledge layers, knowledge layers can be structured by modules, and knowledge within modules is expressed in terms of an object-centred data model. In addition, ideas from entity relationship model clustering are adapted and extended to facilitate the understandability of domain knowledge and support the formation of modules.


Processing Module Domain Knowledge Domain Ontology Inference Action Horn Clause 
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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  1. [1]
    J. Angele, D. Fensel, D. Landes, S. Neubert, and R. Studer: Model-Based and Incremental Knowledge Engineering: The MIKE Approach. In Knowledge Oriented Software Design, J. Cuena, ed. IFIP Transactions A-27, Elsevier, Amsterdam, 1993, 139–168.Google Scholar
  2. [2]
    J. Angele, D. Fensel, and R. Studer: The model of expertise in KARL. In Proc. 2nd World Congress on Expert Systems (Lisbon/Estoril, Portugal, Jan. 10–14), 1994.Google Scholar
  3. [3]
    J. Angele: Operationalisierung des Modells der Expertise mit KARL (Operationalization of the model of expertise with KARL). infix Verlag, St. Augustin, Germany, 1993 (in german).Google Scholar
  4. [4]
    C. Batini, G. Di Battista, and G. Santucci: Structuring primitives for a dictionary of entity relationship data schemas. In IEEE Trans. on Software Engineering 19(4), 1993, 344–365.Google Scholar
  5. [5]
    D. Fensel: The knowledge acquisition and representation language KARL. Doctoral dissertation, University of Karlsruhe, Germany, 1993.Google Scholar
  6. [6]
    P. Jaeschke, A. Oberweis, and W. Stucky: Extending ER model clustering by relationship clustering. In Proc. 12th Int. Conf. on the Entity-Relationship Approach ERA '93 (Arlington, Texas, Dec. 15–17), 1993, 447–459.Google Scholar
  7. [7]
    D. Landes and R. Studer: The design process in MIKE. In Proc. 8th Knowledge Acquisition for Knowledge-Based Systems Workshop KAW'94 (Banff, Canada, Jan. 30–Feb. 4), 1994.Google Scholar
  8. [8]
    K. Poeck, D. Fensel, D. Landes, and J. Angele: Combining KARL and configurable role limiting methods for configuring elevator systems. In Proc. 8th Knowledge Acquisition for Knowledge-Based Systems Workshop KAW'94 (Banff, Canada, Jan. 30–Feb. 4), 1994.Google Scholar
  9. [9]
    U. Pletat: The knowledge representation language LLILOG. In Text Understanding in LILOG, O. Herzog and C.-R. Rollinger, eds. LNAI 546, Springer, Berlin, 1991, 357–379.Google Scholar
  10. [10]
    U. Pletat: Modularizing knowledge in LLILOG. IWBS Report 173, IBM Germany, Stuttgart, 1991.Google Scholar
  11. [11]
    C. Sernadas, J. Fiadeiro, and A. Sernadas: Modular construction of logic knowledge bases: an algebraic approach. In Information Systems 15(1), 1990, 37–59.Google Scholar
  12. [12]
    G. Schreiber, B. Wielinga, and J. Breuker, eds.: KADS — A Principled Approach to Knowledge-Based Systems Development. Academic Press, London, 1993.Google Scholar
  13. [13]
    T.J. Teorey, G. Wei, D.L. Bolton, and J.A. Koenig: ER model clustering as an aid for user communication and documentation in database design. In CACM 32(8), 1989, 975–987.Google Scholar
  14. [14]
    G. Wiederhold, P. Rathmann, T. Barsalou, B.S. Lee, and D. Quass: Partitioning and composing knowledge. In Information Systems 15(1), 1990, 61–72.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • Dieter Landes
    • 1
  • Rudi Studer
    • 1
  1. 1.Institut für Angewandte Informatik und Formale BeschreibungsverfahrenUniversität KarlsruheKarlsruheGermany

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