Advertisement

An Evaluation of Two Approaches to Exploiting Real-World Knowledge by Intelligent Database Design Tools

  • Shahrul Azman Noah
  • Michael Lloyd-Williams
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1507)

Abstract

Recent years have seen the development of a number of expert system type tools whose primary objective is to provide support to a human during the process of database analysis and design. However, whereas human designers are able to draw upon their experience and knowledge of the real world when performing such a task, knowledge-based database design tools are generally unable to do so. This has resulted in numerous calls for the development of tools that are capable of exploiting real-world knowledge during a design session. It has been claimed that the use of such knowledge has the potential to increase the appearance of intelligence of the tools, to improve the quality of the designs produced, and to increase processing efficiency. However to date, little if any formal evaluation of these claims has taken place. This paper presents such an evaluation of two of the approaches proposed to facilitate system-storage and exploitation of real-world knowledge; the thesaurus approach and the knowledge reconciliation approach. Results obtained have demonstrated that certain aspects of the claimed benefits associated with the use of real-world knowledge have been achieved. However, the extent to which these benefits have been attained and subsequently statistically validated varies.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Baldiserra, C., Ceri, S., Pelagatti, G., Bracchi, G.: Interactive specification and formal verification of user’s views in database design. In: Proceedings of the 5th International Conference on Very Large Databases, Rio de Janeiro, Brazil, pp. 262–272 (1979)Google Scholar
  2. 2.
    Batini, C., Ceri, S., Navathe, S.: Conceptual Database Design: An Entity Relationship Approach. Benjamin-Cummings, Redwood City (1992)zbMATHGoogle Scholar
  3. 3.
    Bouzeghoub, M.: Using expert systems in schema design. In: Loucopoulos, P., Zicari, R. (eds.) Conceptual Modeling, Databases, and CASE: an Integrated View of Information Systems Development, pp. 465–487. Wiley, New York (1992)Google Scholar
  4. 4.
    Bowers, D.S.: From Data to Database. Chapman Hall, London (1993)Google Scholar
  5. 5.
    Bracchi, G., Paolini, P., Pelagatti, G.: Binary logical associations in data modeling. In: Nijsen, G.M. (ed.) Modeling in Data Base Management Systems, pp. 125–148. North-Holland, Amsterdam (1976)Google Scholar
  6. 6.
    Elmasri, R., Navathe, S.B.: Fundamentals of Database Systems. Benjamin Cummings, Redwood City (1989)zbMATHGoogle Scholar
  7. 7.
    Gonzalez, A.J., Gupta, U.G., Chianese, R.B.: Performance evaluation of a large diagnostic expert system using a heuristic test case generator. Engineering Application of Artificial Intelligence 9(3), 275–284 (1996)CrossRefGoogle Scholar
  8. 8.
    Kesh, S.: Evaluating the quality of entity relationship models. Information and Software Technology 37(12), 681–689 (1995)CrossRefGoogle Scholar
  9. 9.
    Lloyd-Williams, M.: Expert system support for object-oriented database design. International Journal of Applied Expert Systems 1(3), 197–212 (1993)Google Scholar
  10. 10.
    Lloyd-Williams, M.: Knowledge-based CASE tools: improving performance using domain specific knowledge. Software Engineering Journal 9(4), 167–173 (1994)CrossRefGoogle Scholar
  11. 11.
    Lloyd-Williams, M.: Exploiting domain knowledge during the automated design of object-oriented databases. In: Embley, D.W., Goldstein, R.C. (eds.) Proceedings of the 16th International Conference on Conceptual Modeling, pp. 16–29. Spinger, Berlin (1997)Google Scholar
  12. 12.
    Lloyd-Williams, M., Beynon-Davies, P.: Expert system for database design: a comparative review. Artificial Intelligence Review 6, 263–283 (1992)CrossRefGoogle Scholar
  13. 13.
    Moody, D.L., Shanks, G.G.: What makes a good data model? Evaluating the quality of entity-relationship models. In: Loucopoulos, P. (ed.) Proceedings of the 13th International Conference on the Entity-Relationship Approach, pp. 94–101. Springer, Berlin (1994)Google Scholar
  14. 14.
    O’Keefe, R.M., Balci, O., Smith, E.P.: Validating expert system performance. IEEE Expert, 81–90 (Winter 1987)Google Scholar
  15. 15.
    O’Keefe, R.M., O’Leary, D.E.: Expert system verification and validation: a survey and tutorial. Artificial Intelligence Review 7(1), 3–42 (1993)CrossRefGoogle Scholar
  16. 16.
    O’Keefe, R.M., Preece, A.D.: The development, validation and implementation of knowledge-based systems. European Journal of Operational Research 92(3), 458–473 (1996)CrossRefzbMATHGoogle Scholar
  17. 17.
    Pippenger, N.: Complexity theory. Scientific American 238(6), 90–102 (1978)CrossRefGoogle Scholar
  18. 18.
    Rees, D.G.: Essential Statistics, 3rd edn. Chapman & Hall, London (1995)Google Scholar
  19. 19.
    Rob, P., Rob, C.C.: Database Systems: Design, Implementation and Management. Wadsworth Publishing, Belmont (1993)zbMATHGoogle Scholar
  20. 20.
    Storey, V.C.: Real world knowledge for databases. Journal of Database Administration 3(1), 1–19 (1992)Google Scholar
  21. 21.
    Storey, V.C., Chiang, R.H.L., Dey, D., Goldstein, R.C., Sundararajan, A., Sundaresan, S.: Knowledge reconciliation for common sense reasoning. In: De, P., Woo, C. (eds.) Proceeding of the 4th Annual Workshop on Information Technologies and Systems, pp. 87–96. Univ. British Columbia, Vancouver (1994)Google Scholar
  22. 22.
    Storey, V.C., Goldstein, R.C.: Design and development of an expert database design system. International Journal of Expert Systems Research and Applications 3(1), 31–63 (1990a)Google Scholar
  23. 23.
    Storey, V.C., Goldstein, R.C.: An expert view creation system for database design. Expert Systems Review 2(3), 19–45 (1990b)Google Scholar
  24. 24.
    Storey, V.C., Goldstein, R.C.: Knowledge-based approach to database design. Management Information Systems Quarterly 17(1), 25–46 (1993)Google Scholar
  25. 25.
    Storey, V.C., Goldstein, R.C., Chiang, R.H.L., Dey, D.: A common-sense reasoning facility based on the entity-relationship mode. In: Elmasri, R.A., Kouramajian, V., Thalheim, B. (eds.) Proceedings of the 12th International Conference on the Entity Relationship Approach, pp. 218–229. Springer, Berlin (1993)Google Scholar
  26. 26.
    Vessey, I., Sravanapudi, A.P.: CASE tools as collaborative support technologies. Communications of the ACM 37(1), 83–102 (1995)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Shahrul Azman Noah
    • 1
  • Michael Lloyd-Williams
    • 2
  1. 1.Department of Information StudiesUniversity of SheffieldSheffieldUK
  2. 2.School of Information Systems and ComputingUniversity of Wales Institute CardiffCardiffUK

Personalised recommendations