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Efficient Deduction and Induction: Key to the Success of Data-Intensive Knowledge-Base Systems

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Formal Methods in Databases and Software Engineering

Part of the book series: Workshops in Computing ((WORKSHOPS COMP.))

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Abstract

The development of powerful and efficient deduction and induction mechanisms is the key to the success of Very Large Knowledge-Base systems (VLKBs). Based on our study, we propose (1) an efficient deduction method which applies query-independent compilation and set-oriented, chain-based evaluation in deductive databases, and (2) an efficient attribute-oriented induction method for knowledge discovery in databases. A large knowledge-base system should support both mechanisms and their integration.

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References

  1. F. Bancilhon, D. Maier, Y. Sagiv, and J.D. Ullman. Magic sets and other strange ways to implement logic programs. In Proc. 5th ACM Symp. Principles of Database Systems, pp. 1–15, Cambridge, MA, March 1986.

    Chapter  Google Scholar 

  2. F. Bancilhon and R. Ramakrishnan. An amateur’s introduction to recursive query processing strategies. In Proc. 1986 ACMSIGMOD Conf. Management of Data, pp. 16–52, Washington, DC, May 1986.

    Chapter  Google Scholar 

  3. Y. Cai, N. Cercone, and J. Han. Attribute-oriented induction in relational databases. In G. Piatetsky-Shapiro and W. J. Frawley, editors, Knowledge Discovery in Databases, pp. 213–228. AAAI/MIT Press, 1991.

    Google Scholar 

  4. U.S. Chakravarthy, J. Grant, and J. Minker. Logic-based approach to semantic query optimization. ACM Trans. Database Syst., 15:162–207, 1990.

    Article  Google Scholar 

  5. W. Chen, M. Kifer, and D.S. Warren. Hilog as a platform for a database language. In Proc. 2nd Int. Workshop on Database Programming Languages, pp. 315–329, Gleneden Beach, OR, June 1989.

    Google Scholar 

  6. T.G. Dietterich and R.S. Michalski. A comparative review of selected methods for learning from examples. In R. Michalski et. al., editor, Machine Learning: An Artificial Intelligence Approach, Vol. 1, pp. 41–82. Morgan Kaufmann, 1983.

    Google Scholar 

  7. D. Fisher. Improving inference through conceptual clustering. In Proc. 1987 AAAI Conf, pp. 461–465, Seattle, Washington, July 1987.

    Google Scholar 

  8. A. Van Gelder, K.A. Ross, and J.S. Schlipf. The well-founded semantics for general logic programs. J. ACM, 38:620–650, 1991.

    MATH  Google Scholar 

  9. J. Han. Multi-way counting method. Information Systems, 14:219–229, 1989.

    Article  MATH  Google Scholar 

  10. J. Han. Compilation-based list processing in deductive databases. In A. Pirotte, C. Delobel and G. Gottlob, editors, Extending Database Technology — EDBT’92 [Lecture Notes in Computer Science 580], pp. 104–119. Springer-Verlag, 1992.

    Google Scholar 

  11. J. Han, Y. Cai, and N. Cercone. Knowledge discovery in databases: An attribute-oriented approach. In Proc. of 18th Int’l Conf. on Very Large Data Bases, pp. 547–559, Vancouver, Canada, August 1992.

    Google Scholar 

  12. J. Han and Z.N. Li. Deductive-ER: Deductive entity-relationship model and its data language. Information and Software Technology, 34:192–204, 1992.

    Article  Google Scholar 

  13. J. Han and W. Lu. Asynchronous chain recursions. IEEE Trans. Knowl-edge and Data Engineering, 1:185–195, 1989.

    Article  Google Scholar 

  14. J. Han and K. Zeng. Automatic generation of compiled forms for linear recursions. Information Systems, 17:299–322, 1992.

    Article  MATH  Google Scholar 

  15. R. Hull and R. King. Semantic database modeling: Survey, applications, and research issues. ACM Comput. Surv., 19:201–260, 1987.

    Article  Google Scholar 

  16. M. Kifer and G. Lausen. F-logic: A higher order language for reasoning about objects, inheritance, and scheme. In Proc. 1989 ACM-SIGMOD Conf. Management of Data, pp. 134–146, Portland, Oregon, June 1989.

    Chapter  Google Scholar 

  17. R. Krishnamurthy and C. Zaniolo. Optimization in a logic based language for knowledge and data intensive applications. In Extending Database Technology, editor, 8) [Lecture Notes in Computer Science 303], pp. 16–33. Springer-Verlag, 1988.

    Google Scholar 

  18. L.V.S. Lakshmanan and R. Missaoui. On semantic query optimization in deductive databases. In Proc. 8th Int. Conf. Data Engineering, pp. 368–375, Phoenix, AZ, Feb. 1992.

    Google Scholar 

  19. R.S. Michalski. A theory and methodology of inductive learning. In Michal-ski et.al., editor, Machine Learning: An Artificial Intelligence Approach, Vol. 1, pp. 83–134. Morgan Kaufmann, 1983.

    Google Scholar 

  20. R.S. Michalski, J.G. Carbonell, and T.M. Mitchell. Machine Learning, An Artificial Intelligence Approach, Vol. 2. Morgan Kaufmann, 1986.

    MATH  Google Scholar 

  21. T.M. Mitchell, R.M. Keller, and S.T. Kedar-Cabelli. Explanation-based generalization: A unifying view. Machine Learning, 1:47–80, 1986.

    Google Scholar 

  22. S. Naqvi and S. Tsur. A Logical Data Language for Data and Knowledge Bases. Computer Science Press, 1989.

    Google Scholar 

  23. G. Piatetsky-Shapiro and W.J. Frawley. Knowledge Discovery in Databases. AAAI/MIT Press, 1991.

    Google Scholar 

  24. A. Silberschatz, M. Stonebraker, and J.D. Ullman. Database systems: Achievements and opportunities. Comm. ACM, 34:94–109, 1991.

    Article  MathSciNet  Google Scholar 

  25. S. Tsur. Deductive databases in action. In Proc. 10th ACM Symp. Principles of Database Systems, pp. 142–153, Denver, CO, May 1991.

    Google Scholar 

  26. J.D. Ullman. Principles of Database and Knowledge-Base Systems, Vol. 2. Computer Science Press, 1989.

    Google Scholar 

  27. J.D. Ullman. A comparison of deductive and object-oriented database systems. In obel et. al., editor, Deductive and Object-Oriented Databases (DOOD’91) [Lecture Notes in Computer Science 566], pp. 263–277. Springer Verlag, 1991.

    Google Scholar 

  28. C. Zaniolo. Object identity and inheritance in deductive databases: an evolutionary approach. In J.-M. Nicolas Kim and S. Nishio, editors, Deductive and Object-Oriented Databases, pp. 7–24. Elsevier Science, 1990.

    Google Scholar 

  29. J. Zytkow and J. Baker. Interactive mining of regularities in databases. In G. Piatetsky-Shapiro and W.J. Frawley, editors, Knowledge Discovery in Databases, pp. 31–54. AAAI/MIT Press, 1991.

    Google Scholar 

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Authors and Affiliations

  1. School of Computing Science, Simon Fraser University, Burnaby, B.C., V5A 1S6, Canada

    Jiawei Han

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  1. Jiawei Han
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Editors and Affiliations

  1. Department of Computer Science, Concordia University, 1455 de Maisonneuve Blvd. West, Montreal, Quebec, H3G 1M8, Canada

    V. S. Alagar PhD , Laks V. S. Lakshmanan PhD  & F. Sadri PhD ,  & 

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© 1993 British Computer Society

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Han, J. (1993). Efficient Deduction and Induction: Key to the Success of Data-Intensive Knowledge-Base Systems. In: Alagar, V.S., Lakshmanan, L.V.S., Sadri, F. (eds) Formal Methods in Databases and Software Engineering. Workshops in Computing. Springer, London. https://doi.org/10.1007/978-1-4471-3213-4_9

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  • DOI: https://doi.org/10.1007/978-1-4471-3213-4_9

  • Publisher Name: Springer, London

  • Print ISBN: 978-3-540-19812-3

  • Online ISBN: 978-1-4471-3213-4

  • eBook Packages: Springer Book Archive

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