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Learning in Knowledge-Base Management Systems

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On Knowledge Base Management Systems

Part of the book series: Topics in Information Systems ((TINF))

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Abstract

This chapter argues that techniques from the field at Machine Learning may play a significant role in future Knowledge-Base Management Systems. We describe a specific knowledge-based consultant system which automatically augments its knowledge base by observing and generalizing from the problem solving steps contributed by its users.

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References

  1. De Jong, G., “Automatic Schema Acquisition in a Natural Language Environment”, in Proceedings of the Second National Conference on Artificial Intelligence, pages 410–413, Pittsburgh, PA, August, 1982.

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  2. Michalski,R. S. ,Carbonell,J. G.and Mitchell,T. M (eds.), Machine Learning: An Artificial Intelligence Approach, Tioga Press, 1982.

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  3. Mitchell, T., Carbonell, J., and Michalski, R. (eds.), Machine Learning: A Guide to Current Research, Kluwer Academic Press, 1986.

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  4. Mitchell, T., “Learning and Problem Solving”, Proc. of IJCAI 83, pp.1139–1151, Karlsrhue, Germany, August 1983.

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  5. Mitchell, T., Mahadevan, S. and Steinberg, L., “LEAP — A Learning Apprentice for VLSI Design”, in Proceedings of the Ninth International Joint Conference on Artificial Intelligence, August 1985.

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  6. Mitchell, T.M., Steinberg, L.I., and Shulman, J.S., “A Knowledge-Based Approach to Design”, In Proceedings of the IEEE Workshop of Principles of Knowledge-Based Systems, pages 27–34. IEEE, December, 1984.

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© 1986 Springer-Verlag

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Mitchell, T.M. (1986). Learning in Knowledge-Base Management Systems. In: Brodie, M.L., Mylopoulos, J. (eds) On Knowledge Base Management Systems. Topics in Information Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4980-1_31

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  • DOI: https://doi.org/10.1007/978-1-4612-4980-1_31

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-9383-5

  • Online ISBN: 978-1-4612-4980-1

  • eBook Packages: Springer Book Archive

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