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CBR for Complex Objects Represented in Hierarchical Information Systems

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Rough Sets and Current Trends in Computing (RSCTC 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1424))

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Abstract

We discuss how to use Case-Based Reasoning (CBR) philosophy for solving various problems specified by complex objects represented by means of hierarchical information systems [3]. We show how to use this kind of knowledge base for the recognition of novel cases. Next we show how to identify new problems and how to use and adapt methods which were successful in past situations to the new ones. All issues are illustrated by examples, which are here some elementary mathematical tasks.

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References

  1. A. Aamodt & E. Plaza (1994). Case Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. AI Communications.

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  2. J. Kolodner (1993). Case Based Reasoning. Morgan Kaufmann.

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  3. Z. Pawlak (1991). Rough Sets. Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers, Boston, London, Dordrecht.

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  4. L. Polkowski, A. Skowron, J. Komorowski (1996). Approximate case-based reasoning: A rough mereological approach. In: H.D. Burkhard, M. Lenz (eds.), Fourth German Workshop on Case-Based Reasoning. System Development and Evaluation, Informatik Berichte 55, Humboldt University, Berlin, 144–151.

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  5. M.M. Veloso & J.G. Carbonell (1993). Derivational analogy in PRODIGY: Automating case acquisition, storage and utilization. Machine Learning, Vol.10(iii).

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  6. M.M. Veloso, H. Munioz, R. Bergmann (1996). Case-based planing: Selected methods and systems. AI Communications.

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© 1998 Springer-Verlag Berlin Heidelberg

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Wierzbicki, J. (1998). CBR for Complex Objects Represented in Hierarchical Information Systems. In: Polkowski, L., Skowron, A. (eds) Rough Sets and Current Trends in Computing. RSCTC 1998. Lecture Notes in Computer Science(), vol 1424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-69115-4_78

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  • DOI: https://doi.org/10.1007/3-540-69115-4_78

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64655-6

  • Online ISBN: 978-3-540-69115-0

  • eBook Packages: Springer Book Archive

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