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Why and How Knowledge Discovery Can Be Useful for Solving Problems with CBR

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Case-Based Reasoning. Research and Development (ICCBR 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6176))

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Abstract

In this talk, we discuss and illustrate links existing between knowledge discovery in databases (KDD), knowledge representation and reasoning (KRR), and case-based reasoning (CBR). KDD techniques especially based on Formal Concept Analysis (FCA) are well formalized and allow the design of concept lattices from binary and complex data. These concept lattices provide a realistic basis for knowledge base organization and ontology engineering. More generally, they can be used for representing knowledge and reasoning in knowledge systems and CBR systems as well.

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Authors and Affiliations

  1. LORIA, B.P. 70239, Équipe Orpailleur, Bâtiment B, F-54506, Vandœuvre-lès-Nancy

    Amedeo Napoli

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  1. Amedeo Napoli
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Editors and Affiliations

  1. Institute of Technology, University of Washington, Tacoma, 1900 Commerce Street, Box 358426, 98402, Tacoma, WA, USA

    Isabelle Bichindaritz

  2. Dipartimento di Informatica, Università del Piemonte Orientale, P.O. Box, Alessandria, Italy

    Stefania Montani

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Napoli, A. (2010). Why and How Knowledge Discovery Can Be Useful for Solving Problems with CBR . In: Bichindaritz, I., Montani, S. (eds) Case-Based Reasoning. Research and Development. ICCBR 2010. Lecture Notes in Computer Science(), vol 6176. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14274-1_2

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  • DOI: https://doi.org/10.1007/978-3-642-14274-1_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14273-4

  • Online ISBN: 978-3-642-14274-1

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