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International Conference on Case-Based Reasoning

ICCBR 2012: Case-Based Reasoning Research and Development pp 312–326Cite as

On Knowledge Transfer in Case-Based Inference

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7466))

Abstract

While similarity and retrieval in case-based reasoning (CBR) have received a lot of attention in the literature, other aspects of CBR, such as case reuse are less understood. Specifically, we focus on one of such, less understood, problems: knowledge transfer. The issue we intend to elucidate can be expressed as follows: what knowledge present in a source case is transferred to a target problem in case-based inference? This paper presents a preliminary formal model of knowledge transfer and relates it to the classical notion of analogy.

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Author information

Authors and Affiliations

  1. Computer Science Department, Drexel University, Philadelphia, PA, USA, 19104

    Santiago Ontañón

  2. IIIA, Artificial Intelligence Research Institute, CSIC, Spanish Council for Scientific Research, Campus UAB, 08193, Bellaterra, Catalonia, Spain

    Enric Plaza

Authors
  1. Santiago Ontañón
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  2. Enric Plaza
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Editor information

Editors and Affiliations

  1. Universidad Complutense de Madrid, 28040, Madrid, Spain

    Belén Díaz Agudo

  2. Department of Computer Science, University of Auckland, 1142, Auckland, New Zealand

    Ian Watson

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Ontañón, S., Plaza, E. (2012). On Knowledge Transfer in Case-Based Inference. In: Agudo, B.D., Watson, I. (eds) Case-Based Reasoning Research and Development. ICCBR 2012. Lecture Notes in Computer Science(), vol 7466. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32986-9_24

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  • DOI: https://doi.org/10.1007/978-3-642-32986-9_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32985-2

  • Online ISBN: 978-3-642-32986-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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