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A Case-Based Approach to Mutual Adaptation of Taxonomic Ontologies

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

Abstract

We present a general framework for addressing the problem of semantic intelligibility among artificial agents based on concepts integral to the case-based reasoning research program. For this purpose, we define case-based semiotics (CBS) (based on the well known notion of the semiotic triangle) as the model that defines semantic intelligibility. We show how traditional CBR notions like transformational adaptation can be used in the problem of two agents achieving mutual intelligibility over a collection of concepts (defined in CBS).

Keywords

  • Mutual Adaptation
  • Ontology Match
  • Transformational Adaptation
  • Adaptation Operation
  • Ontology Alignment

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© 2012 Springer-Verlag Berlin Heidelberg

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Manzano, S., Ontañón, S., Plaza, E. (2012). A Case-Based Approach to Mutual Adaptation of Taxonomic Ontologies. 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_18

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  • DOI: https://doi.org/10.1007/978-3-642-32986-9_18

  • 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)