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Pacific Rim International Conference on Artificial Intelligence

PRICAI 1998: PRICAI’98: Topics in Artificial Intelligence pp 205–215Cite as

CAMLET: A platform for automatic composition of inductive learning systems using ontologies

  • Knowledge Management (Ontology, Individual and Collective Knowledge)
  • Conference paper
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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1531))

Abstract

Here is presented a platform for automatic composition of inductive learning systems using ontologies called CAMLET, based on knowledge modeling and ontologies engineering technique. CAMLET constructs an inductive applications with better competence to a given data set, using process and object ontologies. Afterwards, CAMLET instantiates and refines a constructed system based on the following refinement strategies: greedy alteration, random generation and heuristic alteration. Using the UCI repository of ML databases and domain theories, experimental results have shown us that CAMLET supports a user in constructing a inductive applications with best competence.

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Authors and Affiliations

  1. School of Information, Shizuoka University, 3-5-1 Johoku Hamamatsu, 432-8011, Shizuoka, Japan

    Akihiro Suyama, Naoya Negishi & Takahira Yamaguchi

Authors
  1. Akihiro Suyama
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  2. Naoya Negishi
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  3. Takahira Yamaguchi
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Editor information

Hing-Yan Lee Hiroshi Motoda

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© 1998 Springer-Verlag Berlin Heidelberg

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Suyama, A., Negishi, N., Yamaguchi, T. (1998). CAMLET: A platform for automatic composition of inductive learning systems using ontologies. In: Lee, HY., Motoda, H. (eds) PRICAI’98: Topics in Artificial Intelligence. PRICAI 1998. Lecture Notes in Computer Science, vol 1531. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095270

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  • DOI: https://doi.org/10.1007/BFb0095270

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65271-7

  • Online ISBN: 978-3-540-49461-4

  • eBook Packages: Springer Book Archive

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