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Composing Inductive Applications Using Ontologies for Machine Learning

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Discovey Science (DS 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1532))

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Abstract

Recently, some community focuses on computer aided engineering inductive applications, as seen in workshops, such as AAAI98/ICML98 workshop on ‘The Methodology of Applying Machine Learning’ and ECML98 workshop on ‘Upgrading Learning to the Meta-level: Model Selection and Data Transformation‘. It is time to decompose inductive learning algorithms and organize inductive learning methods (ILMs) for reconstructing inductive learning systems. Given such ILMs, we may invent a new inductive learning system that works well to a given data set by re-interconnecting ILMs

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References

  1. Gertjan van Heijst, “The Role of Ontologies in Knowledge Engineering”, Dr Thesis, University of Amsterdam, 1995.

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© 1998 Springer-Verlag Berlin Heidelberg

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Suyama, A., Negishi, N., Yamagchi, T. (1998). Composing Inductive Applications Using Ontologies for Machine Learning. In: Arikawa, S., Motoda, H. (eds) Discovey Science. DS 1998. Lecture Notes in Computer Science(), vol 1532. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49292-5_55

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  • DOI: https://doi.org/10.1007/3-540-49292-5_55

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65390-5

  • Online ISBN: 978-3-540-49292-4

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