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Combining views on concepts in unsupervised concept learning

  • Machine Learning II
  • Conference paper
  • First Online:
PRICAI'96: Topics in Artificial Intelligence (PRICAI 1996)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1114))

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Abstract

Classical, prototype and exemplar views on concepts are combined in an unsupervised concept learning system. A flexible matching procedure, which interprets the concept hierarchy in using additional probabilistic and instance-based recognition constraints, allows the system to improve its inference performance. This paper describes the system and evaluates experimentally its performance.

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Author information

Authors and Affiliations

  1. Japan Advanced Institute of Science and Technology - Hokuriku, Tatsunokuchi, 923-12, Ishikawa, Japan

    TuBao Ho

  2. Institute of Information Technology, Hanoi, Vietnam

    TuBao Ho

Authors
  1. TuBao Ho
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Editor information

Norman Foo Randy Goebel

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© 1996 Springer-Verlag Berlin Heidelberg

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Ho, T. (1996). Combining views on concepts in unsupervised concept learning. In: Foo, N., Goebel, R. (eds) PRICAI'96: Topics in Artificial Intelligence. PRICAI 1996. Lecture Notes in Computer Science, vol 1114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61532-6_29

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  • DOI: https://doi.org/10.1007/3-540-61532-6_29

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61532-3

  • Online ISBN: 978-3-540-68729-0

  • eBook Packages: Springer Book Archive

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