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Sloppy modeling

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Knowledge Representation and Organization in Machine Learning

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 347))

Abstract

In this paper, I would like to present a unifying view on knowledge acquisition and machine learning. In this view, knowledge acquisition systems should support the user in doing the modeling of a domain, and machine learning systems are those which perform part of the modeling autonomously. Taking the notion of modeling as the central point, some aspects of modeling along with their impact for building knowledge acquisition and machine learning systems are discussed. In particular, reversability at all levels is claimed to be supported by the system.

As a result of the unifying view, a new way of integrating machine learning into knowledge acquisition is presented and exemplified by the system BLIP, a system which supports the user in domain modeling and at the same time takes part of the work off the user's back by modeling autonomously. Since all decisions regarding the model can be revised and revision is supported by the system, we call this way of modeling "sloppy modeling"; the user may start with a sloppy model which can be revised and enhanced.

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  1. Technical University Berlin Project Group KIT, Sekr. FR 5-8 Franklinstr.28/29, D-1000, Berlin 10

    Katharina Morik

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  1. Katharina Morik
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© 1989 Springer-Verlag Berlin Heidelberg

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Morik, K. (1989). Sloppy modeling. In: Morik, K. (eds) Knowledge Representation and Organization in Machine Learning. Lecture Notes in Computer Science, vol 347. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0017219

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  • DOI: https://doi.org/10.1007/BFb0017219

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-50768-0

  • Online ISBN: 978-3-540-46081-7

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