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On a Rough Sets Based Data Mining Tool in Prolog: An Overview

  • Conference paper
Book cover Declarative Programming for Knowledge Management (INAP 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4369))

Abstract

RoughNon-deterministicInformation Analysis (RNIA) is a framework for handling rough sets based concepts, which are defined in not only DISs (DeterministicInformation Systems) but also NISs (Non-deterministicInformation Systems), on computers. RNIA is also recognized as a framework of data mining from uncertain tables. This paper focuses on programs in prolog, and briefly surveys a software tool for RNIA.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Aided Science, Faculty of Engineering, Kyushu Institute of Technology, Tobata, Kitakyushu, 804, Japan

    Hiroshi Sakai

Authors
  1. Hiroshi Sakai
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Editor information

Editors and Affiliations

  1. Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology, Iizuka, Fukuoka, Japan

    Masanobu Umeda

  2. Fraunhofer FIRST, Kekuléstr. 7, D-12489, Berlin, Germany

    Armin Wolf

  3. IF Computer Japan, 5-28-2 Sendagi, Bunkyo-ku, 113-0022, Tokyo, Japan

    Oskar Bartenstein

  4. Fraunhofer FIRST, Berlin,  

    Ulrich Geske

  5. Universität Würzburg, Am Hubland, 97074, Würzburg, Germany

    Dietmar Seipel

  6. Graduate School of Computer Science and Systems Engineering,, Kyushu Institute of Technology, Iizuka, Fukuoka, Japan

    Osamu Takata

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© 2006 Springer-Verlag Berlin Heidelberg

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Sakai, H. (2006). On a Rough Sets Based Data Mining Tool in Prolog: An Overview. In: Umeda, M., Wolf, A., Bartenstein, O., Geske, U., Seipel, D., Takata, O. (eds) Declarative Programming for Knowledge Management. INAP 2005. Lecture Notes in Computer Science(), vol 4369. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11963578_5

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  • DOI: https://doi.org/10.1007/11963578_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69233-1

  • Online ISBN: 978-3-540-69234-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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