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Toward Rough Knowledge Bases with Quantitative Measures

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Rough Sets and Current Trends in Computing (RSCTC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3066))

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Abstract

We present a language for defining new rough relations from given decision tables and we show how to query relations defined in this way. The language provides a uniform formalism for expressing rough data together with background knowledge, and for capturing well-known techniques such as the variable precision rough set model. Its essential feature is the use of quantitative measures, such as support, strength and accuracy.

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Author information

Authors and Affiliations

  1. Dept. of Science and Technology, Linköping University, S 601 74, Norrköping, Sweden

    Aida Vitória

  2. Centro de Inteligência Artificial (CENTRIA), Dept. Informática, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516, Caparica, Portugal

    Carlos Viegas Damásio

  3. Dept. of Computer and Information Science, Linköping University, S 581 83, Linköping, Sweden

    Jan Małuszyński

Authors
  1. Aida Vitória
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  2. Carlos Viegas Damásio
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  3. Jan Małuszyński
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Editor information

Editors and Affiliations

  1. Shimane University, 89-1 Enya-cho Izumo, 6938501, Shimane, Japan

    Shusaku Tsumoto

  2. Systems Research Institute, Polish Academy of Sciences, 01-447, Warsaw, Poland

    Roman Słowiński

  3. The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden

    Jan Komorowski

  4. Institute of Computer Science, Polish Academy of Sciences, 01–237, Warsaw, Poland

    Jerzy W. Grzymała-Busse

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© 2004 Springer-Verlag Berlin Heidelberg

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Vitória, A., Damásio, C.V., Małuszyński, J. (2004). Toward Rough Knowledge Bases with Quantitative Measures. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds) Rough Sets and Current Trends in Computing. RSCTC 2004. Lecture Notes in Computer Science(), vol 3066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25929-9_17

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  • DOI: https://doi.org/10.1007/978-3-540-25929-9_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22117-3

  • Online ISBN: 978-3-540-25929-9

  • eBook Packages: Springer Book Archive

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