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Outlier Mining in Rule-Based Knowledge Bases

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Rough Sets and Current Trends in Computing (RSCTC 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7413))

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Abstract

The paper presents the problem of outlier detection in rule-based knowledge bases. Unusual (rare) rules, regarded here as deviation, should be the subject of experts’ and knowledge engineers’ analysis because they allow influencing on the efficiency of inference in decision support systems. A different approaches to find outliers and the results of the experiments are presented.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, University of Silesia, ul. Bȩdzińska 39, 41-200, Sosnowiec, Poland

    Agnieszka Nowak-Brzezińska

Authors
  1. Agnieszka Nowak-Brzezińska
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Regina, S4S 0A2, Regina, SK, Canada

    JingTao Yao

  2. School of Information Science and Technology, Southwest Jiaotong University, 610031, Chengdu, P.R. China

    Yan Yang

  3. Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965, Poznan, Poland

    Roman Słowiński

  4. Faculty of Economics, University of Catania, Corso Italia, 55, 95129, Catania, Italy

    Salvatore Greco

  5. School of Management and Engineering, Nanjing University, 210093, Nanjing, Jiangsu, P.R. China

    Huaxiong Li

  6. Machine Intelligence Unit, Indian Statistical Institute (ISI), 700108, Kolkata, India

    Sushmita Mitra

  7. Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008, Warsaw, Poland

    Lech Polkowski

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© 2012 Springer-Verlag Berlin Heidelberg

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Nowak-Brzezińska, A. (2012). Outlier Mining in Rule-Based Knowledge Bases. In: Yao, J., et al. Rough Sets and Current Trends in Computing. RSCTC 2012. Lecture Notes in Computer Science(), vol 7413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32115-3_24

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  • DOI: https://doi.org/10.1007/978-3-642-32115-3_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32114-6

  • Online ISBN: 978-3-642-32115-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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