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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 99))

Abstract

Our research concerns psychometric data coming from the Minnesota Multiphasic Personality Inventory (MMPI) test. MMPI is used to count the personality-psychometric dimensions which help specialists in diagnosis of mental diseases. In this paper, we present a part of the Copernicus system – the tool for computer-aided diagnosis of mental diseases based on personality inventories. This part is devoted to the rule-based analysis of the MMPI data expressed in the form of the so-called profiles. The paper characterizes the knowledge base embodied in Copernicus which can be used for the rule-based analysis of the patients’ MMPI data as well as the functionality of the designed tool.

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References

  1. Bazan, J.G., Nguyen, H.S., Nguyen, S.H., Synak, P., Wroblewski, J.: Rough set algorithms in classification problem. In: Polkowski, L., Tsumoto, S., Lin, T.Y. (eds.) Rough Set Methods and Applications, pp. 49–88. Physica-Verlag, Heidelberg (2000)

    Google Scholar 

  2. Bazan, J.G., Szczuka, M.S.: The rough set exploration system. In: Peters, J.F., Skowron, A. (eds.) Transactions on Rough Sets III, pp. 37–56. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  3. Cios, K., Pedrycz, W., Swiniarski, R.W., Kurgan, L.A.: Data mining. A knowledge discovery approach. Springer, Heidelberg (2007)

    MATH  Google Scholar 

  4. Dahlstrom, W., Welsh, G., Dahlstrom, L.: An MMPI handbook, vol. 1-2. University of Minnesota Press, Minneapolis (1986)

    Google Scholar 

  5. Grzymala-Busse, J.: A new version of the rule induction system LERS. Fundamenta Informaticae 31, 27–39 (1997)

    MATH  Google Scholar 

  6. Hippe, Z.S.: Machine learning – a promising strategy for business information processing? In: Abramowicz, W. (ed.) Business Information Systems, Academy of Economics Editorial Office, Poznan, pp. 603–622 (1997)

    Google Scholar 

  7. Knap, M.: Research on new algorithms for decision trees generation. Ph. D. Thesis, AGH University of Science and Technology, Krakow (2009) (in Polish)

    Google Scholar 

  8. Paja, W., Hippe, Z.S.: Feasibility studies of quality of knowledge mined from multiple secondary sources. I. Implementation of generic operations. In: Klopotek, M., Wierzchon, S., Trojanowski, K. (eds.) Intelligent Information Processing and Web Mining, pp. 461–465. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  9. Pawlak, Z.: Rough Sets. Theoretical aspects of reasoning about data. Kluwer Academic Publishers, Dordrecht (1991)

    Book  MATH  Google Scholar 

  10. Witten, I.H., Frank, E.: Data mining: practical machine learning tools and techniques. Morgan Kaufmann, San Francisco (2005)

    MATH  Google Scholar 

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Gomuła, J., Paja, W., Pancerz, K., Szkoła, J. (2012). Rule-Based Analysis of MMPI Data Using the Copernicus System. In: Hippe, Z.S., Kulikowski, J.L., Mroczek, T. (eds) Human – Computer Systems Interaction: Backgrounds and Applications 2. Advances in Intelligent and Soft Computing, vol 99. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23172-8_14

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  • DOI: https://doi.org/10.1007/978-3-642-23172-8_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23171-1

  • Online ISBN: 978-3-642-23172-8

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