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Data Mining for Fuzzy Relational Data Servers

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Theoretical Advances and Applications of Fuzzy Logic and Soft Computing

Part of the book series: Advances in Soft Computing ((AINSC,volume 42))

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Abstract

Methods of Perception-based Data Mining (Data Miners DM) for fuzzy relational data servers are considered in the article. The considering problems of DM are limited by problems of clustering and mining of dependences in the form of fuzzy rules because these problems are especially important in practice. The hybrid algorithm of fuzzy clustering and the way of use of a fuzzy inference system as a DM for fuzzy relational data is offered in the article.

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References

  1. Zadeh L.A., Nikravesh M. Perseption based intelligent decision systems. In: AINS; ONR Summer 2002 program Review, July 30-August 1, UCLA (2002)

    Google Scholar 

  2. Hoppner, F., et al.: Fuzzy Cluster Analysis. Wiley, Chichester (1999)

    Google Scholar 

  3. Pedrycz, W.: Knowledge-based Fuzzy Clustering, Wiley, New York (2005)

    Google Scholar 

  4. Batyrshin, I.Z., Sheremetov, L.B.: Perception based associations in time series data bases. In: NAFIS 2006, Canada, Montreal (2006)

    Google Scholar 

  5. Ghosh, R., et al.: A Hybrid clustering Algorithm using two level of abstraction. In: IFSA 2005, vol. 1, China, Beijing,, pp. 586–591 (2005)

    Google Scholar 

  6. Yarushkina, N., Semoushin, I.: A Soft Computing-based Integration Environment for Assessing the Performance of a Complex Enterprise. In: IFSA 2005, vol. III, China, Beijing, pp. 1430–1435 (2005)

    Google Scholar 

  7. Yarushkina, N.: A Soft Computing-based Integration Environment for financial analysis of a complex enterprise. In: BISCSE’2005, University of California, Berkeley, USA, pp. 67–68 (2005)

    Google Scholar 

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Authors and Affiliations

  1. 32, Severny Venets street, Ulyanovsk, 432001, Russia, UlSTU,  

    A. P. Velmisov, A. A. Stetsko & N. G. Yarushkina

Authors
  1. A. P. Velmisov
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  2. A. A. Stetsko
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  3. N. G. Yarushkina
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Editor information

Oscar Castillo Patricia Melin Oscar Montiel Ross Roberto Sepúlveda Cruz Witold Pedrycz Janusz Kacprzyk

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© 2007 Springer-Verlag Berlin Heidelberg

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Velmisov, A.P., Stetsko, A.A., Yarushkina, N.G. (2007). Data Mining for Fuzzy Relational Data Servers. In: Castillo, O., Melin, P., Ross, O.M., Sepúlveda Cruz, R., Pedrycz, W., Kacprzyk, J. (eds) Theoretical Advances and Applications of Fuzzy Logic and Soft Computing. Advances in Soft Computing, vol 42. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72434-6_23

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  • DOI: https://doi.org/10.1007/978-3-540-72434-6_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72433-9

  • Online ISBN: 978-3-540-72434-6

  • eBook Packages: EngineeringEngineering (R0)

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