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Some New Measures of k-Specificity

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Advances in Artificial Intelligence (CAEPIA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9868))

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Abstract

Measures of k-specificity are generalizations of Yager’s measures of specificity to measure the tranquility when choosing k elements from the universe of discourse.

In this paper some new examples of measures of k-specificity are proposed and compared.

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References

  1. Garmendia, L., González del Campo, R., Yager, R.R.: Recursively spreadable and reductible measures of specificity. Inf. Sci. 326, 270–277 (2016)

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  5. Yager, R.R.: Measures of specificity. In: Kaynak, O., Zadeh, L.A., Türkşen, B., Rudas, I.J. (eds.) Computational Intelligence: Soft Computing and Fuzzy-Neuro Integration wiht Applications. NATO ASI Series. Series F: Computer and Systems Sciences, vol. 162, pp. 94–113. Springer, Heidelberg (1998)

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Author information

Authors and Affiliations

  1. Universidad Complutense de Madrid, Madrid, Spain

    José Luis González Sánchez, Ramón González del Campo & Luis Garmendia

Authors
  1. José Luis González Sánchez
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  2. Ramón González del Campo
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  3. Luis Garmendia
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Corresponding author

Correspondence to José Luis González Sánchez .

Editor information

Editors and Affiliations

  1. Artificial Intelligence Center, University of Oviedo, Gijón, Spain

    Oscar Luaces

  2. University of Castilla-La Mancha , Albacete, Spain

    José A. Gámez

  3. Public University of Navarre , Pamplona, Spain

    Edurne Barrenechea

  4. Universidad Pablo de Olavide , Sevilla, Spain

    Alicia Troncoso

  5. Public University of Navarre , Pamplona, Navarra, Spain

    Mikel Galar

  6. University of Salamanca , Salamanca, Spain

    Héctor Quintián

  7. University of Salamanca , Salamanca, Spain

    Emilio Corchado

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© 2016 Springer International Publishing Switzerland

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González Sánchez, J.L., González del Campo, R., Garmendia, L. (2016). Some New Measures of k-Specificity. In: Luaces , O., et al. Advances in Artificial Intelligence. CAEPIA 2016. Lecture Notes in Computer Science(), vol 9868. Springer, Cham. https://doi.org/10.1007/978-3-319-44636-3_46

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  • DOI: https://doi.org/10.1007/978-3-319-44636-3_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44635-6

  • Online ISBN: 978-3-319-44636-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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