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Similarity Measure Construction Using Fuzzy Entropy and Distance Measure

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Computational Intelligence (ICIC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4114))

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Abstract

The similarity measure is derived using fuzzy entropy and distance measure. By the relations of fuzzy entropy, distance measure, and similarity measure, we first obtain the fuzzy entropy. And with both fuzzy entropy and distance measure, similarity measure is obtained. We verify that the proposed measure become the similarity measure.

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© 2006 Springer-Verlag Berlin Heidelberg

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Lee, SH., Kim, JM., Choi, YK. (2006). Similarity Measure Construction Using Fuzzy Entropy and Distance Measure. In: Huang, DS., Li, K., Irwin, G.W. (eds) Computational Intelligence. ICIC 2006. Lecture Notes in Computer Science(), vol 4114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37275-2_120

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  • DOI: https://doi.org/10.1007/978-3-540-37275-2_120

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37274-5

  • Online ISBN: 978-3-540-37275-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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