Abstract
The paper proposes new definitions of (im)precision measures for type-2 fuzzy sets representing linguistic terms and linguistically quantified statements. The proposed imprecision measures extend similar concepts for traditional (type-1) fuzzy sets, cf. [1,2]. Applications of those new concepts to linguistic summarization of data are proposed in the context of the problem statement of finding the best summaries.
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Niewiadomski, A. (2008). Imprecision Measures for Type-2 Fuzzy Sets: Applications to Linguistic Summarization of Databases. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science(), vol 5097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69731-2_28
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DOI: https://doi.org/10.1007/978-3-540-69731-2_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69572-1
Online ISBN: 978-3-540-69731-2
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