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Communication Dans Un Congrès Année : 2015

A first attempt towards a fuzzy c-means for the linguistic 2-tuple model

Résumé

This paper deals with clustering analysis in a fuzzy linguistic environment. Clustering and fuzzy clustering are now commonly used for numerical and/or symbolic data. But what about linguistic data? Since decades, there are several computational models that deal with linguistic or semantic terms to describe imprecise systems and perform computing with words. One of them is now widely used: the fuzzy linguistic 2-tuple representation model. In this paper we lay the foundations of a fuzzy clustering for linguistic data expressed through fuzzy linguistic 2-tuples. We define the notion of distance between 3-D fuzzy linguistic 2- tuples that is central to the clustering problem. Then we propose a real case study to show the importance of clustering analysis for linguistic data.
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Dates et versions

hal-01192798 , version 1 (03-09-2015)

Identifiants

  • HAL Id : hal-01192798 , version 1

Citer

Marie E.C. Durand, Isis Truck. A first attempt towards a fuzzy c-means for the linguistic 2-tuple model. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2015), Aug 2015, Istanbul, Turkey. ⟨hal-01192798⟩
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