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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/4998

Title: A context model for fuzzy concept analysis based upon modal logic
Authors: Huynh, V. N.
Nakamori, Y.
Ho, T. B.
Resconi, G.
Keywords: Context model
modal logic
fuzzy concept
membership function
Issue Date: 2004-03-22
Publisher: Elsevier
Magazine name: Information Sciences
Volume: 160
Number: 1-4
Start page: 111
End page: 129
DOI: 10.1016/j.ins.2003.08.010
Abstract: In this paper we present interesting relationships between the context model, modal logic and fuzzy concept analysis. It has been shown that the context model proposed by Gebhardt and Kruse (1993) can be semantically extended and considered as a data model for fuzzy concept analysis within the framework of the meta-theory developed by Resconi et al. in 1990s. Consequently, the context model provides a practical framework for constructing membership functions of fuzzy concepts and gives the basis for a theoretical justification of suitably use of well-known t-norm based connectives such as min-max and product-sum rules in applications. Furthermore, an interpretation of mass assignments of fuzzy concepts within the context model is also established.
Rights: NOTICE: This is the author's version of a work accepted for publication by Elsevier. V. N. Huynh, Y. Nakamori, T. B. Ho and G. Resconi, Information Sciences, 160(1-4), 2004, 111-129, http://dx.doi.org/10.1016/j.ins.2003.08.010
URI: http://hdl.handle.net/10119/4998
Material Type: author
Appears in Collections:a10-1. 雑誌掲載論文 (Journal Articles)

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