Title: An extension of context model for representing vague knowledge
Authors: Van-Nam Huynh; Sadaaki Miyamoto; Yoshiteru Nakamori
School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa 923-1292, Japan.
Department of Risk Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan.
School of Knowledge Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa 923-1292, Japan
Abstract: In this paper, a framework for representing vague knowledge based on the notion of context model introduced by Gebhardt and Kruse (1993) is discussed. From a concept analysis point of view, it has been shown that the context model can be semantically considered as a data model for fuzzy concept analysis (Huynh et al., 2004). From a decision analysis point of view, in order to deal with the problem of synthesis of vague evidence linguistically provided by experts in some situations of decision analysis, the notions of context-dependent vague characteristics and fuzzy context model will be introduced. It is shown that each context-dependent vague characteristic within fuzzy context model directly induces a uncertainty measure of type 2 interpreted as 'vague' belief function, which is inferred from vague evidence expressed linguistically.
Keywords: context modelling; Dempster-Shafer theory; fuzzy context models; vague knowledge; uncertainty measures; type 2; vagueness.
Int. J. of Reasoning-based Intelligent Systems, 2012 Vol.4, No.3, pp.171 - 179
Available online: 16 Nov 2012