Analysis of interval-valued decision formal contexts

Article type: Research Article

Authors: Wang, Hong^* | Cui, Pin-Zhi

Affiliations: College of Mathematics and Computer Science, Shan’xi Normal University, Linfen, Shanxi, P.R. China

Correspondence: [*] Corresponding author. Hong Wang, College of Mathematics and Computer Science, Shan’xi Normal University, Linfen, Shanxi 041004, P.R. China. Tel.: +86 13835726593; E-mail: [email protected].

Abstract: This study investigates a novel approach to knowledge reduction in interval-valued decision formal contexts. Applying rule acquisition, we formulate a new framework of knowledge reduction for interval-valued decision formal contexts and the presented framework can be applicable to any interval-valued decision formal contexts. Based on this reduction method, more compact decision rules that can imply all of those derived from the initial interval-valued decision formal contexts in the form of implication rules are obtained. Furthermore, a corresponding reduction method is developed by constructing a discernibility matrix and its associated Boolean function.

Keywords: Interval-valued decision formal contexts, large interval-valued concept lattices, knowledge reduction, rule acquisition

DOI: 10.3233/IFS-151635

Journal: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1565-1574, 2015