Rule reductions of decision formal context based on mixed information

Abstract

Formal concept analysis is an effective tool in knowledge discovery. Nonetheless, it ignores the negative information, especially in rule extraction. And some applications require to mix positive and negative information for management and representation explicitly. This paper discusses an emerging method for rule reduction in formal contexts with mixed information by presenting a mixed decision rule based on a mixed concept lattice. Based on the mixed concept model, we discuss the relationships between mixed concept, formal concept and three-way concept, respectively. In this paper, to fully consider the mixed information, we construct a mixed decision rule. Moreover, to reduce the redundance of rule, a novel approach for weak-basis from the viewpoint of granular computing is designed to selection the core mixed decision rules and necessary mixed decision rules. Finally, the comparison of mixed decision rules and three-way decision rules is perfectly discussed, and case study is presented for the difference.