Knowledge Granulation and Uncertainly Measure of Incomplete Information System Based on Dominance Relation
Jian-Cheng Chen, Angyan Tu · 2009
Real-life data are frequently imperfect: data may be affected by uncertainty, vagueness, and incompleteness. In this paper, based on dominance relation, the concepts of knowledge granulation and rough entropy of imcomplete information system (include missing data and imprecise data) are defined, their important properties are given, and the relationship between those concepts is established. These results will be helpful for measuring the indiscernibility of knowledge, and have instructive significance for studying for knowledge acquisition in imcomplete information system.