Knowledge Granulation and Uncertainly Measure of Incomplete Information System Based on Dominance Relation

Author

Chen Jian-cheng ; Tu Ang-Yan

Author_Institution

Dept. of Comput., Zhejiang Ind. Polytech. Coll., Shaoxing, China

fYear

2009

fDate

19-20 Dec. 2009

Firstpage

1

Lastpage

5

Abstract

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.

Keywords

information systems; knowledge acquisition; rough set theory; dominance relation; incomplete information system; knowledge acquisition; knowledge granulation; knowledge indiscernibility; real life data; rough entropy; uncertainty; Artificial intelligence; Computer industry; Educational institutions; Entropy; Heuristic algorithms; Industrial relations; Information systems; Knowledge acquisition; Measurement uncertainty; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4994-1

Type

conf

DOI

10.1109/ICIECS.2009.5362863

Filename

5362863