Title :
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
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;
Conference_Titel :
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4994-1
DOI :
10.1109/ICIECS.2009.5362863