DocumentCode
424087
Title
A new uncertainty measure of knowledge in incomplete information systems
Author
Li, Ren-Pu ; Huang, Dao
Author_Institution
Inst. of Inf., East China Univ. of Sci. & Technol., Shanghai, China
Volume
3
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
1486
Abstract
In this paper, the problem of estimating the uncertainty of knowledge in incomplete information systems is studied. Some limitations of the previous measure - rough entropy are first analyzed and then a new measure called incomplete entropy is presented. Compared with rough entropy, incomplete entropy can be used in both incomplete and complete information system and has more precise estimation for uncertainty of knowledge in incomplete information systems.
Keywords
entropy; estimation theory; information systems; knowledge based systems; rough set theory; uncertainty handling; incomplete entropy; incomplete information systems; knowledge uncertainty estimation; rough entropy analysis; Algorithm design and analysis; Cybernetics; Data mining; Entropy; Information analysis; Information systems; Machine learning; Measurement uncertainty; Set theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1382008
Filename
1382008
Link To Document