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http://dx.doi.org/10.7236/JIIBC.2014.14.2.107

Uncertainty Measurement of Incomplete Information System based on Conditional Information Entropy  

Park, Inkyoo (Dept. of Computer Science, Joongbu University)
Publication Information
The Journal of the Institute of Internet, Broadcasting and Communication / v.14, no.2, 2014 , pp. 107-113 More about this Journal
Abstract
The derivation of optimal information from decision table is based on the concept of indiscernibility relation and approximation space in rough set. Because decision table is more likely to be susceptible to the superposition or inconsistency in decision table, the reduction of attributes is a important concept in knowledge representation. While complete subsets of the attribute's domain is considered in algebraic definition, incomplete subsets of the attribute's domain is considered in information-theoretic definition. Therefore there is a marked difference between algebraic and information-theoretic definition. This paper proposes a conditional entropy using rough set as information theoretical measures in order to deduct the optimal information which may contain condition attributes and decision attribute of information system and shows its effectiveness.
Keywords
Rough Set; Indiscernibility Relation; Entropy; Uncertainty; Information System;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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