@ARTICLE { Rsds1217,
author = {Yao, Yiyu}, 
title = {Probabilistic approaches to rough sets}, 
journal = {Expert Systems}, 
number = 	{(no. 5)}, 
volume = 20, 
pages = {287-297}, 
publisher = {Kluwer Academic Publishers}, 
address = {Dordrecht, The Netherlands}, 
year = 2003, 
abstract = {Probabilistic approaches to rough sets in granulation, approximation and rule induction are reviewed. The Shannon entropy function is used to quantitatively characterize partitions of a universe. Both algebraic and probabilistic rough set approximations are studied. The probabilistic approximations are defined in a decision-theoretic framework. The problem of rule induction, a major application of rough set theory, is studied in probabilistic and information-theoretic terms. Two types of rules are analyzed: the local, low order rules, and the global, high order rules.}, 
keywords = {rough set approximations, granular computing, decision-theoretic rough set model, rule induction, }, 
}