@INPROCEEDINGS { Rsds2165,
author = {Yin, Ping and Lin, Tsau Young}, 
title = {Heuristically Fast Finding of the Shortest Reducts}, 
booktitle = {Rough Sets and Current Trends in Computing}, 
conference = {Rough Sets and Current Trends in Computing}, 
series =  = {Lecture Notes in Artificial Intelligence}, 
volume = 3066, 
pages = {465-470}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
month = {June}, 
year = 2004, 
editor = {Tsumoto, Shusaku and Slowinski, Roman W. and Komorowski, Jan and Grzymala-Busse, Jerzy W.}, 
issn = {0302-9743}, 
isbn = {3-540-22117-4}, 
abstract = {It is well known that finding the shortest reduct is NP hard. In this paper, we present an heuristic fast way of finding shortest relative reducts by exploring the specific nature of the input data. As a byproduct, we can show that the shortest relative reducts can be found in polynomial time, provided that we do know apriori that the lengths of the shortest reducts is bounded by a constant, that is, independent of the column size n. It should be noted that there are heuristic factors in the algorithm ("speeds" are not guaranteed) but the results, namely, the founded shortest reducts, are the precise answers.}, 
keywords = {data mining, rough set, reduct, granular computing, bitmap, }, 
}