@ARTICLE { Rsds3602,
author = {Guan, Ziyu and Bell, David A. and Guan, Ji-wen}, 
title = {Matrix computation for information systems}, 
journal = {Information Sciences: An International Journal}, 
number = 	{(no. 1-4)}, 
volume = 131, 
pages = {129-156}, 
publisher = {Elsevier Science Inc.}, 
address = {Amsterdam, The Netherlands}, 
month = {January}, 
year = 2001, 
issn = {0020-0255}, 
abstract = {Rough set theory is a new mathematical tool to deal with vagueness and uncertainty. We need a practical approach to apply the theory. Some problems (for example, the general problem of finding all reducts) are NP-hard. Thus, it is important to investigate computational methods for the theory. In rough set theory, a table called information system or database is used as a special kind of formal language to represent knowledge. We discuss matrix computation for information systems in this paper. Matrices can be computed intuitively and efficiently. A matrix can be seen as an internal representation of equivalence relations. Furthermore, matrix computation "min" implements the operation "AND" on equivalence relations, and the matrix relation "less-than-or-equals, slant" corresponds to the relation "subset of or equal to". Finally, this operation on matrices is carried out for its elements individually. So it can be implemented in parallel mode to get concurrently the "AND" matrix.}, 
keywords = {intelligent information systems, database and knowledge base systems, }, 
}