@INPROCEEDINGS { Rsds3250,
author = {Machuca, Fernando and Millan, Marta}, 
title = {Using the Rough set theory to Exploit the Data Mining Potential in Relational Database Systems}, 
booktitle = {Joint Conference of Information Science}, 
pages = {344--347}, 
month = {March}, 
year = 1997, 
abstract = {We propose a new method for mining data capabilities in relational database systems in such a way as to fully exploit the relational and the rough set theory. We extend the relational algebra with a new operator called Rough Classifier. This operator generates an extended indiscernibility relation of the given attributes. In so doing, it also stores the fundamental information for mining data by retaining the subsets that participate in the calculus of the lower and upper approximations of a concept. We demonstrate that such a relation is an optimized and self-sufficient base for mining data by using the rough set theory. We show that this new operator achieves a high level of efficiency based on a classical group algorithm with slight modifications.}, 
keywords = {data mining, rough set theory (RST), knowledge discovery database, relational algebra, query optimization, query evaluation, }, 
}