@INPROCEEDINGS { Rsds4437,
author = {Nguyen, Hung Son}, 
title = {Learning Concept Approximation from the Pair-wise Space}, 
booktitle = {Proceedings of the Workshop on Concurrency, Specification and Programming (CS&P'2007)}, 
volume = 2, 
pages = {446--451}, 
publisher = {Warsaw University}, 
address = {Warsaw, Poland}, 
month = {September}, 
year = 2007, 
editor = {Czaja, Ludwik}, 
isbn = {978-83-88374-28-9}, 
abstract = {In this paper we investigate the problem of searching for approximation of relations from the pairwise space, i.e., the set of pairs of objects. We show that this method is the basic component of many compound tasks. We present a novel rough set based approach tho discovering useful patterns from nonstandard and complex data for which the standard inductive learning methodology fails. The proposed solution is based on a two-layered learning algorithm. We consider a few representive examples to demonstrate the power of the proposed methodology.}, 
keywords = {rough sets, relation approximation, knowledge discovery, }, 
}