@INPROCEEDINGS { Rsds3275,
author = {Skowron, Andrzej and Stepaniuk, Jaroslaw and Peters, James F.}, 
title = {Extracting Patterns Using Information Granules}, 
booktitle = {Proceedings of International Workshop on Rough Set Theory and Granular Computing (RSTGC-2001)}, 
conference = {International Workshop on Rough Set Theory and Granular Computing}, 
series =  = {Bulletin of International Rough Set Society}, 
volume = 5, 
pages = {135--142}, 
month = {May}, 
year = 2001, 
editor = {Hirano, Shoji and Inuiguchi, Masahiro and Tsumoto, Shusaku}, 
issn = {1346-0013}, 
abstract = {The paper introduces a step in developing a foundation for approximate reasoning from experimental data to conclusions in natural language. We consider schemes of approximate reasoning consisting of information granules from different information sources. By tuning the parameters of schemes, the information granules representing patterns relevant to given tasks can be generated. Approximation granules, rough-fuzzy granules and granule decomposition based on background knowledge are briefly considered in this paper. The contribution of this presentation of an approach to obtaining relevant patterns from parameterized schemes of information granule construction.}, 
keywords = {rough set theory (RST), information granulation, pattern, granular computing, schemes of approximate reasoning, decomposition, information fusion, }, 
}