@ARTICLE { Rsds2465,
author = {Pawlak, Zdzislaw}, 
title = {Flow Graphs and Data Mining}, 
booktitle = {T. Rough Sets}, 
journal = {Transactions on Rough Sets}, 
number = 	{(no. III)}, 
volume = 3, 
pages = {1-36}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
year = 2005, 
url = {http://www.springer.de}, 
issn = {0302-9743}, 
isbn = {3-540-25998-8}, 
abstract = {In this paper we propose a new approach to data mining and knowledge discovery based on information flow distribution in a flow graph. Flow graphs introduced in this paper are different from those proposed by Ford and Fulkerson for optimal flow analysis and they model flow distribution in a network rather than the optimal flow which is used for information flow examination in decision algorithms. It is revealed that flow in a flow graph is governed by Bayes' rule, but the rule has an entirely deterministic interpretation without referring to its probabilistic roots. Besides, a decision algorithm induced by a flow graph and dependency between conditions and decisions of decision rules is introduced and studied, which is used next to simplify decision algorithms.}, 
keywords = {flow graph, data mining, knowledge discovery, decision algorithms, }, 
}