@INPROCEEDINGS { Rsds4139,
author = {Zhang, Huijie and Qi, Changsong and Liu, Huawen and Sun, Jigui}, 
title = {An Interpretation of Flow Graphs by Granular Computing}, 
booktitle = {Rough Sets and Current Trends in Computing}, 
conference = {Rough Sets and Current Trends in Computing}, 
series =  = {Lecture Notes in Artificial Intelligence}, 
volume = 4259, 
pages = {448--457}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
month = {November}, 
year = 2006, 
editor = {Greco, Salvatore and Hirano, Shoji and Inuiguchi, Masahiro and Miyamoto, Sadaaki and Nguyen,  Hung Son and Slowinski, Roman W.}, 
issn = {0302-9743}, 
isbn = {978-3-540-47693-1}, 
abstract = {Flow graph (FG) is a unique approach in data mining and data analysis mainly in virtue of its well-structural characteristics of network, which is naturally consistent with granular computing (GrC). Meanwhile, GrC provides us with both structured thinking at the philosophical level and structured problem solving at the practical level. The main objective of the present paper is to develop a simple and more concrete model for flow graph using GrC. At first, FG will be mainly discussed in three aspects under GrC, namely, granulation of FG, some relationships and operations of granules. Moreover, as one of advantages of this interpretation, an efficient approximation reduction algorithm of flow graph is given under the framework of GrC.}, 
keywords = {flow graph, granular computing, data mining, }, 
}