In Pursuit of Patterns in Data Reasoning from Data The Rough Set Way
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
Granular computing using information tables
Data mining, rough sets and granular computing
Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing: 10th International Conference, RSFDGrC 2005, Regina, Canada, August 31 - September 3, 2005, ... / Lecture Notes in Artificial Intelligence)
Flow graphs and decision algorithms
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
The quotient space theory of problem solving
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Association rule mining: models and algorithms
Association rule mining: models and algorithms
An extension of pawlak's flow graphs
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
The computational complexity of inference using rough set flow graphs
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Transactions on Rough Sets III
Inference and Reformation in Flow Graphs Using Granular Computing
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Knowledge discovery by rough sets mathematical flow graphs and its extension
AIA '08 Proceedings of the 26th IASTED International Conference on Artificial Intelligence and Applications
Interpretation of extended Pawlak flow graphs using granular computing
Transactions on rough sets VIII
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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.