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Knowledge discovery by rough sets mathematical flow graphs and its extension
Author(s)
Chitchareon, Doungrat
Pattaraintakorn, Puntip
Date Issued
December 1, 2008
Type
Conference Paper
Abstract
Mathematical rough set theory has attracted both practical and theoretical researchers. A significant extension of rough set theory is called flow graphs. It is a knowledge representation in the form of information flow. Flow graph is a promising approach to analyze data flow, decision trees, decision rules, probability learning, etc. In this article, we present their connections to pertinent techniques and propose a new extension to association rules. Two new propositions are used to reveal the relationship between flow graphs and association rules. We conduct experiment on real-world data collected from POSN with the evaluation. We discuss some important properties of flow graphs, with examples throughout.
Citation
Proceedings of the IASTED International Conference on Artificial Intelligence and Applications Aia 2008, 340-345, 2008