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Knowledge discovery by rough sets mathematical flow graphs and its extension. (English) Zbl 1157.68453
Gammerman, A. (ed.), Artificial intelligence and applications. Machine learning. As part of the 26th IASTED international multi-conference on applied informatics. Calgary: International Association of Science and Technology for Development (IASTED); Anaheim, CA: Acta Press (ISBN 978-0-88986-710-9/CD-ROM). 340-345 (2008).
Summary: 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.
For the entire collection see [Zbl 1154.68012].

MSC:
68T30 Knowledge representation
68R10 Graph theory (including graph drawing) in computer science
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