Extended Pawlak's Flow Graphs and Information Theory

Authors:
Huawen Liu;Jigui Sun;Huijie Zhang;Lei Liu
Affiliations:
College of Computer Science and Technique, Jilin University, Changchun, P.R. China 130012;College of Computer Science and Technique, Jilin University, Changchun, P.R. China 130012;Department of Computer Science, Northeast Normal University, Changchun, P.R. China 130021;College of Computer Science and Technique, Jilin University, Changchun, P.R. China 130012 and Key Laboratory of Symbolic Computation and Knowledge Engineering, of Ministry of Education, Changchun, ...
Venue:
Transactions on Computational Science V
Year:
2009

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Abstract

Flow graph is an effective and graphical tool of knowledge representation and analysis. It explores dependent relation between knowledge in the form of information flow quantity. However, the quantity of flow can not exactly represent the functional dependency between knowledge. In this paper, we firstly present an extended flow graph using concrete information flow, and then give its interpretation under the framework of information theory. Subsequently, an extended flow graph generation algorithm based on the significance of attribute is proposed in virtue of mutual information. In addition, for the purpose of avoiding over-fitting and reducing store space, a reduction method about this extension using information metric has also been developed.