Knowledge Visualization Using Optimized General Logic Diagrams




Śnieżyński, Bartłomiej
Szymacha, Robert
Michalski, Ryszard S.

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Knowledge Visualizer (KV) uses a General Logic Diagram (GLD) to display examples and/or various forms of knowledge learned from them in a planar model of a multi-dimensional discrete space. Knowledge can be in different forms, for example, decision rules, decision trees, logical expressions, clusters, classifiers, and neural nets with discrete input variables. KV is implemented as a module of the inductive database system VINLEN, which integrates a conventional database system with a range of inductive inference and data mining capabilities. This paper describes briefly the KV module and then focuses on the problem of arranging attributes that span the diagram in a way that leads to the most readable rule visualization in the diagram. This problem has been solved by applying a simulated annealing.



Knowledge visualization, General logic diagrams (GLD), Diagram optimization, Machine learning


Śnieżyński, B., Szymacha, R. and Michalski, R. S., "Knowledge Visualization Using Optimized General Logic Diagrams," Proceedings of the Intelligent Information Processing and Web Mining Conference, IIPWM 05, Gdansk, Poland, June 13-16, 2005.