Discovery of Concurrent Data Models from Experimental Tables: A Rough Set Approach

Andrzej Skowron, Warsaw University and Zbigniew Suraj, Pedagogical University, Poland

The main objective of machine discovery is the determination of relations between data and of data models. In the paper we describe a method for discovery of data models represented by concurrent systems from experimental tables. The basic step consists in a determination of rules which yield a decomposition of experimental data tables; the components are then used to define fragments of the global system corresponding to a table. The method has been applied for automatic data models discovery from experimental tables with Petri nets as models for concurrency.

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