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

Article type: Research Article

Authors: Suraj, Zbigniew

Affiliations: Institute of Mathematics, Pedagogical University, Rzeszów, Poland. email: suraj@prz.rzeszow.pl

Note: [] This work has been supported by the grant #8T11C01011 from the State Committee for Scientific Research in Poland

Abstract: 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 to automatic data models discovery from experimental tables with Petri nets as models for concurrency.

Keywords: data mining, system decomposition, rough sets, concurrent models, laws discovery from experimental data

DOI: 10.3233/FI-1996-283411

Journal: Fundamenta Informaticae, vol. 28, no. 3-4, pp. 353-376, 1996