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1995
ACM

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

12 years 3 months ago
Discovery of Concurrent Data Models from Experimental Tables: A Rough Set Approach
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 roles 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. Key words: data mining, system decomposition, rough sets, concurrent models
Andrzej Skowron, Zbigniew Suraj
Added 26 Aug 2010
Updated 26 Aug 2010
Type Conference
Year 1995
Where KDD
Authors Andrzej Skowron, Zbigniew Suraj
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