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

• Type: Conference
• Year: 1995
• Where: KDD
• Authors: Andrzej Skowron, Zbigniew Suraj
• Keywords: Data Mining, Data Models, Data Models Discovery, KDD 1995, Machine Discovery