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Multi‐level decomposition of probabilistic relations

Multi‐level decomposition of probabilistic relations Two methods of decomposition of probabilistic relations are presented in this paper. They consist of splitting relations (blocks) into pairs of smaller blocks related to each other by new variables generated in such a way so as to minimize a cost function which depends on the size and structure of the result. The decomposition is repeated iteratively until a stopping criterion is met. Topology and contents of the resulting structure develop dynamically in the decomposition process and reflect relationships hidden in the data. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Kybernetes Emerald Publishing

Multi‐level decomposition of probabilistic relations

Stanislaw Grygiel; Martin Zwick; Marek Perkowski
Kybernetes , Volume 33 (5/6): 14 – Jun 1, 2004
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Publisher
Emerald Publishing
Copyright
Copyright © 2004 Emerald Group Publishing Limited. All rights reserved.
ISSN
0368-492X
DOI
10.1108/03684920410533994
Publisher site
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Abstract

Two methods of decomposition of probabilistic relations are presented in this paper. They consist of splitting relations (blocks) into pairs of smaller blocks related to each other by new variables generated in such a way so as to minimize a cost function which depends on the size and structure of the result. The decomposition is repeated iteratively until a stopping criterion is met. Topology and contents of the resulting structure develop dynamically in the decomposition process and reflect relationships hidden in the data.

Journal

Kybernetes – Emerald Publishing

Published: Jun 1, 2004

Keywords: Cybernetics; Complexity theory; Probability calculations

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