An object-relational neural network database type

Authors:
Erich Schikuta;Paul Glantschnig
Affiliations:
Department of Business and Knowledge Engineering, University of Vienna, Vienna, Austria;Department of Business and Knowledge Engineering, University of Vienna, Vienna, Austria
Venue:
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Year:
2007

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Abstract

A framework for the conceptual and physical integration of neural networks into object-relational database systems is presented. The neural network 'meta model', as the neural network paradigms, the static and dynamic properties, and the pattern description, is realized by a collection of objects, relations and dependencies between them. The specific network objects (the 'ortho' networks) are objects in these relations. A handling scheme for the application data set, as input, output and training information, stored in the relational database together with the neural networks is depicted. Finally the implementation of the new NeuroOracle system based on the proposed framework is presented.