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Artificial Learning approaches for the next generation web: part I

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Author(s): J.R. Gutiérrez–Pulido | E.M. Ramos–Michel | M.E. Cabello–Espinosa | S. Legrand | D. Elliman

Journal: Ingeniería Investigación y Tecnologia
ISSN 1405-7743

Volume: 9;
Issue: 1;
Start page: 67;
Date: 2008;
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Keywords: : Ontology creation process | semantic Web approach | clustering | pattern recognition | artificial neural networks

ABSTRACT
In this paper we present a review of learning approaches that have been used by the research community to carry out clustering and pattern recognition tasks. Artificial neural net works are then introduced by presenting existing topologies, learning algorithms, and recall approaches . Finally, the relation of these techniques with the semantic web ontology creation process, as we envision it, is introduced. In part II of this paper, an artificial learning approach based on Self–Organizing Maps (SOM) that we have proposed as an ontology learning tool for assembling and visualizing ontology components from a specific domain for the semantic web is introduced.
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