Inference Bayesian Network for Multi-topographic neural network communication: a case study in documentary data

Shadi Al Shehabi 1 Jean-Charles Lamirel 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : In this paper we present an original approach consisting in assimilating the behavior of the MultiSOM model, whose core model represents a significant extension of the classical Kohonen SOM model, to the one model of a Bayesian inference network. This approach is used both for validating the MultiSOM inter-map communication principles and for enhancing the accuracy of the probabilistic correlation computation mode that is already provided by the model In a complementary way, our approach also led us to prove that a neural multi-map model provided with unsupervised learning might well behave as a Bayesian inference network in which the estimation of posterior probabilities becomes a simple process only using prior similarity measures.
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Communication dans un congrès
International Conference on Information and Communication Technologies: from Theory to Applications - ICTTA 2004, 2004, Damascus, Syria, 6 p, 2004
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https://hal.inria.fr/inria-00099927
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Soumis le : mardi 26 septembre 2006 - 10:10:18
Dernière modification le : jeudi 11 janvier 2018 - 06:19:48
Document(s) archivé(s) le : mercredi 29 mars 2017 - 13:10:41

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Shadi Al Shehabi, Jean-Charles Lamirel. Inference Bayesian Network for Multi-topographic neural network communication: a case study in documentary data. International Conference on Information and Communication Technologies: from Theory to Applications - ICTTA 2004, 2004, Damascus, Syria, 6 p, 2004. 〈inria-00099927〉

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