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Cluster detection algorithm in neural networks

Abstract : Complex networks have received much attention in the last few years, and reveal global properties of interacting systems in domains like biology, social sciences and technology. One of the key feature of complex networks is their clusterized structure. Most methods applied to study complex networks are based on undirected graphs. However, when considering neural networks, the directionality of links is fundamental. In this article, a method of cluster detection is extended for directed graphs. We show how the extended method is more efficient to detect a clusterized structure in neural networks, without significant increase of the computational cost.
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Contributor : David Meunier <>
Submitted on : Tuesday, May 16, 2006 - 7:20:57 PM
Last modification on : Monday, June 22, 2020 - 2:02:01 PM
Document(s) archivé(s) le : Saturday, April 3, 2010 - 11:23:52 PM


  • HAL Id : hal-00069268, version 1



David Meunier, Hélène Paugam-Moisy. Cluster detection algorithm in neural networks. 2006, pp.19-24. ⟨hal-00069268⟩



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