On Graph Entropy Measures for Knowledge Discovery from Publication Network DataReportar como inadecuado

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1 HCI4MED - Research Unit Human-Computer Interaction for Medicine & Health Care 2 Human-Computer Interaction Center at RWTH Aachen University 3 Institute for Bioinformatics and Translational Research Tyrol

Abstract : Many research problems are extremely complex, making interdisciplinary knowledge a necessity; consequently cooperative work in mixed teams is a common and increasing research procedure. In this paper, we evaluated information-theoretic network measures on publication networks. For the experiments described in this paper we used the network of excellence from the RWTH Aachen University, described in 1. Those measures can be understood as graph complexity measures, which evaluate the structural complexity based on the corresponding concept. We see that it is challenging to generalize such results towards different measures as every measure captures structural information differently and, hence, leads to a different entropy value. This calls for exploring the structural interpretation of a graph measure 2 which has been a challenging problem.

Keywords : Network Measures Graph Entropy structural information graph complexity measures structural complexity

Autor: Andreas Holzinger - Bernhard Ofner - Christof Stocker - André Calero Valdez - Anne Schaar - Martina Ziefle - Matthias Dehmer -

Fuente: https://hal.archives-ouvertes.fr/


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