Edge Metrics for Visual Graph Analytics: A Comparative Study

Guy Melançon 1, 2 Arnaud Sallaberry 3
1 TATOO - Fouille de données environnementales
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
2 GRAVITE - Graph Visualization and Interactive Exploration
Université Sciences et Technologies - Bordeaux 1, Inria Bordeaux - Sud-Ouest, École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), CNRS - Centre National de la Recherche Scientifique : UMR
Abstract : Visual graph analytics definitely relies on the use of node and edge metrics to identify salient properties in graphs. Most often, these metrics are turned into useful visual cues, or are used to interactively filter out parts of a graph while querying it, for instance. Along the years, analysts coming from different application domains have designed metrics to serve specific needs. Graph analytics, sometimes also called network science, recently developed as a cross-discipline field developing models shared by numerous application domains such as bio-informatics, social network analysis, web graphs, etc. As a consequence, we end up finding various metrics in the literature aiming at similar goals; different names and analytics description often hide similarity between two metrics that originated from different fields. We survey a list of edge metrics for graphs and compare their relative value and behaviour, in an effort to organize them into a taxonomy and underline the genuine ingredients in each of them disregarding their origin.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00272784
Contributor : Guy Melançon <>
Submitted on : Friday, April 11, 2008 - 6:01:07 PM
Last modification on : Thursday, May 24, 2018 - 3:59:23 PM

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  • HAL Id : lirmm-00272784, version 1

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Guy Melançon, Arnaud Sallaberry. Edge Metrics for Visual Graph Analytics: A Comparative Study. IV: Information Visualisation, Jul 2008, London, United Kingdom. ⟨lirmm-00272784⟩

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