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Graph mapping: Multi-scale community visualization of massive graph data / David Jonker in Information visualization, vol 16 n° 3 (July 2017)  

Public [article]  inInformation visualization > vol 16 n° 3 (July 2017) Titre : Graph mapping: Multi-scale community visualization of massive graph data Type de document : Article/Communication Auteurs : David Jonker, Auteur ; Scott Langevin, Auteur ; David Giesbrecht, Auteur ; et al., Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] graphe [Termes IGN] regroupement de données [Termes IGN] traitement réparti [Termes IGN] visualisation multiéchelle [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Graph visualizations increase the perception of entity relationships in a network. However, as graph size and density increases, readability rapidly diminishes. In this article, we present an end-to-end, tile-based visual analytic approach called graph mapping that utilizes cluster computing to turn large-scale graph (node–link) data into interactive visualizations in modern web browsers. Our approach is designed for end-user analysis of community structure and relationships at macro- and micro scales. We also present the results of several experiments using alternate methods for qualitatively improving comprehensibility of hierarchical community detection visualizations by proposing constraints to state-of-the-art modularity maximization algorithms. Numéro de notice : A2017-758 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1177/1473871616661195 En ligne : https://doi.org/10.1177/1473871616661195 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89117 [article]