• DocumentCode
    3537107
  • Title

    A distance metric between directed weighted graphs

  • Author

    Yunwen Xu ; Salapaka, Srinivasa M. ; Beck, Carolyn L.

  • Author_Institution
    Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • fYear
    2013
  • fDate
    10-13 Dec. 2013
  • Firstpage
    6359
  • Lastpage
    6364
  • Abstract
    Directed weighted graphs are increasingly used to model complex systems and interactions, such as networks of interconnected physical or biological subsystems. The analysis of these graphs often requires some form of dissimilarity, or distance measure to compare graphs. In this paper, we extend connectivity-based dissimilarity measures previously used to compare unweighted undirected graphs of the same dimensions to: (1) directed weighted graphs of the same dimensions and (2) directed weighted graphs of different dimensions. To our knowledge, this is the first approach proposed for comparing two graphs containing different numbers of nodes. We derive the conditions under which this dissimilarity measure is a pseudo-metric. This derivation provides new insights on our algorithms (previously proposed) for the graph aggregation optimization problem.
  • Keywords
    directed graphs; large-scale systems; optimisation; complex systems; connectivity-based dissimilarity measure; directed weighted graphs; distance measure; distance metric; graph aggregation optimization problem; interconnected biological subsystems; interconnected physical subsystems; pseudometric dissimilarity measure; Atmospheric measurements; Indexes; Optimization; Particle measurements; Vectors; Weight measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
  • Conference_Location
    Firenze
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-5714-2
  • Type

    conf

  • DOI
    10.1109/CDC.2013.6760895
  • Filename
    6760895