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Dirichlet Graph Densifiers

  • Francisco EscolanoEmail author
  • Manuel Curado
  • Miguel A. Lozano
  • Edwin R. Hancook
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10029)

Abstract

In this paper, we propose a graph densification method based on minimizing the combinatorial Dirichlet integral for the line graph. This method allows to estimate meaningful commute distances for mid-size graphs. It is fully bottom up and unsupervised, whereas anchor graphs, the most popular alternative, are top-down. Compared with anchor graphs, our method is very competitive (it is only outperformed for some choices of the parameters, namely the number of anchors). In addition, although it is not a spectral technique our method is spectrally well conditioned (spectral gap tends to be minimized). Finally, it does not rely on any pre-computation of cluster representatives.

Keywords

Graph densification Dirichlet problems Random walkers 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Francisco Escolano
    • 1
    Email author
  • Manuel Curado
    • 1
  • Miguel A. Lozano
    • 1
  • Edwin R. Hancook
    • 2
  1. 1.Department of Computer Science and AIUniversity of AlicanteAlicanteSpain
  2. 2.Department of Computer ScienceUniversity of YorkYorkUK

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