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math.COFeb 17, 2018
23
citations (OpenAlex)
authors
  • Konstantin Avrachenkov
  • Pavel Chebotarev
  • Dmytro Rubanov
institutions
  • Centre Inria d'Université Côte d'Azur
  • Kotelnikov Institute of Radioengineering and Electronics of the Russian Academy of Sciences
  • Moscow Institute of Physics and Technology
  • Russian Academy of Sciences
  • V. A. Trapeznikov Institute of Control Sciences
arXiv abstractPDF
paper

Similarities on Graphs: Kernels versus Proximity Measures

arXiv:1802.06284 · doi:10.1016/j.ejc.2018.02.002

Abstract

We analytically study proximity and distance properties of various kernels and similarity measures on graphs. This helps to understand the mathematical nature of such measures and can potentially be useful for recommending the adoption of specific similarity measures in data analysis.

16 pages

References in corpus (4)

  • Communicability in complex networks
  • Statistical-mechanical approach to subgraph centrality in complex networks
  • Supervised Random Walks: Predicting and Recommending Links in Social Networks
  • Do logarithmic proximity measures outperform plain ones in graph clustering?

Cited by in corpus (4)

  • An Unsupervised Framework for Comparing Graph Embeddings
  • Selection of Centrality Measures Using Self-Consistency and Bridge Axioms
  • Red Light Green Light Method for Solving Large Markov Chains
  • How to choose the most appropriate centrality measure? A decision tree approach
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