Measuring the complexity of directed graphs: A polynomial-based approach

PLoS One. 2019 Nov 14;14(11):e0223745. doi: 10.1371/journal.pone.0223745. eCollection 2019.

Abstract

In this paper, we define novel graph measures for directed networks. The measures are based on graph polynomials utilizing the out- and in-degrees of directed graphs. Based on these polynomial, we define another polynomial and use their positive zeros as graph measures. The measures have meaningful properties that we investigate based on analytical and numerical results. As the computational complexity to compute the measures is polynomial, our approach is efficient and can be applied to large networks. We emphasize that our approach clearly complements the literature in this field as, to the best of our knowledge, existing complexity measures for directed graphs have never been applied on a large scale.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / statistics & numerical data*
  • Computer Graphics / statistics & numerical data*
  • Computer Simulation
  • Game Theory
  • Mathematical Concepts
  • Systems Biology / statistics & numerical data

Grants and funding

Matthias Dehmer thanks the Austrian Science Funds for supporting this work (project P 30031). Lihua Feng was supported by the National Natural Science Foundation of China (Nos. 11671402, 11871479), the Hunan Provincial Natural Science Foundation (2016JJ2138, 2018JJ2479) and the Mathematics and Interdisciplinary Sciences Project of Central South University. Jin Tao was supported by Academy of Finland (no. 315660).