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

Clicks: 197
ID: 92259
2019
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
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.
Reference Key
dehmer2019measuringplos Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Dehmer, Matthias;Chen, Zengqiang;Emmert-Streib, Frank;Tripathi, Shailesh;Mowshowitz, Abbe;Levitchi, Alexei;Feng, Lihua;Shi, Yongtang;Tao, Jin;
Journal PloS one
Year 2019
DOI
10.1371/journal.pone.0223745
URL
Keywords
Defect detection k-means feature fusion irregular surfaces

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.