Francesco Tudisco

Associate Professor (Reader) in Machine Learning

School of Mathematics, The University of Edinburgh
The Maxwell Institute for Mathematical Sciences
School of Mathematics, Gran Sasso Science Institute JCMB, King’s Buildings, Edinburgh EH93FD UK
email: f dot tudisco at ed.ac.uk

Generalized modularity matrices

Dario Fasino, Francesco Tudisco,
Linear Algebra and its Applications, 502 : 327--345 (2016)

Abstract

Various modularity matrices appeared in the recent literature on network analysis and algebraic graph theory. Their purpose is to allow writing as quadratic forms certain combinatorial functions appearing in the framework of graph clustering problems. In this paper we put in evidence certain common traits of various modularity matrices and shed light on their spectral properties that are at the basis of various theoretical results and practical spectral-type algorithms for community detection.

Please cite this work as:

@article{fasino2016generalized,
  title={Generalized modularity matrices},
  author={Fasino, Dario and Tudisco, Francesco},
  journal={Linear Algebra and its Applications},
  volume={502},
  pages={327--345},
  year={2016},
  publisher={Elsevier}
}

Links: doi arxiv

Keywords: Community detection Modularity matrix graph Modularity Nodal domains networks