A note on a generalization of eigenvector centrality for bipartite graphs and applications
Combinatorics
2016-10-06 v1
Abstract
Eigenvector centrality is a linear algebra based graph invariant used in various rating systems such as webpage ratings for search engines. A generalization of the eigenvector centrality invariant is defined which is motivated by the need to design rating systems for bipartite graph models of time-sensitive and other processes. The linear algebra connection and some applications are described.
Cite
@article{arxiv.1610.01544,
title = {A note on a generalization of eigenvector centrality for bipartite graphs and applications},
author = {Peteris Daugulis},
journal= {arXiv preprint arXiv:1610.01544},
year = {2016}
}
Comments
Published in Networks: Peteris Daugulis: A note on a generalization of eigenvector centrality for bipartite graphs and applications. Networks 59(2): 261-264 (2012)