Tuning Ranking in Co-occurrence Networks with General Biased Exchange-based Diffusion on Hyper-bag-graphs
Social and Information Networks
2020-03-17 v1 Discrete Mathematics
Combinatorics
Abstract
Co-occurence networks can be adequately modeled by hyper-bag-graphs (hb-graphs for short). A hb-graph is a family of multisets having same universe, called the vertex set. An efficient exchange-based diffusion scheme has been previously proposed that allows the ranking of both vertices and hb-edges. In this article, we extend this scheme to allow biases of different kinds and explore their effect on the different rankings obtained. The biases enhance the emphasize on some particular aspects of the network.
Cite
@article{arxiv.2003.07323,
title = {Tuning Ranking in Co-occurrence Networks with General Biased Exchange-based Diffusion on Hyper-bag-graphs},
author = {Xavier Ouvrard and Jean-Marie Le Goff and Stéphane Marchand-Maillet},
journal= {arXiv preprint arXiv:2003.07323},
year = {2020}
}