Quantifying layer similarity in multiplex networks: a systematic study-Reference-Cited by-同舟云学术

Quantifying layer similarity in multiplex networks: a systematic study

Published:2018-08 Issue:8 Volume:5 Page:171747
ISSN:2054-5703
Container-title:Royal Society Open Science
language:en
Short-container-title:R. Soc. open sci.

Author:

Bródka Piotr¹^ORCID,Chmiel Anna²,Magnani Matteo³,Ragozini Giancarlo⁴

Affiliation:

1. Department of Computational Intelligence, Faculty of Computer Science and Management, Wroclaw University of Science and Technology, Wroclaw, Poland

2. Faculty of Physics, Warsaw University of Technology, Warsaw, Poland

3. InfoLab, Department of Information Technology, Uppsala University, Uppsala, Sweden

4. Department of Political Science, University of Naples Federico II, Napoli, Campania, Italy

Abstract

Computing layer similarities is an important way of characterizing multiplex networks because various static properties and dynamic processes depend on the relationships between layers. We provide a taxonomy and experimental evaluation of approaches to compare layers in multiplex networks. Our taxonomy includes, systematizes and extends existing approaches, and is complemented by a set of practical guidelines on how to apply them.

Funder

Horizon 2020 Framework Programme

Ministerstwo Nauki i Szkolnictwa Wyższego

H2020 Marie Skłodowska-Curie Actions

Narodowe Centrum Nauki

Publisher

The Royal Society

Subject

Multidisciplinary

Link

https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.171747

Reference40 articles.