M. Latapy, C. Magnien, and N. Vecchio. (February 2008)the article defines and discusses the basics for complex networks with the focus on bipartite graphs
deals with (weighted) projection approaches;
gives a framework for basic notations.
Abstract
Many real-world complex networks actually have a bipartite nature: their nodes may
be separated into two classes, the links being between nodes of different classes only.
Despite this, and despite the fact that many ad-hoc tools have been designed for the
study of special cases, very few exist to analyse (describe, extract relevant information)
such networks in a systematic way. We propose here an extension of the most basic
notions used nowadays to analyse classical complex networks to the bipartite case. To
achieve this, we introduce a set of simple statistics, which we discuss by comparing
their values on a representative set of real-world networks and on their random versions
the article defines and discusses the basics for complex networks with the focus on bipartite graphs
deals with (weighted) projection approaches;
gives a framework for basic notations
%0 Journal Article
%1 paper:latapy:08
%A Latapy, Matthieu
%A Magnien, Clemence
%A Vecchio, Nathalie Del
%D 2008
%K 2008 basic graph networks
%T Basic Notions for the Analysis of Large
%U http://arxiv.org/PS_cache/cond-mat/pdf/0611/0611631v1.pdf
%X Many real-world complex networks actually have a bipartite nature: their nodes may
be separated into two classes, the links being between nodes of different classes only.
Despite this, and despite the fact that many ad-hoc tools have been designed for the
study of special cases, very few exist to analyse (describe, extract relevant information)
such networks in a systematic way. We propose here an extension of the most basic
notions used nowadays to analyse classical complex networks to the bipartite case. To
achieve this, we introduce a set of simple statistics, which we discuss by comparing
their values on a representative set of real-world networks and on their random versions
@article{paper:latapy:08,
abstract = {Many real-world complex networks actually have a bipartite nature: their nodes may
be separated into two classes, the links being between nodes of different classes only.
Despite this, and despite the fact that many ad-hoc tools have been designed for the
study of special cases, very few exist to analyse (describe, extract relevant information)
such networks in a systematic way. We propose here an extension of the most basic
notions used nowadays to analyse classical complex networks to the bipartite case. To
achieve this, we introduce a set of simple statistics, which we discuss by comparing
their values on a representative set of real-world networks and on their random versions},
added-at = {2008-05-05T15:15:10.000+0200},
author = {Latapy, Matthieu and Magnien, Clemence and Vecchio, Nathalie Del},
biburl = {https://www.bibsonomy.org/bibtex/210e62042c8bc83120e4ec9d043c88f54/mschuber},
interhash = {fddead47fde0d4f52282ecc93a5798fa},
intrahash = {10e62042c8bc83120e4ec9d043c88f54},
keywords = {2008 basic graph networks},
month = {February},
note = {the article defines and discusses the basics for complex networks with the focus on bipartite graphs
deals with (weighted) projection approaches;
gives a framework for basic notations},
timestamp = {2008-09-09T12:59:20.000+0200},
title = {Basic Notions for the Analysis of Large},
url = {http://arxiv.org/PS_cache/cond-mat/pdf/0611/0611631v1.pdf},
year = 2008
}