Structural Analysis of Networks


Autoria(s): Melançon G.; Rozenblat C.; Rozenblat C. (ed.); Melançon G. (ed.)
Data(s)

2013

Resumo

Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.

Identificador

http://serval.unil.ch/?id=serval:BIB_227EEEC9D87B

isbn:978-94-007-6676-1 (hardback) and 978-94-007-6677-8 (paperback)

http://link.springer.com/chapter/10.1007/978-94-007-6677-8_5

Idioma(s)

en

Publicador

Dordrecht: Springer

Fonte

Methods for Multilevel Analysis and Visualisation of Geographical Networks

Palavras-Chave #Computer Imaging, Vision, Pattern Recognition and Graphics, Human Geography, Methodology of the Social Sciences, Quantitative Geography
Tipo

info:eu-repo/semantics/bookPart

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