Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2005-05-07
Advances in Physics, Volume 56, pages 167 - 242, Issue 1 (2007)
Physics
Condensed Matter
Disordered Systems and Neural Networks
A working manuscript with 78 pages, 32 figures. Suggestions of measurements for inclusion are welcomed by the authors
Scientific paper
10.1080/00018730601170527
Each complex network (or class of networks) presents specific topological features which characterize its connectivity and highly influence the dynamics of processes executed on the network. The analysis, discrimination, and synthesis of complex networks therefore rely on the use of measurements capable of expressing the most relevant topological features. This article presents a survey of such measurements. It includes general considerations about complex network characterization, a brief review of the principal models, and the presentation of the main existing measurements. Important related issues covered in this work comprise the representation of the evolution of complex networks in terms of trajectories in several measurement spaces, the analysis of the correlations between some of the most traditional measurements, perturbation analysis, as well as the use of multivariate statistics for feature selection and network classification. Depending on the network and the analysis task one has in mind, a specific set of features may be chosen. It is hoped that the present survey will help the proper application and interpretation of measurements.
Costa Luciano da F.
Rodrigues Francisco A.
Travieso Gonzalo
Villas Boas Paulino R.
No associations
LandOfFree
Characterization of complex networks: A survey of measurements does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Characterization of complex networks: A survey of measurements, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Characterization of complex networks: A survey of measurements will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-484742