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Complex networks: Structure and dynamics

TLDR
The major concepts and results recently achieved in the study of the structure and dynamics of complex networks are reviewed, and the relevant applications of these ideas in many different disciplines are summarized, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.
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This article is published in Physics Reports.The article was published on 2006-02-01 and is currently open access. It has received 9441 citations till now. The article focuses on the topics: Network dynamics & Complex network.

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Ranking hubs and authorities using matrix functions

TL;DR: In this paper, the authors propose an extension of subgraph centrality and communicability based on the exponential of the adjacency matrix of the underlying graph, and apply them to the problem of ranking hubs and authorities.
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Spreading of sexually transmitted diseases in heterosexual populations

TL;DR: It is shown that the epidemic outbreak in bipartite populations, with number of sexual partners distributed as in empirical observations from national sex surveys, takes place for larger spreading rates than for the case in which the bipartITE nature of the network is not taken into account.
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Time series clustering via community detection in networks

TL;DR: The proposed network-based approach for time series clustering using community detection in complex networks achieves better results than various classic or up-to-date clustering techniques under consideration and is robust enough to group time series presenting similar pattern but with time shifts and/or amplitude variations.
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Components in time-varying graphs

TL;DR: In this article, the problem of finding strongly connected components in a time-varying graph can be mapped into finding the maximal-cliques in an opportunely constructed static graph, which is called the affine graph.
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Optimization by Simulated Annealing

TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Book

Computers and Intractability: A Guide to the Theory of NP-Completeness

TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
Journal ArticleDOI

Collective dynamics of small-world networks

TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Book

Matrix computations

Gene H. Golub
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The authors review the major concepts and results recently achieved in the study of the structure and dynamics of complex networks, and summarize the relevant applications of these ideas in many different disciplines, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.