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Open AccessJournal ArticleDOI

Vital nodes identification in complex networks

TLDR
In this paper, the state-of-the-art algorithms for vital node identification in real networks are reviewed and compared, and extensive empirical analyses are provided to compare well-known methods on disparate real networks.
About
This article is published in Physics Reports.The article was published on 2016-09-13 and is currently open access. It has received 919 citations till now. The article focuses on the topics: Complex network.

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Journal ArticleDOI

The Web of Human Sexual Contacts

TL;DR: In this article, the authors analyze data on the sexual behavior of a random sample of individuals, and find that the cumulative distributions of the number of sexual partners during the twelve months prior to the survey decays as a power law with similar exponents for females and males.
Book ChapterDOI

Flows in Networks

TL;DR: This chapter sees how the simplex method simplifies when it is applied to a class of optimization problems that are known as “network flow models” and finds an optimal solution that is integer-valued.

Trust management for the Semantic Web

TL;DR: In this article, the authors propose a web of trust, in which each user maintains trust in a small number of other users and then composes these trust values into trust values for all other users.
Book

Submodular functions and optimization

悟 藤重
TL;DR: In this paper, the Lovasz Extensions of Submodular Functions are extended to include nonlinear weight functions and linear weight functions with continuous variables, and a Decomposition Algorithm is proposed.
References
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Journal ArticleDOI

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.
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.
Journal ArticleDOI

Emergence of Scaling in Random Networks

TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
Journal ArticleDOI

A note on two problems in connexion with graphs

TL;DR: A tree is a graph with one and only one path between every two nodes, where at least one path exists between any two nodes and the length of each branch is given.
Journal ArticleDOI

The meaning and use of the area under a receiver operating characteristic (ROC) curve.

James A. Hanley, +1 more
- 01 Apr 1982 - 
TL;DR: A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented and it is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a random chosen non-diseased subject.