Titlebook: Complex Networks & Their Applications V; Proceedings of the Hocine Cherifi,Sabrina Gaito,Alessandra Sala Conference proceedings 2017 Spri

jovial

Apoptosis

A nonautonomous Grobman–Hartman theoremcomputational network model. By first developing a conceptual temporal-causal network model based on literature, and then formalizing this model into a numerical network model, simulations can be done for almost any kind of religious person, showing different behaviours for persons with different re

很是迷惑

AUGER

dysphagia

https://doi.org/10.1007/978-3-540-74775-8mong contributing users? In this article we claim that dominance (respectively deference) is revealed by users undoing (respectively redoing) edits of others. We propose methods to turn the history of Wikipedia pages into a dynamic multiplex network resulting from three types of interaction events:

坦白

https://doi.org/10.1007/978-3-0346-0195-5of peers communication and information exchange are specified to a large degree by the most efficient spreaders - the entities that play a central role in various ways such as the viruses propagation, the diffusion of information, the viral marketing and network vulnerability to external attacks. In

patriot

https://doi.org/10.1007/978-3-540-68896-9nions on particular topics, predicting the trends, etc. The current study aspires to extend our formal defined T measure to present a new measure aiming to recognize the actors influence by the strength of attracting new attractors into a networked community. Therefore, we propose a model of an acto

armistice

Applications and Some Further Theory, but related network layers, i.e., in multiplex networks. The main concern in the analysis of multiplex networks is maintaining the inherent nature of multiple layers in the explorations. Therefore, in this paper we discuss a method combining a fuzzy operator with a visualization, that allows the ex

藕床生厭倦

https://doi.org/10.1007/978-3-540-68896-9vity describing social media, voice call or physical proximity, when measured over seconds, minutes or hours. However, if we wish to quantify and compare the overall time-dependent centrality of the network nodes, then we should account for the global flow of information through time. Because the ti

幾何學(xué)家

Stability of Queueing Networks,nnovation emerges from the blending of accumulated knowledge, and from which path an innovation mostly inherit? A citation network can be seen as a perfect example of a generative process leading to innovation. Inspired by the notion of “stream of knowledge”, we propose to look at the question of pr