Results 11 to 20 of about 43,402 (304)
Perturbation centrality and turbine: a novel centrality measure obtained using a versatile network dynamics tool. [PDF]
PLoS ONE, 2013 Analysis of network dynamics became a focal point to understand and predict changes of complex systems. Here we introduce Turbine, a generic framework enabling fast simulation of any algorithmically definable dynamics on very large networks.
Kristóf Z Szalay, Peter Csermely
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Mint Centrality: A Centrality Measure for the Bitcoin Transaction Graph [PDF]
2019 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), 2019 In this work, we consider the graph of confirmed transactions in bitcoin. Understanding this graph is essential to discern the different economic activities conducted by the pseudonymous actors. In addition to traditional graph analysis methods, new metrics need to be engineered specifically for the bitcoin transaction graph.
Beltran Borja Fiz Pontiveros +2 more
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Fitness centrality: a non-linear centrality measure for complex networks
Journal of Physics: ComplexityAs often happens in science, tools, and methods originally developed in one field can unexpectedly become useful in others. This paper explores the formalism of Economic Fitness Complexity (EFC), initially designed to predict and explain the economic ...
Vito D P Servedio +3 more
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A Self-Adaptive Centrality Measure for Asset Correlation Networks [PDF]
EconomiesWe propose a new centrality measure based on a self-adaptive epidemic model characterized by an endogenous reinforcement mechanism in the transmission of information between nodes. We provide a strategy to assign to nodes a centrality score that depends,
Paolo Bartesaghi +2 more
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Kolmogorov–Smirnov-Based Edge Centrality Measure for Metric Graphs
DynamicsIn this work, we introduce an edge centrality measure for the Helmholtz equation on metric graphs, a particular flow network, based on spectral edge energy density.
Christina Durón +2 more
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Comparison-based centrality measures [PDF]
International Journal of Data Science and Analytics, 2021 AbstractRecently, learning only from ordinal information of the type “itemxis closer to itemythan to itemz” has received increasing attention in the machine learning community. Such triplet comparisons are particularly well suited for learning from crowdsourced human intelligence tasks, in which workers make statements about the relative distances in a
Luca Rendsburg, Damien Garreau
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The measurement of Central Corneal Thickness
romanian journal of ophthalmology, 2023 We aimed to compare five different devices that measure Central Corneal Thickness. The Central Corneal Thickness (CCT) is an important parameter in ophthalmology. It is involved in the management of various eye conditions such as: glaucoma, keratoconus, contact lens wearing, corneal dystrophies, refractive surgery and keratoplasty.
Camburu, Georgiana +3 more
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An Analysis of Centrality’s Features as a New Measure for Network Analysis, Risk Measurement & Portfolio Selection [PDF]
تحقیقات مالی, 2021 Objective: In network theory, centrality is a measure to estimate importance and influence of a special node to the whole network structure. The aim of this research is to investigate the characteristics of stock centrality and its reliability in risk ...
Saeed Fallahpour, Ali Ghahramani
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Nodes having a major influence to break cooperation define a novel centrality measure: game centrality. [PDF]
PLoS ONE, 2013 Cooperation played a significant role in the self-organization and evolution of living organisms. Both network topology and the initial position of cooperators heavily affect the cooperation of social dilemma games.
Gabor I Simko, Peter Csermely
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Total communicability as a centrality measure [PDF]
Journal of Complex Networks, 2013 We examine a node centrality measure based on the notion of total communicability, defined in terms of the row sums of the exponential of the adjacency matrix of the network. We argue that this is a natural metric for ranking nodes in a network, and we point out that it can be computed very rapidly even in the case of large networks.
Michele Benzi, Christine Klymko
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