Filters








333 Hits in 3.9 sec

Multi-Dimensional, Multilayer, Nonlinear and Dynamic HITS [article]

Francesca Arrigo, Francesco Tudisco
2018 arXiv   pre-print
We introduce a ranking model for temporal multi-dimensional weighted and directed networks based on the Perron eigenvector of a multi-homogeneous order-preserving map.  ...  The model extends to the temporal multilayer setting the HITS algorithm and defines five centrality vectors: two for the nodes, two for the layers, and one for the temporal stamps.  ...  Multi-Dimensional HITS We propose an extension of the HITS model to the framework of temporal directed multilayer networks.  ... 
arXiv:1809.08004v1 fatcat:tienlnpi2jf2ldtqb4pnodbzne

Fast computation of matrix function-based centrality measures for layer-coupled multiplex networks [article]

Kai Bergermann, Martin Stoll
2022 arXiv   pre-print
With a suitable choice of edge weights, the definition of single-layer matrix function-based centrality measures in terms of walks on networks carries over naturally to the multilayer case.  ...  We use the supra-adjacency matrix as network representation, which has already been used to generalize eigenvector centrality to temporal and multiplex networks.  ...  Stoll acknowledges the funding of the BMBF grant 01-S20053A. The authors thank all referees for their helpful comments.  ... 
arXiv:2104.14368v4 fatcat:72qofku76zf7linpt2u7lbr5xq

Tunable Eigenvector-Based Centralities for Multiplex and Temporal Networks [article]

Dane Taylor, Mason A. Porter, Peter J. Mucha
2020 arXiv   pre-print
We present a linear-algebraic framework that generalizes eigenvector-based centralities, including PageRank and hub/authority scores, to provide a common framework for two popular classes of multilayer  ...  Our framework provides a unifying foundation for centrality analysis of multiplex and temporal networks; it also illustrates a complicated dependency of the supracentralities on the topology and weights  ...  We now present a supracentrality framework that provides a common mathematical foundation for eigenvector-based centralities for layer-coupled multiplex and temporal networks.  ... 
arXiv:1904.02059v4 fatcat:miifoyfcwvgnnpibnhpf5tvbi4

The use of multilayer network analysis in animal behaviour [article]

Kelly R. Finn, Matthew J. Silk, Mason A. Porter, Noa Pinter-Wollman
2018 arXiv   pre-print
Finally, we discuss caveats to undertaking multilayer network analysis in the study of animal social networks, and we call attention to methodological challenges for the application of these approaches  ...  Our aim is to instigate the study of new questions about animal sociality using the new toolbox of multilayer network analysis.  ...  We also thank Raissa D'Souza and the members of her lab for discussions on multilayer networks and Brenda McCowan and her lab members, especially Brianne Beisner, for support and extensive conversations  ... 
arXiv:1712.01790v4 fatcat:lkgoj53ytbbldebozdnghvrgom

Multilayer networks

M. Kivela, A. Arenas, M. Barthelemy, J. P. Gleeson, Y. Moreno, M. A. Porter
2014 Journal of Complex Networks  
To unify the disparate terminology in the large body of recent work, we discuss a general framework for multilayer networks, construct a dictionary of terminology to relate the numerous existing concepts  ...  In this paper, we discuss the history of multilayer networks (and related concepts) and review the exploding body of work on such networks.  ...  In the same paper, they also used the tensorial framework for multilayer networks developed in Ref. [103] to define generalizations of eigenvector centrality, Katz centrality, and HITS centrality.  ... 
doi:10.1093/comnet/cnu016 fatcat:gkvuniqrdbgkpn22t7fkt7vdke

Multilayer Networks in a Nutshell

Alberto Aleta, Yamir Moreno
2018 Annual Review of Condensed Matter Physics  
To account for this source of complexity, a more general framework, in which different networks evolve or interact with each other, is needed. These are known as multilayer networks.  ...  Here we provide an overview of the basic methodology used to describe multilayer systems as well as of some representative dynamical processes that take place on top of them.  ...  Other centrality measures used in single-layer networks can also be extended to the framework of multilayer networks like PageRank (21), betweenness (22) , or eigenvector centrality (23, 24) .  ... 
doi:10.1146/annurev-conmatphys-031218-013259 fatcat:sjpyl3vih5h6tc5makibpyhdb4

Identifying critical nodes in temporal networks by network embedding

En-Yu Yu, Yan Fu, Xiao Chen, Mei Xie, Duan-Bing Chen
2020 Scientific Reports  
centralities in one synthetic and five real temporal networks.  ...  Considering the topological information of networks, the algorithm MLI based on network embedding and machine learning are proposed in this paper. we convert the critical node identification problem in  ...  Taylor et al. proposed the eigenvector-based centrality for temporal networks 21 , where the eigenvector and its components of a supra-centrality matrix can reflect the importance of nodes.  ... 
doi:10.1038/s41598-020-69379-z pmid:32719327 fatcat:xf3agsvzrvhoxkoikrnkdhu6i4

Evolution of the Global Financial Network and Contagion: A New Approach

Yevgeniya Korniyenko, Manasa Patnam, Rita Maria del Rio-Chanon, Mason Porter
2018 IMF Working Papers  
That is, we consider the transpose of the adjacency tensor (M i j α β T ) for computing the transition probability tensor included in equation (7) .  ...  We use the Einstein sum notation as generalization for the multiplex centrality measures: • Eigenvector centrality: In network theory eigenvector centrality is a measure of the influence of a node in a  ...  Similarly, for the multiplex network we consider the state of node-layer (i, α) to be given by σ i,α .  ... 
doi:10.5089/9781484353240.001 fatcat:nuqmb2snirhthknudpy5u4465y

MuxViz: a tool for multilayer analysis and visualization of networks

M. De Domenico, M. A. Porter, A. Arenas
2014 Journal of Complex Networks  
We present open-source software (muxViz) that contains a collection of algorithms for the analysis of multilayer networks, which are an important way to represent a large variety of complex systems throughout  ...  We demonstrate the ability of muxViz to analyze and interactively visualize multilayer data using empirical genetic, neuronal, and transportation networks.  ...  Acknowledgement The authors thank Serafina Agnello for support with graphics.  ... 
doi:10.1093/comnet/cnu038 fatcat:6x7c5ty4uzaddcruutxmu5mc3e

Deep graphs—A general framework to represent and analyze heterogeneous complex systems across scales

Dominik Traxl, Niklas Boers, Jürgen Kurths
2016 Chaos  
Furthermore, to be able to utilize existing network-based methods and models, we derive different representations of multilayer networks from our framework and demonstrate the advantages of our representation  ...  In this paper, we introduce a collection of definitions resulting in a framework that, on the one hand, entails and unifies existing network representations (e.g., network of networks, multilayer networks  ...  ACKNOWLEDGMENTS This paper was developed within the scope of the IRTG 1740/TRP 2011/50151-0, funded by the DFG/FAPESP.  ... 
doi:10.1063/1.4952963 pmid:27368793 fatcat:mudqlr7uunf2tmr2p5l2exlqbu

Multilayer Spectral Graph Clustering via Convex Layer Aggregation [article]

Pin-Yu Chen, Alfred O. Hero III
2016 arXiv   pre-print
This paper presents a theoretical framework for multilayer spectral graph clustering of the nodes via convex layer aggregation.  ...  Under a novel multilayer signal plus noise model, we provide a phase transition analysis that establishes the existence of a critical value on the noise level that permits reliable cluster separation.  ...  In temporal networks, each layer corresponds to the snapshot of the entire network at a sampled time instance.  ... 
arXiv:1609.07200v1 fatcat:6fjwvmpeqjajzpevnpo532onyy

A survey of community detection methods in multilayer networks

Xinyu Huang, Dongming Chen, Tao Ren, Dongqi Wang
2020 Data mining and knowledge discovery  
The comparison results indicate that the promoting of algorithm efficiency and the extending for general multilayer networks are also expected in the forthcoming studies.  ...  In recent years, there's an increasing focus on the rapid development of more complicated networks, namely multilayer networks.  ...  Acknowledgements We would like to thank the anonymous reviewers for their careful reading and useful comments that helped us to improve the final version of this paper.  ... 
doi:10.1007/s10618-020-00716-6 fatcat:z3arrhq52fd6fiosfawtdr2hbq

Comparing multilayer brain networks between groups: Introducing graph metrics and recommendations

Kanad Mandke, Jil Meier, Matthew J. Brookes, Reuben D. O'Dea, Piet Van Mieghem, Cornelis J. Stam, Arjan Hillebrand, Prejaas Tewarie
2018 NeuroImage  
Here, we discuss how a multilayer network framework allows for integration of multiple networks into a single network description and how graph metrics can be applied to quantify multilayer network organisation  ...  All of this evidence advocates an integrative approach. A generic framework that enables integration of information from different networks is the multilayer network approach.  ...  Acknowledgements: We thank the University of Nottingham for Vice Chancellor's Scholarship awarded to KM.  ... 
doi:10.1016/j.neuroimage.2017.11.016 pmid:29138088 fatcat:tykal74btrbsvkxxsgp3d5bqly

Detecting Dynamic Community Structure in Functional Brain Networks Across Individuals: A Multilayer Approach [article]

Chee-Ming Ting, S. Balqis Samdin, Meini Tang, Hernando Ombao
2020 arXiv   pre-print
We present a unified statistical framework for characterizing community structure of brain functional networks that captures variation across individuals and evolution over time.  ...  We first formulate a multilayer extension of SBM to describe the time-dependent, multi-subject brain networks.  ...  Fig. 1 . 1 Overview of the proposed MSS-SBM framework for detecting state-based dynamic community structure in multi-subject brain functional networks.  ... 
arXiv:2004.04362v3 fatcat:34ooiejxxvgwla76v62efiq46a

Detecting Dynamic Community Structure in Functional Brain Networks Across Individuals: A Multilayer Approach

Chee-Ming Ting, S. Balqis Samdin, Meini Tang, Hernando Ombao
2020 IEEE Transactions on Medical Imaging  
We present a unified statistical framework for characterizing community structure of brain functional networks that captures variation across individuals and evolution over time.  ...  We first formulate a multilayer extension of SBM to describe the time-dependent, multi-subject brain networks.  ...  Fig. 1 . 1 Overview of the proposed MSS-SBM framework for detecting state-based dynamic community structure in multi-subject brain functional networks.  ... 
doi:10.1109/tmi.2020.3030047 pmid:33044929 fatcat:fawa67nmj5ee7atmhycnarezie
« Previous Showing results 1 — 15 out of 333 results