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Modularity-Driven Clustering of Dynamic Graphs [chapter]

Robert Görke, Pascal Maillard, Christian Staudt, Dorothea Wagner
2010 Lecture Notes in Computer Science  
In an experimental evaluation on both a real-world dynamic network and on dynamic clustered random graphs, we show that the dynamic maintenance of a clustering of a changing graph yields higher modularity  ...  Our algorithms efficiently maintain a modularity-based clustering of a graph for which dynamic changes arrive as a stream.  ...  Conclusion As the first work on modularity-driven clustering of dynamic graphs, we deal with the NPhard problem of updating a modularity-optimal clustering after a change in the graph.  ... 
doi:10.1007/978-3-642-13193-6_37 fatcat:ow2o43vomfhzno32obs6wkpawq

Organization of Excitable Dynamics in Hierarchical Biological Networks

Mark Müller-Linow, Claus C. Hilgetag, Marc-Thorsten Hütt, Olaf Sporns
2008 PLoS Computational Biology  
The approach also shows that the dynamic behavior of the cerebral cortical systems network in the cat is dominated by the network's modular organization, while the activation behavior of the cellular neuronal  ...  This study investigates the contributions of network topology features to the dynamic behavior of hierarchically organized excitable networks.  ...  A Measure of Dynamic Modularity For computation of our new quantity assessing the match between topology and dynamics, the dynamic modularity Q dyn , we compare two clustering trees, one coming from topology  ... 
doi:10.1371/journal.pcbi.1000190 pmid:18818769 pmcid:PMC2542420 fatcat:t6bosbknbrg3tm6wif463ewcp4

Dynamic graph clustering combining modularity and smoothness

Robert Görke, Pascal Maillard, Andrea Schumm, Christian Staudt, Dorothea Wagner
2013 ACM Journal of Experimental Algorithmics  
In an experimental evaluation on both a real-world dynamic network and on dynamic clustered random graphs, we show that the dynamic maintenance of a clustering of a changing graph yields higher modularity  ...  Our algorithms efficiently maintain a modularity-based clustering of a graph for which dynamic changes arrive as a stream.  ...  Conclusion As the first work on modularity-driven clustering of dynamic graphs, we deal with the NP-hard problem of updating a modularity-optimal clustering after a change in the graph.  ... 
doi:10.1145/2444016.2444021 fatcat:cpaxhctkuvfh3acfomvkw5b3fq

Context-aware Dynamic Data-driven Pattern Classification

Shashi Phoha, Nurali Virani, Pritthi Chattopadhyay, Soumalya Sarkar, Brian Smith, Asok Ray
2014 Procedia Computer Science  
This work aims to mathematically formalize the notion of context, with the purpose of allowing contextual decision-making in order to improve performance in dynamic data driven classification systems.  ...  Field data, collected with seismic sensors on different ground types, are analyzed in order to classify two types of walking across the border, namely, normal and stealthy.  ...  Clustering using these graphs is same as community detection, where a community in a graph is a cluster of nodes with more intra-cluster edges than inter-cluster edges.  ... 
doi:10.1016/j.procs.2014.05.119 fatcat:oh3sh2ocyrbzzpieiemrvbzmry

Community Detection via Local Dynamic Interaction [article]

Junming Shao, Zhichao Han, Qinli Yang
2014 arXiv   pre-print
(d) Attractor is easy to parameterize, since there is no need to specify the number of clusters.  ...  Instead of investigating the node dynamics, we actually examine the change of "distances" among linked nodes.  ...  For detailed reviews of graph clustering, please refer to [14] . Cut-Criterion Clustering.  ... 
arXiv:1409.7978v1 fatcat:3ko7i5dyhfec5o5avwtigvurue

PeerSim: A scalable P2P simulator

Alberto Montresor, Mark Jelasity
2009 2009 IEEE Ninth International Conference on Peer-to-Peer Computing  
report graph-theoretical properties of overlay topologies, such as diameter, clustering, and so on.  ...  Modularity and Configuration PEERSIM was designed with modularity and ease of configuration in mind.  ... 
doi:10.1109/p2p.2009.5284506 dblp:conf/p2p/MontresorJ09 fatcat:rcaaunex7naq5f5lnuhlo4d66e

Towards a new approach to reveal dynamical organization of the brain using topological data analysis

Manish Saggar, Olaf Sporns, Javier Gonzalez-Castillo, Peter A. Bandettini, Gunnar Carlsson, Gary Glover, Allan L. Reiss
2018 Nature Communications  
Most previous work has focused on analyzing changes in co-fluctuations between a set of brain regions over several temporal segments of the data.  ...  Little is known about how our brains dynamically adapt for efficient functioning.  ...  The second dataset was originally collected as part of the Human Connectome Project (HCP 35 ) while participants performed working-memory tasks.  ... 
doi:10.1038/s41467-018-03664-4 pmid:29643350 pmcid:PMC5895632 fatcat:cxbund33zjbf3ilvlenezp5rye

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
The proposed multilayer network representation provides a principled way of detecting synchronous, dynamic modularity in brain networks across subjects.  ...  Our approach detected dynamic reconfiguration of modular connectivity elicited by varying task demands and identified unique profiles of intra and inter-community connectivity across different task conditions  ...  of T = 240 temporal graphs {W r,t } were characterized by time-evolving modular connectivity Θ [st] driven by underlying piece-wise stationary state time course s t ∈ 1, . . . , S.  ... 
arXiv:2004.04362v3 fatcat:34ooiejxxvgwla76v62efiq46a

Unfolding the multiscale structure of networks with dynamical Ollivier-Ricci curvature [article]

Adam Gosztolai, Alexis Arnaudon
2021 arXiv   pre-print
Here, we define a dynamic edge curvature for the study of arbitrary networks measuring the deformation between pairs of evolving dynamical network processes on different timescales.  ...  Importantly, curvature gaps robustly encode communities until the phase transition of detectability, where spectral clustering methods fail.  ...  Geometric modularity for the multiscale clustering of networks To exploit the property of the dynamical OR curvature to give multiple geometric representations, we develop a multiscale graph clustering  ... 
arXiv:2106.05847v1 fatcat:erayhxxasbb6vdkxg7irdddrxq

Application of Graph Theory to Assess Static and Dynamic Brain Connectivity: Approaches for Building Brain Graphs

Qingbao Yu, Yuhui Du, Jiayu Chen, Jing Sui, Tulay Adali, Godfrey D. Pearlson, Vince D. Calhoun
2018 Proceedings of the IEEE  
The first step in creating brain graphs is to define the nodes and edges connecting them. We review a number of approaches for defining brain nodes including fixed versus data-driven nodes.  ...  in structure and function, the organization of dynamic behavior over time, and disease related brain changes.  ...  of the  ... 
doi:10.1109/jproc.2018.2825200 pmid:30364630 pmcid:PMC6197492 fatcat:uh6tvaymifgh3cubnkemqgcd5a

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  
The proposed multilayer network representation provides a principled way of detecting synchronous, dynamic modularity in brain networks across subjects.  ...  Our approach detected dynamic reconfiguration of modular connectivity elicited by varying task demands and identified unique profiles of intra and inter-community connectivity across different task conditions  ...  of T = 240 temporal graphs {W r,t } were characterized by time-evolving modular connectivity Θ [st] driven by underlying piece-wise stationary state time course s t ∈ 1, . . . , S.  ... 
doi:10.1109/tmi.2020.3030047 pmid:33044929 fatcat:fawa67nmj5ee7atmhycnarezie

LICOD: A Leader-driven algorithm for community detection in complex networks

Zied Yakoubi, Rushed Kanawati
2014 Vietnam Journal of Computer Science  
External criteria for evaluating obtained clusters can then be used for comparing performances of different community detection approaches.  ...  We propose also a new way for evaluating performances of community detection algorithms. This consists on transforming data clustering problems into a community detection problems.  ...  Data clustering-driven evaluation We propose here to use the task of data clustering to apply a task-driven evaluation of community detection algorithms.  ... 
doi:10.1007/s40595-014-0025-6 fatcat:wpj4kfp62bh7fcjcnrqtuzrb5m

The many facets of community detection in complex networks

Michael T. Schaub, Jean-Charles Delvenne, Martin Rosvall, Renaud Lambiotte
2017 Applied Network Science  
Community detection, the decomposition of a graph into essential building blocks, has been a core research topic in network science over the past years.  ...  Since a precise notion of what constitutes a community has remained evasive, community detection algorithms have often been compared on benchmark graphs with a particular form of assortative community  ...  Consequently, depending on the dynamics of interest, the modular building blocks may look different.  ... 
doi:10.1007/s41109-017-0023-6 pmid:30533512 pmcid:PMC6245232 fatcat:25z3qfifofhr3chmimfokxbika

Dynamic communities in evolving customer networks: an analysis using landmark and sliding windows

Márcia Oliveira, Américo Guerreiro, João Gama
2014 Social Network Analysis and Mining  
In this paper, we introduce a methodology to examine the dynamics of customer communities, which relies on two dierent time window models: a landmark and a sliding window.  ...  Such approach is appropriate for the long term analysis of networks, but may fail to provide a realistic picture of the current evolution.  ...  We also thank the anonymous reviewers for their valuable comments and suggestions on earlier versions of this manuscript.  ... 
doi:10.1007/s13278-014-0208-2 fatcat:dopl56noz5chjphmgeonuyhp3m

Static and Dynamic Aspects of Scientific Collaboration Networks

C. Staudt, A. Schumm, H. Meyerhenke, R. Gorke, D. Wagner
2012 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining  
Additionally, we detect communities with modularity-based clustering and compare the resulting clusters to a ground-truth based on conferences and thus topical similarity.  ...  Using the computer science publication database DBLP, we compile relations between authors and publications as graphs and proceed with examining and quantifying collaborative relations with graph-based  ...  ACKNOWLEDGMENT We thank Ulrik Brandes for helpful discussions during the preparation of this work.  ... 
doi:10.1109/asonam.2012.90 dblp:conf/asunam/StaudtSMGW12 fatcat:niiamd47hrgt7p4czwfhiyzqda
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