Results 11 to 20 of about 557,147 (262)
Bayesian Community Detection [PDF]
Neural Computation, 2012 Many networks of scientific interest naturally decompose into clusters or communities with comparatively fewer external than internal links; however, current Bayesian models of network communities do not exert this intuitive notion of communities.
Morten Mørup, Mikkel N. Schmidt
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From community detection to community profiling [PDF]
Proceedings of the VLDB Endowment, 2017 Most existing community-related studies focus on detection, which aim to find the community membership for each user from user friendship links. However, membership alone, without a complete profile of what a community is and how it interacts with other communities, has limited applications.
Hongyun Cai 0001 +4 more
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Community Detection in Multiplex Networks [PDF]
ACM Computing Surveys, 2021 A multiplex network models different modes of interaction among same-type entities. In this article, we provide a taxonomy of community detection algorithms in multiplex networks. We characterize the different algorithms based on various properties and we discuss the type of communities detected by each method. We then provide an extensive experimental
Magnani, Matteo +4 more
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Community detection in large hypergraphs. [PDF]
Sci Adv, 2023 Hypergraphs, describing networks where interactions take place among any number of units, are a natural tool to model many real-world social and biological systems. Here, we propose a principled framework to model the organization of higher-order data.
Ruggeri N +3 more
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Deep Community Detection [PDF]
IEEE Transactions on Signal Processing, 2015 15 pages, 13 figures, journal submission and supplementary file (Figures 11-13), to appear in IEEE Transactions on Signal ...
Pin-Yu Chen, Alfred O. Hero III
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Community Detection on the GPU [PDF]
2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2017 We present and evaluate a new GPU algorithm based on the Louvain method for community detection. Our algorithm is the first for this problem that parallelizes the access to individual edges. In this way we can fine tune the load balance when processing networks with nodes of highly varying degrees.
Md. Naim +3 more
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Anomaly detection and community detection in networks
Journal of Big Data, 2022 AbstractAnomaly detection is a relevant problem in the area of data analysis. In networked systems, where individual entities interact in pairs, anomalies are observed when pattern of interactions deviates from patterns considered regular. Properly defining what regular patterns entail relies on developing expressive models for describing the observed ...
Hadiseh Safdari, Caterina De Bacco
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COMMUNITY DETECTION IN NETWORKS
International Journal of Bifurcation and Chaos, 2010 The problem of community detection is relevant in many disciplines of science. A community is usually defined, in a qualitative way, as a subset of nodes of a network which are more connected among themselves than to the rest of the network. In this article, we introduce a new method for community detection in complex networks.
Dorso, Claudio Oscar, Medus, A. D.
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2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014 In this work, we propose a new method which can detect image communities inside an image set. The proposed method differs from previous works by representing image relations with directed graphs and performing community anaysis on these directed graphs.
Esen, Ersin +4 more
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The art of community detection [PDF]
BioEssays, 2008 AbstractNetworks in nature possess a remarkable amount of structure. Via a series of data‐driven discoveries, the cutting edge of network science has recently progressed from positing that the random graphs of mathematical graph theory might accurately describe real networks to the current viewpoint that networks in nature are highly complex and ...
Gulbahce, Natali, Lehmann, Sune
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