Results 31 to 40 of about 557,147 (262)
Bayesian Analysis, 2018 We introduce a Bayesian estimator of the underlying class structure in the stochastic block model, when the number of classes is known. The estimator is the posterior mode corresponding to a Dirichlet prior on the class proportions, a generalized Bernoulli prior on the class labels, and a beta prior on the edge probabilities.
Pas, S.L. van der, Vaart, A.W. van der
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Large Scale Community Detection Using a Small World Model
Applied Sciences, 2017 In a social network, small or large communities within the network play a major role in deciding the functionalities of the network. Despite of diverse definitions, communities in the network may be defined as the group of nodes that are more densely ...
Ranjan Kumar Behera +4 more
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Entropy, 2023 To address the problem that traditional spectral clustering algorithms cannot obtain the complete structural information of networks, this paper proposes a spectral clustering community detection algorithm, PMIK-SC, based on the point-wise mutual ...
Yinan Chen, Wenbin Ye, Dong Li
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Network Community Detection on Metric Space
Algorithms, 2015 Community detection in a complex network is an important problem of much interest in recent years. In general, a community detection algorithm chooses an objective function and captures the communities of the network by optimizing the objective function,
Suman Saha, Satya P. Ghrera
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Post-Processing Partitions to Identify Domains of Modularity Optimization
Algorithms, 2017 We introduce the Convex Hull of Admissible Modularity Partitions (CHAMP) algorithm to prune and prioritize different network community structures identified across multiple runs of possibly various computational heuristics.
William H. Weir +4 more
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Computers, 2023 The rapid dissemination of misinformation on social networks, particularly during public health crises like the COVID-19 pandemic, has become a significant concern.
Zafer Duzen +2 more
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A paradox in community detection [PDF]
EPL (Europhysics Letters), 2014 Recent research has shown that virtually all algorithms aimed at the identification of communities in networks are affected by the same main limitation: the impossibility to detect communities, even when these are well-defined, if the average value of the difference between internal and external node degrees does not exceed a strictly positive value ...
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Statistical mechanics of community detection [PDF]
Physical Review E, 2006 Starting from a general \textit{ansatz}, we show how community detection can be interpreted as finding the ground state of an infinite range spin glass. Our approach applies to weighted and directed networks alike. It contains the \textit{at hoc} introduced quality function from \cite{ReichardtPRL} and the modularity $Q$ as defined by Newman and Girvan
Reichardt, Joerg, Bornholdt, Stefan
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Learner2Vec-Based Learner Community Evolution Analysis–A Case Study Involving Student Card Data
IEEE Access, 2019 The learner community evolution analysis is an important technique in the area of social network analysis and education management. Accurately expressing the complex characteristics of individual social behavior is the core problem associated with ...
Chao Li +4 more
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CoDiS: Community Detection via Distributed Seed Set Expansion on Graph Streams
Information, 2023 Community detection has been (and remains) a very important topic in several fields. From marketing and social networking to biological studies, community detection plays a key role in advancing research in many different fields.
Austin Anderson +2 more
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