Surprise maximization reveals the community structure of complex networks
Published 2013 View Full Article
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Title
Surprise maximization reveals the community structure of complex networks
Authors
Keywords
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Journal
Scientific Reports
Volume 3, Issue 1, Pages -
Publisher
Springer Nature
Online
2013-01-14
DOI
10.1038/srep01060
References
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Related references
Note: Only part of the references are listed.- Multi-resolution modularity methods and their limitations in community detection
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- Limitation of multi-resolution methods in community detection
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- Communities and bottlenecks: Trees and treelike networks have high modularity
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- Closed benchmarks for network community structure characterization
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- Resolving the structure of interactomes with hierarchical agglomerative clustering
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- (2010) Rodrigo Aldecoa et al. PLoS One
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- Community detection algorithms: A comparative analysis
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- Community detection in graphs
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- Fast unfolding of communities in large networks
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- Efficient modularity optimization by multistep greedy algorithm and vertex mover refinement
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- Benchmark graphs for testing community detection algorithms
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- Optimal partition and effective dynamics of complex networks
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- Maps of random walks on complex networks reveal community structure
- (2008) M. Rosvall et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
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