Finding Communities by Their Centers
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Summary
This work develops a simple yet effective approach that simultaneously uncovers communities and their centers, based on the premise that organization of a community generally can be viewed as a high-density node surrounded by neighbors with lower densities, and community centers reside far apart from each other.
- Type
- article
- Published
- 2016-04-07
- Cited by
- 31
- References
- 56
- Access
- Open access
- OpenAlex
- https://openalex.org/W27053090
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:15325720
Keywords
Humanities, Art
References
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- Detecting Communities Based on Network Topology
- Consensus clustering in complex networks
- Interplay between structure and dynamics in adaptive complex networks: emergence and amplification of modularity by adaptive dynamics.
- Identifying overlapping communities as well as hubs and outliers via nonnegative matrix factorization
Cited by
- Multi-resolution community detection in massive networks
- Automatic clustering based on density peak detection using generalized extreme value distribution
- A new community detection algorithm based on adding and deleting links
- Comparative density peaks clustering
- Clustering environmental flow cytometry data by searching density peaks
- Community detection by propagating the label of center
- Critical analysis of (Quasi-)Surprise for community detection in complex networks
- A fuzzy logic approach to influence maximization in social networks
- Detecting communities from networks using an improved self-organizing map
- A new method for detecting communities and their centers using the Adamic/Adar Index and game theory
- Privbus: A privacy-enhanced crowdsourced bus service via fog computing
- Community Detection with Self-Adapting Switching Based on Affinity
- Community Detection Algorithm Based on Nonnegative Matrix Factorization and Improved Density Peak Clustering
- Community-based Influence Maximization framework for Social Networks
- Big Networks: A Survey
- Detecting leaders and key members of scientific teams in co-authorship networks
- TNS-LPA: An Improved Label Propagation Algorithm for Community Detection Based on Two-Level Neighbourhood Similarity
- RefineDCN: An Improved Community Detection Algorithm Based on Center Finding
- A stable community detection approach for complex network based on density peak clustering and label propagation
- Large-Scale Network Community Detection Using Similarity-Guided Merge and Refinement
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