ArticleScientific reports2016
Overlapping Community Detection based on Network Decomposition.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Social user geolocation based on K-medoids and Gaussian Kernel graph attention network.Scientific reports · 2026Article
- A multi-objective evolutionary algorithm for detecting protein complexes in PPI networks using gene ontology.Scientific reports · 2025Article
- Social Network Forensics Analysis Model Based on Network Representation Learning.Entropy (Basel, Switzerland) · 2024Article
- Network analysis of stroke systems of care in Korea.BMJ neurology open · 2024Article
- LazyFox: fast and parallelized overlapping community detection in large graphs.PeerJ. Computer science · 2023Article
- Effect of Seeding Strategy on the Efficiency of Brand Spreading in Complex Social Networks.Frontiers in psychology · 2022Article
- A New Framework for Discovering Protein Complex and Disease Association via Mining Multiple Databases.Interdisciplinary sciences, computational life sciences · 2021Article
- Neuronal Graphs: A Graph Theory Primer for Microscopic, Functional Networks of Neurons Recorded by Calcium Imaging.Frontiers in neural circuits · 2021Review
- Influence of number of individuals and observations per individual on a model of community structure.PloS one · 2021Article
- Overlapping community detection in networks based on link partitioning and partitioning around medoids.PloS one · 2021Article
- Article
- Critical analysis of (Quasi-)Surprise for community detection in complex networks.Scientific reports · 2018Article
- Closed trail distance in a biconnected graph.PloS one · 2018Article
- An algorithm based on positive and negative links for community detection in signed networks.Scientific reports · 2017Article
- Disease-related gene module detection based on a multi-label propagation clustering algorithm.PloS one · 2017Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms.
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Registered trials
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