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A local multiresolution algorithm for detecting communities of unbalanced structuresRizman Žalik, Krista ; Žalik, BorutIn complex networks such as computer and information networks, social networks or biological networks a community structure is a common and important property. Community detection in complex networks ... has attracted a lot of attention in recent years. Community detection is the problem of finding closely related groups within a network. Modularity optimisation is a widely accepted method for community detection. It has been shown that the modularity optimisation has a resolution limit because it is unable to detect communities with sizes smaller than a certain number of vertices defined with network size. In this paper we propose a metric for describing community structures that enables community detection better than other metrics. We present a fast local expansion algorithm for community detection. The proposed algorithm provides online multiresolution community detection from a source vertex. Experimental results show that the proposed algorithm is efficient in both real-world and synthetic networks.Source: Physica. A, Statistical mechanics and its applications. - ISSN 0378-4371 (Vol. 407, 2014, str. 380-393)Type of material - article, component part ; adult, seriousPublish date - 2014Language - englishCOBISS.SI-ID - 20912904
Author
Rizman Žalik, Krista |
Žalik, Borut
Topics
modularity |
objective function |
community detection |
dense subgraphs |
networks
source: Physica. A, Statistical mechanics and its applications. - ISSN 0378-4371 (Vol. 407, 2014, str. 380-393)
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Database name | Field | Year |
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Rizman Žalik, Krista | 08638 |
Žalik, Borut | 06671 |
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and: SICRIS
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