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Researchers have proposed many community detection algorithms.
Many community detection methods have been proposed like hierarchical methods.
A variety of objective functions, such as Modularity, weighted clustering coefficient (WCC), etc., have been developed to characterize the cohesiveness of a community, and thus many community detection approaches are proposed by optimizing a predefined objective function.
Ensemble clustering was proposed recently which has been successfully used to solve many community detection problems [ 20- 23].
When λ = 1, H is the standard Newman-Girvan modularity quality function, upon which many community detection algorithms are based [ 11, 46].
Recently there has been an acknowledgement that many community detection algorithms - in particular all those that rely on optimising the quality function known as modularity - impose an artificial resolution limit on the communities detected [ 22].
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(b) Though most of the ASes satisfy some notion of community, their largely variable sizes represent a hard problem for many classical community detection algorithms.
The results of experiments based on real-world datasets demonstrate the effectiveness of SCIFNET and show that it outperforms many well-known community detection approaches and clustering algorithms.
Many quality functions for community detection can be unified in the framework of the self-loop rescaling.
One could argue that there exist as many plausible analyses as there are community detection methods.
Finally, we discussed the limitations of the community detection methods for detecting ground-truth communities.
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various community detection
several community detection
some community detection
many community programs
many community energy
many attack detection
many object detection
many shadow detection
many mutation detection
many motion detection
many community health
many target detection
many community food
many outbreak detection
many face detection
many pitch detection
many disease detection
many homology detection
many edge detection
many seizure detection
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