Identifying Modules in Complex Networks by a Graph-Theoretical Method and Its Application in Protein Interaction Networks

Wang, Rui-Sheng; Zhang, Shihua; Xia, Yu; Chen, Luonan

doi:10.1007/978-3-540-74205-0_113

Cited by 1 publication

(1 citation statement)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this network, the word “play” is strongly associated with most words, so it is an overlapping node. This result has also been obtained by a graph-theoretical method for node community detection [35] .…”

Section: Resultssupporting

confidence: 66%

Discovering Link Communities in Complex Networks by an Integer Programming Model and a Genetic Algorithm

Zhang

Wang

et al. 2013

PLoS ONE

Self Cite

View full text Add to dashboard Cite

Identification of communities in complex networks is an important topic and issue in many fields such as sociology, biology, and computer science. Communities are often defined as groups of related nodes or links that correspond to functional subunits in the corresponding complex systems. While most conventional approaches have focused on discovering communities of nodes, some recent studies start partitioning links to find overlapping communities straightforwardly. In this paper, we propose a new quantity function for link community identification in complex networks. Based on this quantity function we formulate the link community partition problem into an integer programming model which allows us to partition a complex network into overlapping communities. We further propose a genetic algorithm for link community detection which can partition a network into overlapping communities without knowing the number of communities. We test our model and algorithm on both artificial networks and real-world networks. The results demonstrate that the model and algorithm are efficient in detecting overlapping community structure in complex networks.

show abstract

Section: Resultssupporting

confidence: 66%