Abstract
In the past ten years, community detection in complex networks has attracted more and more attention of researchers. Communities often correspond to functional subunits in the complex systems. In complex network, a node community can be defined as a subgraph induced by a set of nodes, while a link community is a subgraph induced by a set of links. Although most researches pay more attention to identifying node communities in both unipartite and bipartite networks, some researchers have investigated the link community detection problem in unipartite networks. But current research pays little attention to the link community detection problem in bipartite networks. In this paper, we investigate the link community detection problem in bipartite networks, and formulate it into an integer programming model. We proposed a genetic algorithm for partition the bipartite network into overlapping link communities. Simulations are done on both artificial networks and real-world networks. The results show that the bipartite network can be efficiently partitioned into overlapping link communities by the genetic algorithm.
Highlights
Many interesting systems can be represented as networks [1]-[4]
The algorithms above can find node communities in bipartite network, current research activity has paid no attention to the link community detection problem in bipartite networks
We investigate the link community detection problem of bipartite network and propose a quantity function for link community detection of bipartite network
Summary
Many interesting systems can be represented as networks [1]-[4]. The networks are composed of nodes and links, each node represents a unit and each link represents a relation between two nodes. (2015) Mathematical Model and Algorithm for Link Community Detection in Bipartite Networks. Given the number of communities, we can partition the unipartite network into link communities by maximize D or H. Some research has paid attention to the node community detection problem of bipartite networks [15] [16]. In [15], the authors proposed a projection-based algorithm for node communities detection in bipartite network. In [21], the authors proposed an approach for detecting overlap node communities in a bipartite network based on dual optimization of modularity. The algorithms above can find node communities in bipartite network, current research activity has paid no attention to the link community detection problem in bipartite networks. By the model and algorithm, the communities including two sets of nodes in bipartite network can be identified simultaneously
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