There are several large-scale entities that are related with each other. Web hyperlink networks, social networks and metabolic networks are the examples of such networks. Discovering dense subnetworks (communities) from given networks is important for detecting macroscopic and microscopic structures. Although many discovery methods are proposed, qualitative and quantitative differences among them are not fully discussed. As the first step for interactive analysis of network structures, the authors are developing a system for discovering and visualizing network communities. The system has abilities for divisive and agglomerative discovery of communities from given networks based on modularity.
['Tsuyoshi Murata', 'Koji Takeichi']
Discovering and Visualizing Network Communities