A Cooperative and Heuristic Community Detecting Algorithm

This paper introduces the concept of community seed, vector and relation matrix. In terms of the relation similarity between free nodes and the existing communities, nodes are put into different groups. A minimum similarity threshold was proposed to filter the nodes, which gives a method to find the nodes who located at the overlapped area between different communities. This paper analyzed a series of network dataset for our algorithm and proved that it is able to accurately put nodes into different communities with high cohesion and weak coupling. We use a variety of test to illustrate that our algorithm is highly effective at detecting social structures in both artificial and real-world networks, and show how they can be used to give direction to other complex systems.