About Complex Network and Map Graph Group

Examples of big graph data in the real world include complex networks, such as social networks and the Web graph, and the map graph used to represent traffic networks. The Complex Network and Map Graph Group conducts research into these two graphs from the viewpoints of computer science and physics.

In computer science, a range of algorithms for these graphs have been presented. However, although these algorithms produce positive experimental results, the reason for their performance has not been theoretically clarified. And while physics is successfully clarifying the nature of these graphs, there are hardly any practical algorithms that utilize these discoveries.

Experimentation and theory must be two halves of a whole. In fact, the natural sciences have developed through this cycle of developing a theory from experimental discoveries and confirming the validity of the developed theory with further experiments. The aim of this group is to establish the same cycle in our research into complex networks and map graphs. Our research results are expected to accelerate the development of truly practical algorithms for big graph data through a synergy of computer science and physics.
 

Members

• Members (To NII website）