Network Thinking and Network Intelligence

Deyi Li, Liping Xiao, Yanni Han, Guisheng Chen, Kun Liu

Abstract: Networks interact with one another and are recursive. Network intelligence and networked intelligence, as the way of knowledge representation, have become very active recently. What topological measures can be used to characterize properties of networks? What properties do different structures of real-world networks share, and why? How did theses properties come about? How do these properties affect the dynamics of such networks? How to use network topology to extend other dimensions? Given a real-world network with certain properties, what are the best ways to search for particular nodes? Furthermore, some specific implementations and examples of network intelligence will be given in this paper. Such as mining typical topologies, discovering sensitive links and important communities from real complex networks, networked control, and making a virtual reality of emergence phenomenon in complex systems.