Networks are widely used to characterize and model a broad range of complex systems in various fields from biology to the social sciences. Important information about the topology and dynamics of the network can be obtained by analyzing random walks on the network.
This talk will give the theoretical background of the random-walker-based approach for complex networks and address some of the current challenges, such as partitioning of networks and identifying important nodes.