Registration: Please email firstname.lastname@example.org or register at eventbrite before 15th May 2015 for a guaranteed spot. This is just before Euro 2015 at Strathclyde; so places may be limited.
Data science tools, such as data mining and optimization heuristics, have been used
to analyze many large (and massive) data-sets that can be represented as a network. In these
networks, certain attributes are associated with vertices and edges. This analysis often provides
useful information about the internal structure of the data-sets they represent. We are going to
discuss our work on several networks from telecommunications (call graph), financial
networks (market graph), social networks, and neuroscience.
In addition, we are going to present recent results on critical element selection. In network
analysis, the problem of detecting subsets of elements important to the connectivity of a
network (i.e., critical elements) has become a fundamental task over the last few years.
Identifying the nodes, arcs, paths, clusters, cliques, etc., that are responsible for network
cohesion can be crucial for studying many fundamental properties of a network.