Clustered, but when? From static to temporal graph algorithms

VCLA hosted a talk by Manuel Sorge

ABSTRACT

Complex Network Analysis is an extremely active and broad field of research. In recent years, changes in the networks over time and time-stamped interactions are studied in more detail. Time-varying data in a network can be modeled using a temporal graph, a sequence of ordinary graphs, one for each time step. In this talk, I want to illustrate some chances and challenges in algorithmics for temporal graph analysis by showing two case studies in this area. First, I will talk about enumerating regular meetings and how sparsity of the input can make such enumeration efficient. Second, I will talk about tracking clusterings over time and a property that can make it computationally hard.