  Dynamics of interactions play an increasingly important role in the analysis
of complex networks. A modeling framework to capture this are temporal graphs
which consist of a set of vertices (entities in the network) and a set of
time-stamped binary interactions between the vertices. We focus on enumerating
delta-cliques, an extension of the concept of cliques to temporal graphs: for a
given time period delta, a delta-clique in a temporal graph is a set of
vertices and a time interval such that all vertices interact with each other at
least after every delta time steps within the time interval. Viard, Latapy, and
Magnien [ASONAM 2015, TCS 2016] proposed a greedy algorithm for enumerating all
maximal delta-cliques in temporal graphs. In contrast to this approach, we
adapt the Bron-Kerbosch algorithm - an efficient, recursive backtracking
algorithm which enumerates all maximal cliques in static graphs - to the
temporal setting. We obtain encouraging results both in theory (concerning
worst-case running time analysis based on the parameter "delta-slice
degeneracy" of the underlying graph) as well as in practice with experiments on
real-world data. The latter culminates in an improvement for most interesting
delte-values concerning running time in comparison with the algorithm of Viard,
Latapy, and Magnien.
