Before revision:  Finally, we conduct several case studies on real world data sets and show how our method can find cyclic patterns, deviations from those patterns, and one-time events in time-varying graphs  .
After revision:  Finally, we conduct several case studies on real world data sets and show how our method can find cyclic patterns, deviations from those patterns, and one-time events in time-varying graphs . We also examine whether persistence-based similarity measure as a graph metric satisfies a set of well-established, desirable properties for graph metrics .