Is the amount of data or just a model to give an idea of the structure you have?
A few ideas on how to look at this ... I apologize if it is redundant to your current state when viewing this set.
To compare such an interval, it is necessary to recall two main ideas: absolute or relative. Relative comparison ignores the absolute time for these intervals and looks for repeating structures or signatures that occur in both groups, but not necessarily at the same time. The absolute version would allow for simultaneous events to be relevant, and it doesn’t matter if something happens every week, if it is divided by year ... You can make this distinction by knowing something about the origin of the data.
If this is the total amount of data available for your association decision, it comes down to some assumptions about what constitutes “correlation”. For example, if you have a specific model for what is happening - for example, the start time, the time for the model to stop (fail), you could estimate the probability of observing one sequence, given the other. However, without unnecessary data examples, you are unlikely to be able to draw any solid conclusions.
The first interval in the two groups is almost identical, so they will greatly affect any correlation measure that I can imagine for the two groups. If there is a random model for this set, I would expect that many models will demonstrate these two observations and are “unlikely” because of this.
One way to evaluate “similarity” would be to ask which part of the time axis is covered (possibly generalized for multiple coverage) and compare the two groups on this basis.
Another possibility is to assign a function that adds one for each sequence that occurs during any given day in the total interval of these events. Thus, you have a continuous function with a rudimentary description of several events covering the same date. Calculating the correlation between the two groups may give you suggestions for structural similarity, but again you will need more data groups to draw any conclusions.
Well, that was a little weird. Good luck with your project!