I am not sure how many actions are needed, but I can think of a few more:
* Not now, but later is fine
* Maybe next month
* Play the opposite of this
* Something similar but new to me
That's not just nice, that is the most obvious "feature" a normal person would design. I've stopped watching Netflix because of nonsense like this. They know I've seen it before, because I watched in their player. Also, even the tiniest, most modest application of analytics would discover that I always watch one series at the time, from start till end, or whenever I'm bored with it. In the past years, I have never ever watched a thing twice. Still, it was constantly showing me things I've already seen.
The only conclusion I can draw from this is that Netflix does not have have my best interest in mind when designing their algorithms and that they don't respect their customers. So I canceled.
Older recommendation systems use background and foreground timeframes to build frames of references, hence repeats.
The question to ask then is: what is the correct thing to optimize for? Dwell time is usually chosen for advertising and stickiness (you are more likely to stick with a service that plays what you like). Optimizing for novelty is difficult because the set of unknown things is much larger than the set of known things. Plus, it is risky from a business point of view.