Collaborative filtering when multiple items are rated multiple times by same user When trying to model as a recommendation problem the selection of an item that can be selected (and rated) by the same user many times, I can't find references of previous work. 

For example User1 can select item A (and rate it) then item A again (and give it a different rate) and then again item A can be selected n times.. then the same for item B, but item A could be again selected at any time point, and that could happen for any of the A, B, C... Z items. Could this be modelled somehow as a recommender system?

When asked in SO I was told that can't be modelled even as a multi-modal recommneder, then I think my question should be extended to how could I model this for prediction of next rate?

SO question
I don't think there is any academic work on the subject, at least that I know of. 

One simple way of using that data would be to use the mean of the ratings or other average like measures such as a moving average, a time weighted average, the median, etc. 

But this approach is probably not exactly what you're looking for.

Try to look at collaborative filtering approaches with temporal dynamics, there might be something interesting for you.