What is the best approach to solving this problem?
I can make a table that records all the posts that each user has ever seen, then filter out seen posts after a list of recommendations are created. But this seems like a solution that will become more and more costly over time as more people see more posts, and we will need to check it every single time we recommend posts.
This feels like a standard problem that must have been answered by others over the past decades. Perhaps there is a framework that I am not aware of that takes an opinionated approach for this problem as well as other problems in the content recommendation space. But then again, I see seen contents all the time on YouTube, so maybe this is not a solvable problem with current computing capacity.
Please share your experiences and insights!