I'm working on a recommender system that will recommend movies to users.
On top of collaborative filtering, I would like the model to take tags into account. How do I prepare a correct dataframe for this task, considering that one movie can have multiple tags?
Obvious solution is one-hot encoding, where I would make each tag a column with
0 depending on whether a movie has this tag, like so:
The problem is - I have more than 5000 unique tags to work with, dataframe will be huge. Should I just leave only top 10 tags and drop the rest? What would be the correct approach here?