I have a content based recommender system, which finds similar items given a list of past liked items using cosine similarity.
What would be best way to implement feedback or personalization in the recommender system, when the user rates the output of recommender.
For ex. A user is recommended 5 items from the recommender. But the user liked 2nd, 4th and 5th item, but disliked 1st and 3rd item. Is there a way to use this information to improve the result of recommendations?