How to create a recommendation algorithm ("If you like X and Y, you might like Z")?
I want to create an algorithm which recommends "You might also like" items from an itemlist, based on user's current liked itemlist (favorites) and based on those created by other users with similar preferences (in JS/MySQL, but that should not be of importance).
The input is simply a set of all items, and subsets (list of favorites) created by users.
Update: @Robert Harvy's Music example is a good one for clarification. Itemset: 100 bands. John likes bands 1,2,3,4,5, 11,12. Jane likes 1,2,3,4,5, 10,12. Their music tastes are likely to be similar, just as their fav lists are. The algorithm should notice this and recommend band 10 to John and 11 to Jane. No characteristics would need to be concidered in this simple scenario.