From @martinbel on Mon Dec 19 2016 21:39:01 GMT+0000 (UTC)
I’ve tested the app and it works great! I believe the project would benefit by having a recommender system where a user would be getting personalized recommendations based on the movies they’ve seen.
I’m aware this is a big feature request, if this feels something that would fit the project I can expand on how to approach it.
EDIT (adding info):
I feel there are two ways of doing this:
- Save users data. Given the movies that are presented to them, save which ones they have clicked. It’s really really easy to implement a fairly simple/useful algo to do this. I can help with this if this route is choosen, not that hard. The data format/set up for this would be:
This is one user and a an example of a transaction (when he choose a movie from a set of movies): user_id, movie_id, watched 12dasd, foo23aa, 1 12dasd, bla55aa, 0 12dasd, foo66aa, 0 12dasd, bar11aa, 0 add all the movies the user "ignored" ... more
In machine learning parlance this would be an implicit recommender system, the problem is also called learning to rank. The advantage of this, is we don’t need to ask the users to do anything (rate movies).
- Use an existing site and hack an API from it. Movielens is a research project where people study how to make recommender systems. I actually use it to choose movies sometimes. There are many others.
Copied from original issue: https://github.com/popcorn-official/popcorn-desktop/issues/406