From the NYC Machine Learning meetup on Jan 17, 2013: http://www.meetup.com/NYC-Machine-Learning/events/97871782/
Video is available here: http://vimeo.com/57900625
Erik BernhardssonHead of Engineering — we're hiring at Better Mortgage
4. Collaborative filtering
Idea:
- If two movies x, y get similar ratings then they are probably similar
- If a lot of users all listen to tracks x, y, z, then those tracks are
probably similar
44. Vectors are pretty nice because things are now super fast
- User-item score is a dot product:
- Item-item similarity score is a cosine similarity:
- Both cases have trivial complexity in the number of factors f: