Yes Lazyday is a rules based search engine. It makes best guesses based on what's currently popuplar, the movie's meta data and user search preferences and history. We have not evaluated it against a CF system in an A/B setup. Of course we have years of user frustration with Netflix / Prime recommends that has taught us a few valuable lessons about how to solve the problem of what to watch next.
And yes it seems intuitive to assume that two people with the same tastes will like the same titles. The problem is, I might not be in the mood for movie A even though my virtual twin is, sometimes I would be in the mood for movie A if I had company that was also in the mood for movie A. So many edge cases when a recommendation engine is trying to guess what you want to watch next.
Using the averages of your friends is very interesting. The issue would be building your dataset. Attaching it to a network like FB or building it yourself which would take even more time.
Yes Lazyday is a rules based search engine. It makes best guesses based on what's currently popuplar, the movie's meta data and user search preferences and history. We have not evaluated it against a CF system in an A/B setup. Of course we have years of user frustration with Netflix / Prime recommends that has taught us a few valuable lessons about how to solve the problem of what to watch next.
And yes it seems intuitive to assume that two people with the same tastes will like the same titles. The problem is, I might not be in the mood for movie A even though my virtual twin is, sometimes I would be in the mood for movie A if I had company that was also in the mood for movie A. So many edge cases when a recommendation engine is trying to guess what you want to watch next.
Using the averages of your friends is very interesting. The issue would be building your dataset. Attaching it to a network like FB or building it yourself which would take even more time.