I'm not sure what you're asking here-- Netflix doesn't care about anything but movies, and it probably wouldn't be able to recommend movies any better if it knew your musical tastes, or even how your tastes compare to mine.
The idea is that if you search for "sony SSK70ED," on the "discovery engine," it will show you what other people have paired with those speakers, such as receivers, furniture, and televisions. In a way those things are "similar" to the speakers because they complement them. Of course, the system shows you similar speakers first, but the complementing items are interesting results to have when you're searching for a specific item.
> I'm not sure what you're asking here-- Netflix doesn't care about anything but movies, and it probably wouldn't be able to recommend movies any better if it knew your musical tastes, or even how your tastes compare to mine.
That's wrong. The only thing that is movie-specific about the netflix recommendation system is the preference data that it runs over. It doesn't know movies from eyebrows.
If netflix (the company) also collected preference information about music, the recommendation engine would predict music preferences. And, since it would have both music and movie info, it would use music prefs to recommend movies and the reverse, just as it uses movie prefs to predict movie prefs today.
Amazon's "users who bought {something} also bought" is an example of "doesn't know anything about the domain". (They have to tone it down to keep it from recommending "strange" things that are way out of category.)
Disclosure: I know the guy who implemented NetFlix first recommendation system and have written a collaborative filter myself. I know what I can do with the fact that we both like the Pogues and Chunky Monkey. I still don't see what I can do with how we group those preferences.
"I still don't see what I can do with how we group those preferences. "
The way in which this site will allow users to group their preferences seems like a slight organizational difference when compared with other recommendation sites that use collaborative filters, but it has huge implications. This post is meant to give people a taste of what I'm starting to try and find others who are interested. I'd love to talk about any and all specifics and their implications especially if you are programmer. If you want to chat my AIM is rocksld3.
The idea is that if you search for "sony SSK70ED," on the "discovery engine," it will show you what other people have paired with those speakers, such as receivers, furniture, and televisions. In a way those things are "similar" to the speakers because they complement them. Of course, the system shows you similar speakers first, but the complementing items are interesting results to have when you're searching for a specific item.