[div]

I think a strong algorithm may surprise you.

I remember reading about the Netflix contest and how one of the algorithms categorizes movies into it's own statistically relevant categories*.

Once a comparative algorithm is used and the dataset gets large enough, I have no doubt the recommendations will start to get real good real fast.

http://devlicio.us/blogs/billy_mccafferty/archive/2007/01/02...

[jfarmer]

What I'm trying to say is this: it's not about a "match" between the product and the potential consumer.

The who, what, and how of the recommendation matter almost as much as the product itself. Just the fact that I know this recommendation came from a human counts for something, especially if it's a human I trust or respect when it comes to fashion (not necessarily a friend).

e.g., a celebrity wearing a shirt and having it sell out the next day.

Movies are different because their consumption isn't inherently conspicuous. I do it alone and talk about it with friends if I choose, but everyone sees the clothes I wear no matter what.

For example, I can choose to hide the fact that I love Katy Perry, but I can't hide the fact that LVMH made my handbag.

How you dress is a performance, and so the decision to wear something is filtered more rigorously through a social dimension than watching a movie or listening to a song is.

[encoderer]

In the context of my most previous reply above -- how would you feel about reccomendation algorithms that pull more visibly from your own social graph -- Friends, yes, but also people you follow on Twitter and Like on facebook.

That seems almost a perfect marriage of my comments on the innate human quality behind a nearest-neighbor algorithm your comments here.