The Need for Good Item Recommendation Systems

As discussed in a recent study group paper in which I participated, the online item recommendation systems currently employed are really crappy. A major problem stems from data sparsity because people's actual preferences are determined by what is known as the "long tail," which refers to the idea of rare events (where data is quite sparse) being the most important determining factor of something. (OK, what I wrote isn't a mathematical definition. See our discussion in the paper.) For example, you can't reasonably tell very much about which Wii games I might like based on the fact that I bought Super Smash Brother Brawl because so many people bought it. (You can certainly narrow things down to the fact that I might want games for the Wii as opposed to picking a system at random.) Instead, you would need to go to one of my preferences that is much less common to indicate what my preferences actually are. Then the trouble becomes how to do this effectively because the data sparsity in such regimes makes it hard to do such things effectively. It's quite mathematically challenging. Anyway, the reason I write this now is that because of the fact that I bought Super Smash Brothers Brawl, I have just gotten an e-mail from Amazon suggesting that I might also like to purchase Onechanbara: Bikini Zombie Slayers. Um, no thanks.