No, i only breifely scanned Elkan and Mohan's. not really in the same details as I did the Yahoo research's paper.
I am not saying they are not doing that. I am just saying there's a case for generalizing Bayesian hierarchy instead of constraining it to two particular models in a particular order with a particular link function. On Wed, Dec 29, 2010 at 3:22 PM, Ted Dunning <[email protected]> wrote: > Are you sure that you read the Elkan and Mohan paper? > > They tested this cold-start process. And got real results. > > On Wed, Dec 29, 2010 at 2:29 PM, Dmitriy Lyubimov <[email protected]> > wrote: > > > Also, another observation they were making was that if we learn latent > > links > > and regression based on static user/item profiles as a first stage model, > > and then > > add model that considers side information as a second stage (when first > > stage is being frozen) then we can have reasonable prediction for a user > > based on its > > profile out of the door before the user has yet to make any ratings (i.e. > > before any side information has been available). Thus they say it is a > > reasonable cold start > > solution (which i think was part of the inquery in the original post, > they > > say they add 100s users per day i would like to make recommendations out > of > > the door). i think they implied that was a technique that yahoo media was > > using. > > >
