I have been reading up on gradient boosting machines, and in particular GBRT's. I've come across numerous mentions (and finally tracked down some papers) on applying these models to ranking problems - particularly in web search.
Is there any particular motivation for using GBRT's for ranking problems? I assume any classifier that outputs a probability could be used for ranking problems as well. Does the flexibility in choice of loss function motivate this choice? Or is it mainly that empirical results with GBRT's greatly outperform other methods? Any insight would be appreciated.