I think I see the picture now. Thanks!
On Mon, May 6, 2013 at 5:25 PM, Ted Dunning <[email protected]> wrote: > On Mon, May 6, 2013 at 12:50 PM, Koobas <[email protected]> wrote: > > > Since Dominik mentioned item-based and ALS, let me throw in a question > > here. > > I believe that one of the Netflix price solutions combined KNN and ALS. > > > > 1) What is the best way to combine the results of both? > > > > I think that combinations are important, but I think that the combination > of very similar kinds of algorithms working on essentially the same data > has almost no practical impact. > > 2) Is there really merit to this approach? > > > > Yes, but. > > > > 3) Are there other combinations that make sense? > > (user-based + item-based)? > > > > Absolutely. > > But I really think that the real mileage for improvement comes from the > following: > > a) combining different kinds of behavior into a single recommendation > framework > > b) judicious use of dithering to improve exploration > > c) substantial UI improvements to gather additional exploratory data for > the recommendation engine > > d) principled testing framework for design and algorithmic alternatives > > Minor algorithmic changes are almost not visible on the priority list. > Once you hit "pretty-good" there are far more important things to take on > in a real rec engine project. >
