What item similarity metric are you using? Log-likelihood tends to account for an item's baseline popularity and normalize it away. So a best-seller isn't similar to an item just because it's a best-seller and shows up a lot, but because it shows up an unusually large number of times, even granting it's a best seller. Try that if you're not already using it.
On Mon, Dec 26, 2011 at 4:01 PM, Valentin Pletzer <[email protected]> wrote: > Hi, > > I am trying to achieve some item-to-item-recommendations and the setup > works quite well. But one thing I stumbled across is that some items are so > popular that they are a recommendation for nearly every other item. In the > Amazon paper they say that they are sampling the bestseller buying > customers. Do I have to do this preprocessing step myself or does Mahout > help with that? > > Thanks > Valentin
