Yes, this is a simpler problem. You just want to find which items are most similar to a given item, for some definition of 'similar'. GenericItemBasedRecommender has a mostSimilarItems() method that just saves you the trouble of computing this by hand, and any ItemSimiliarity function you like can be used.
On Sun, Aug 29, 2010 at 7:26 PM, Ted Dunning <[email protected]> wrote: > These are examples of what I call cross-recommendation where you have user x > item1 and user x item2 data and you > want item1 => item2 recommendations. > > All of the standard techniques apply (user-based, LLR cooccurrence, SVD, > latent factor models), but you have to rejigger things here > and there. > > Sean, can Mahout's recommendation system do this cross recommendation? >
