On Sat, Feb 20, 2010 at 12:46 PM, Claudio Martella <[email protected]> wrote: > Can we rephrase jamborta's idea by saying that an item's neighboorhood > can be created by putting > "around" an item all those items that have been rated by the same users > with similar ratings?
Yes, that's how I would define a neighborhood around anything: things that are similar / closest. "Similar" could indeed be based on user ratings (this is what PearsonCorrelationSimilarity does). > neighboorhood for items. What you can do now, is take your user's items > and see what's near them. > > This is probably a rephrase of user-based recommendation, though. I wouldn't say you're describing user-based reocommendation. You've correctly described defining a neighborhood of similar items. This is how ItemBasedRecommender.mostSimilarItems() works, indeed. But that method is not computing recommendations. And I thought the question was, why doesn't an item neighborhood enter into a recommender computation? It doesn't at the moment, and I mentioned above how it could, but why it might not help or be beneficial. But I haven't tried it. But yes maybe that remains the issue here... what's the question exactly about item neighborhoods? Their definition is clear; the use is not as much.
