On Jun 19, 2009, at 8:47 AM, Sean Owen wrote:
On Fri, Jun 19, 2009 at 8:40 AM, Grant
Ingersoll<[email protected]> wrote:
I don't know, "Programming Collective Intelligence" (page 17) seems
to
suggest transposing as being pretty useful for product-product
suggestions.
I suppose, however, that it really is just getting the
neighborhood then
and not going the extra step of getting items (er users in this
case).
The main cost is in having a second model in memory, I suppose.
Yes, I mean, it works. I think they were showing this approach for
simplicity and brevity. By turning a user-based recommender on its
side you kind of get an item-based recommender, which is computing
item-item similarities under the hood, and indeed that is the basis of
what you want. My suggestion a) just goes straight to that.
Yeah, Taste's TopItems is the equiv of the topMatches() method in the
book, it seems.
Also, as opposed to calling TopItems directly, I could just call the
mostSimilarItems method on GenericBasedItemRecommender, right? That
way I can rely on the recommender for the Estimator, etc. and the API
seems cleaner.
