On Sat, Dec 12, 2009 at 8:09 AM, Ted Dunning <ted.dunn...@gmail.com> wrote: > On Fri, Dec 11, 2009 at 5:48 PM, Sean Owen <sro...@gmail.com> wrote: > >> While it would be nice to integrate this approach harmoniously into >> the existing item-based recommender implementation, it's no big deal >> to add in a different style of item-based recommender. Just hoping to >> avoid repetition where possible; the project is already becoming a >> rich and varied but intimidating bag of tools to solve the same >> problem. >> > > It should be pretty harmonious as far as the off-line part is concerned, but > the on-line part is likely to be considerably less flexible if only because > scoring has to fit the lucene mold. > > This is still a very powerful deployment strategy.
I'm into it because it does, it seems, address a gap in content-based recommendation. It's also not as if it means everyone using any implementation needs Lucene now. And if you do implement Recommender then it fits very cleanly into the framework and you get benefits there. The idea of the recommender and the backing store (DataModel) are purposely quite separate so there's no assumption to work around there. > You are right that general similarity is a but much, but anything that can > be expressed as a set of terms in in-scope. Recommendations can be > meta-data or history driven. Both are valuable and both are easily combined > in a Lucene-ish framework. I think we're all on the same page then, I agree that this is also a gap and a need. It goes without saying I'd be pleased for anyone to do some work in that area as I think it all completely fits into the framework.
