Since Dominik mentioned item-based and ALS, let me throw in a question here.
I believe that one of the Netflix price solutions combined KNN and ALS.
1) What is the best way to combine the results of both?
2) Is there really merit to this approach?
3) Are there other combinations that make sense?
(user-based + item-based)?
On Mon, May 6, 2013 at 3:35 PM, Dominik Hübner <cont...@dhuebner.com> wrote:
> Well, as you already might have guessed, I am building a product
> recommender system for my thesis.
>
> I am planning to evaluate ALS (both, implicit and explicit) as well as
> item -similarity recommendation for users with at least a few known
> products. Nevertheless, the majority of users only has seen a single (or
> 2-3) product(s). I want to recommend them the most popular items from
> clusters, their only product comes from (as a workaround for the cold-start
> problem). Furthermore, I expect to be able to see which "kind" of products
> users like. This might provide me some information about how well ALS and
> similarity recommenders fit the user's area of interest (an early
> evaluation) or at least to estimate if the chosen approach will work in
> some way.
>
> On May 6, 2013, at 9:09 PM, Ted Dunning <ted.dunn...@gmail.com> wrote:
>
> > I don't even think that clustering is all that necessary.
> >
> > The reduced cooccurrence matrix will give you items related to each item.
> >
> > You can use something like PCA, but SVD is just as good here due to near
> > zero mean. You could SSVD or ALS from Mahout to do this analysis and
> then
> > use k-means on the right singular vectors (aka item representation).
> >
> > What is the high level goal that you are trying to solve with this
> > clustering?
> >
> >
> >
> >
> > On Mon, May 6, 2013 at 12:01 PM, Dominik Hübner <cont...@dhuebner.com
> >wrote:
> >
> >> And running the clustering on the cooccurrence matrix or doing PCA by
> >> removing eigenvalues/vectors?
> >>
> >> On May 6, 2013, at 8:52 PM, Ted Dunning <ted.dunn...@gmail.com> wrote:
> >>
> >>> On Mon, May 6, 2013 at 11:29 AM, Dominik Hübner <cont...@dhuebner.com
> >>> wrote:
> >>>
> >>>> Oh, and I forgot how the views and sales are used to build product
> >>>> vectors. As of now, I implemented binary vectors, vectors counting the
> >>>> number of views and sales (e.g 1view=1count, 1sale=10counts) and
> >> ordinary
> >>>> vectors ( view => 1, sale=>5).
> >>>>
> >>>
> >>> I would recommend just putting the view and sale in different columns
> and
> >>> doing cooccurrence analysis on this.
> >>
> >>
>
>
