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From Parimi Rohit <rohit.par...@gmail.com>
Subject Re: Bi-Factorization vs Tri-Factorization for recommender systems
Date Mon, 01 Dec 2014 16:48:28 GMT
Thanks for your reply Ted!!

To summarize, if I am interested in constraining (normalizing) both user
and item vectors, then tri-factorization is a better approach. But if I
want only one, either user or item features, then bi-factorization works.

Please correct me if I understood it incorrectly.

Also, is there any implementation in Mahout that allows me to tri-factorize
user-item preferences (implicit feedback)? If not, are there any other
alternatives?

Thanks,
Rohit






On Mon, Nov 24, 2014 at 11:28 AM, Ted Dunning <ted.dunning@gmail.com> wrote:

> There is no inherent mathematical difference, but there may be some pretty
> significant practical differences.
>
> Using the three matrix form (X = USV') puts the normalization constants
> into a place where you can control them a bit easier.  This can be useful
> if you want *both* user and item vectors that are normalized.
>
> If you only want item vectors, then it really doesn't matter since you can
> incorporate as much of S as you like into the item vectors as you like and
> the rest winds up in the factor that you aren't looking at anyway.
>
>
>
> On Thu, Nov 20, 2014 at 1:34 AM, Parimi Rohit <rohit.parimi@gmail.com>
> wrote:
>
> > Hi All,
> >
> > Are there any (dis)advantages of using tri-factorization (||X - USV'||)
> as
> > opposed to bi-factorization ((||X - UV'||)) for recommender systems? I
> have
> > been reading a lot about tri-factorization and how they can be seen as
> > co-clustering of rows and columns and was wondering if such as technique
> is
> > implemented in Mahout?
> >
> > Also, I am particularly interested in implicit-feedback datasets and the
> > only MF approach I am aware of is the ALS-WR for implicit feedback data
> > implemented in mahout. Are there any other MF techniques? If not, is it
> > possible (and useful) to extend some tri-factorization to handle
> > implicit-feedback along the lines of "Collaborative Filtering for
> Implicit
> > Feedback Datasets" (the approach implemented in Mahout).
> >
> > I apologize for any inconvenience as this question is very general and
> > might not be relevant to Mahout and I would really appreciate any
> > thoughts/feedback.
> >
> > Thanks,
> > Rohit
> >
>

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