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.dunn...@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.par...@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 > > >