MapReduce implementation of ALS-WR
----------------------------------
Key: MAHOUT-542
URL: https://issues.apache.org/jira/browse/MAHOUT-542
Project: Mahout
Issue Type: New Feature
Components: Collaborative Filtering
Affects Versions: 0.5
Reporter: Sebastian Schelter
As Mahout is currently lacking a distributed collaborative filtering algorithm
that uses matrix factorization, I spent some time reading through a couple of
the Netflix papers and stumbled upon the "Large-scale Parallel Collaborative
Filtering for the Netflix Prize" available at
http://www.hpl.hp.com/personal/Robert_Schreiber/papers/2008%20AAIM%20Netflix/netflix_aaim08(submitted).pdf.
It describes a parallel algorithm that uses "Alternating-Least-Squares with
Weighted-λ-Regularization" to factorize the preference-matrix and gives some
insights on how the authors distributed the computation using Matlab.
It seemed to me that this approach could also easily be parallelized using
Map/Reduce, so I sat down and created a prototype version. I'm not really sure
I got the mathematical details correct (they need some optimization anyway),
but I wanna put up my prototype implementation here per Yonik's law of patches.
Maybe someone has the time and motivation to work a little on this with me. It
would be great if someone could validate the approach taken (I'm willing to
help as the code might not be intuitive to read) and could try to factorize
some test data and give feedback then.
--
This message is automatically generated by JIRA.
-
You can reply to this email to add a comment to the issue online.
