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Posted to dev@mahout.apache.org by "Dmitriy Lyubimov (JIRA)" <ji...@apache.org> on 2013/11/26 01:04:35 UTC

[jira] [Created] (MAHOUT-1365) Weighted ALS-WR iterator for Spark

Dmitriy Lyubimov created MAHOUT-1365:
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             Summary: Weighted ALS-WR iterator for Spark
                 Key: MAHOUT-1365
                 URL: https://issues.apache.org/jira/browse/MAHOUT-1365
             Project: Mahout
          Issue Type: Task
            Reporter: Dmitriy Lyubimov
            Assignee: Dmitriy Lyubimov
             Fix For: Backlog


Given preference P and confidence C distributed sparse matrices, compute ALS-WR solution for implicit feedback (Spark Bagel version).

Following Hu-Koren-Volynsky method (stripping off any concrete methodology to build C matrix), with parameterized test for convergence.

The computational scheme is followsing ALS-WR method (which should be slightly more efficient for sparser inputs). 

The best performance will be achieved if non-sparse anomalies prefilitered (eliminated) (such as an anomalously active user which doesn't represent typical user anyway).

the work is going here https://github.com/dlyubimov/mahout-commits/tree/dev-0.9.x-scala. I am porting away our (A1) implementation so there are a few issues associated with that.



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