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

["Dmitriy Lyubimov (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/MAHOUT-1365?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13832110#comment-13832110 ] 

Dmitriy Lyubimov edited comment on MAHOUT-1365 at 11/26/13 12:26 AM:
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Oh. One thing to mention is that the confidence matrix C is not sparse per se. but if there's a base confidence c_0 such that subtracting it from each element of C turns it into sparse matrix C', then we can use that matrix as an input (along with c_0 parameter). This is further clarified in the attachment (which is basically just a conspect of both papers for my own sake.) See attached.


was (Author: dlyubimov):
Oh. the confidence matrix C is not sparse per se. but if there's a base confidence c_0 such that subtracting it from each element of C turns it into sparse matrix C', then we can use that matrix as an input (along with c_0 parameter). This is further clarified in the attachment (which is basically just a conspect of both papers for my own sake.) See attached.

> 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
>
>         Attachments: distributed-als-with-confidence.pdf
>
>
> 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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