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From "Tamas Jambor (Commented) (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MAHOUT-737) Implicit Alternating Least Squares SVD
Date Fri, 13 Jan 2012 15:05:44 GMT

    [ https://issues.apache.org/jira/browse/MAHOUT-737?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13185622#comment-13185622
] 

Tamas Jambor commented on MAHOUT-737:
-------------------------------------

hi Sebastian,
I managed to run the code, it get reasonable results. I am a bit concerned with the memory
usage. Is there a more efficient way to store diagonal matrices? I assume the don't have to
be stored in DenseMatrix, as the storage and computation is not very efficient that case.
                
> Implicit Alternating Least Squares SVD
> --------------------------------------
>
>                 Key: MAHOUT-737
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-737
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Collaborative Filtering
>    Affects Versions: 0.6
>            Reporter: Tamas Jambor
>            Assignee: Sebastian Schelter
>         Attachments: MAHOUT-737-2.patch, MAHOUT-737.patch, MAHOUT-737.patch, MAHOUT-737.patch,
MAHOUT-737.patch
>
>
> I am sharing this Java implementation of mine that is based on the paper - Collaborative
Filtering with Implicit Datasets. The implementation is multi-treading and can be easily extended
to use it on Hadoop. In fact this approach would possibly work with non-implicit datasets,
but further testing is needed. The algorithm is tried and tested on an implicit TV-viewing
dataset, and the performance was pretty good (details to follow). 

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