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https://issues.apache.org/jira/browse/MAHOUT-737?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen reassigned MAHOUT-737:
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Assignee: Sebastian Schelter
My one significant concern with the patch is that it is introducing JAMA,
instead of using Mahout matrix representations and methods. Now, that's not to
say we shouldn't use JAMA or even move to it, but it's a different question.
How hard is it to not use JAMA?
Otherwise looking great.
> Implicit Alternating Least Squares SVD
> --------------------------------------
>
> Key: MAHOUT-737
> URL: https://issues.apache.org/jira/browse/MAHOUT-737
> Project: Mahout
> Issue Type: Improvement
> Reporter: Tamas Jambor
> Assignee: Sebastian Schelter
> Attachments: 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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