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https://issues.apache.org/jira/browse/MAHOUT-877?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sebastian Schelter updated MAHOUT-877:
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Attachment: MAHOUT-877.patch
> Enable the parallel ALS recommender to use implicit feedback data
> -----------------------------------------------------------------
>
> Key: MAHOUT-877
> URL: https://issues.apache.org/jira/browse/MAHOUT-877
> Project: Mahout
> Issue Type: New Feature
> Components: Collaborative Filtering
> Affects Versions: 0.6
> Reporter: Sebastian Schelter
> Assignee: Sebastian Schelter
> Attachments: MAHOUT-877.patch
>
>
> Mahout's ParallelALSFactorizationJob offers a distributed matrix
> factorization for computing recommendations. The current implementation is
> only suited for explicit feedback data (ratings) unfortunately.
> The majority of usecases has to work with implicit feedback however. The
> paper "Collaborative Filtering for Implicit Feedback Datasets"
> http://research.yahoo.com/pub/2433 describes a closely related approach that
> is aimed at implicit feedback data and should easily be integratable into the
> current ParallelALSJob.
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