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From "Sean Owen (JIRA)" <j...@apache.org>
Subject [jira] Commented: (MAHOUT-305) Combine both cooccurrence-based CF M/R jobs
Date Tue, 23 Feb 2010 11:58:27 GMT

    [ https://issues.apache.org/jira/browse/MAHOUT-305?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12837209#action_12837209
] 

Sean Owen commented on MAHOUT-305:
----------------------------------

They don't influence the similarity metric but they do influence the estimated ratings and
therefore recommendations. Are we talking about the same algorithm? The last step is to multiply
the co-occurrence matrix by the user -rating- vector.

> Combine both cooccurrence-based CF M/R jobs
> -------------------------------------------
>
>                 Key: MAHOUT-305
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-305
>             Project: Mahout
>          Issue Type: Improvement
>          Components: Collaborative Filtering
>    Affects Versions: 0.2
>            Reporter: Sean Owen
>            Assignee: Ankur
>            Priority: Minor
>
> We have two different but essentially identical MapReduce jobs to make recommendations
based on item co-occurrence: org.apache.mahout.cf.taste.hadoop.{item,cooccurrence}. They ought
to be merged. Not sure exactly how to approach that but noting this in JIRA, per Ankur.

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