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https://issues.apache.org/jira/browse/MAHOUT-305?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12837230#action_12837230
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Ankur commented on MAHOUT-305:
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*smile* There we go.
Our last steps are essentially different. I don't do any multiplication,
instead I just join (user, movie) on 'movie' with co-occurrence set followed
by a group on 'user' to calculate recommendations. I guess while joining I
should multiply ratings with co-occurrence counts for better evaluation.
Can you give a small illustrative example with dummy data to describe your last
steps?
> 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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