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https://issues.apache.org/jira/browse/MAHOUT-305?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12837156#action_12837156
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Sean Owen commented on MAHOUT-305:
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You don't entirely drop ratings, it's that they don't figure into the
similarity metric, right? But yes, ratings are not relevant to the point I was
trying to make. Regardless, Harry Potter 3 is a better recommendation.
I really think you have to take out the highest-rated items or this is a fairly
flawed test, for this reason. Does anyone else have experience in or thoughts
on defining precision and recall in this context? 3,4,5 is arbitrary, just pick
the top n, or top n%, I'd imagine.
> 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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