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https://issues.apache.org/jira/browse/MAHOUT-321?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved MAHOUT-321.
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Resolution: Fixed
Committed
> Rationalize use of similarity metrics as weights in user-based, item-based
> recommendation
> -----------------------------------------------------------------------------------------
>
> Key: MAHOUT-321
> URL: https://issues.apache.org/jira/browse/MAHOUT-321
> Project: Mahout
> Issue Type: Improvement
> Components: Collaborative Filtering
> Affects Versions: 0.2
> Reporter: Sean Owen
> Assignee: Sean Owen
> Priority: Minor
> Fix For: 0.4
>
>
> See this thread: http://old.nabble.com/weighted-score-td27686783.html
> In short, using similarity values as weights in a weighted average is
> problematic since they can be negative. This can result in weighted averages
> well out of range of possible preference values, even infinite. The current
> solution simply moves the values from [-1,1] to [0,2] but this has
> undesirable effects like giving weight of 1 to entities with no similarity.
> Tamas advances, and Ted refined, a convincing argument that negative weights
> can be handled in a different way which doesn't require them to be
> arbitrarily shifted. It is simply a matter of capping the estimated
> preference at the max or min value the preference value can take on.
> It's possible for the framework to track this max/min value observed in the
> data, and do the capping, with little performance impact. Hence I want to
> make this change after 0.3 is released.
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