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Posted to dev@mahout.apache.org by "Sebastian Schelter (JIRA)" <ji...@apache.org> on 2010/11/26 21:10:14 UTC
[jira] Created: (MAHOUT-553) Unify ranking of boolean
recommendations in distributed and non-distributed recommenders
Unify ranking of boolean recommendations in distributed and non-distributed recommenders
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Key: MAHOUT-553
URL: https://issues.apache.org/jira/browse/MAHOUT-553
Project: Mahout
Issue Type: Improvement
Components: Collaborative Filtering
Affects Versions: 0.5
Reporter: Sebastian Schelter
When use a weighted some for preference estimation on boolean data the predicted preferences can only be 1 or NaN which is mathematically correct but not very useful for ranking them. The distributed recommender should adapt the behavior of GenericBooleanPrefItemBasedRecommender in that case: use the sums of similarities to rank the recommended items.
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[jira] Commented: (MAHOUT-553) Unify ranking of boolean
recommendations in distributed and non-distributed recommenders
Posted by "Hudson (JIRA)" <ji...@apache.org>.
[ https://issues.apache.org/jira/browse/MAHOUT-553?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12936129#action_12936129 ]
Hudson commented on MAHOUT-553:
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Integrated in Mahout-Quality #482 (See [https://hudson.apache.org/hudson/job/Mahout-Quality/482/])
> Unify ranking of boolean recommendations in distributed and non-distributed recommenders
> ----------------------------------------------------------------------------------------
>
> Key: MAHOUT-553
> URL: https://issues.apache.org/jira/browse/MAHOUT-553
> Project: Mahout
> Issue Type: Improvement
> Components: Collaborative Filtering
> Affects Versions: 0.5
> Reporter: Sebastian Schelter
> Fix For: 0.5
>
>
> When using a weighted sum for preference estimation on boolean data, the predicted preferences can only be 1 or NaN which is mathematically correct but not very useful for ranking them. The distributed recommender should therefore adapt the behavior of GenericBooleanPrefItemBasedRecommender in that case: use the sums of similarities to rank the recommended items.
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[jira] Updated: (MAHOUT-553) Unify ranking of boolean
recommendations in distributed and non-distributed recommenders
Posted by "Sebastian Schelter (JIRA)" <ji...@apache.org>.
[ https://issues.apache.org/jira/browse/MAHOUT-553?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sebastian Schelter updated MAHOUT-553:
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Description: When using a weighted sum for preference estimation on boolean data, the predicted preferences can only be 1 or NaN which is mathematically correct but not very useful for ranking them. The distributed recommender should therefore adapt the behavior of GenericBooleanPrefItemBasedRecommender in that case: use the sums of similarities to rank the recommended items. (was: When use a weighted some for preference estimation on boolean data the predicted preferences can only be 1 or NaN which is mathematically correct but not very useful for ranking them. The distributed recommender should adapt the behavior of GenericBooleanPrefItemBasedRecommender in that case: use the sums of similarities to rank the recommended items.)
> Unify ranking of boolean recommendations in distributed and non-distributed recommenders
> ----------------------------------------------------------------------------------------
>
> Key: MAHOUT-553
> URL: https://issues.apache.org/jira/browse/MAHOUT-553
> Project: Mahout
> Issue Type: Improvement
> Components: Collaborative Filtering
> Affects Versions: 0.5
> Reporter: Sebastian Schelter
>
> When using a weighted sum for preference estimation on boolean data, the predicted preferences can only be 1 or NaN which is mathematically correct but not very useful for ranking them. The distributed recommender should therefore adapt the behavior of GenericBooleanPrefItemBasedRecommender in that case: use the sums of similarities to rank the recommended items.
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[jira] Resolved: (MAHOUT-553) Unify ranking of boolean
recommendations in distributed and non-distributed recommenders
Posted by "Sebastian Schelter (JIRA)" <ji...@apache.org>.
[ https://issues.apache.org/jira/browse/MAHOUT-553?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sebastian Schelter resolved MAHOUT-553.
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Resolution: Fixed
Fix Version/s: 0.5
> Unify ranking of boolean recommendations in distributed and non-distributed recommenders
> ----------------------------------------------------------------------------------------
>
> Key: MAHOUT-553
> URL: https://issues.apache.org/jira/browse/MAHOUT-553
> Project: Mahout
> Issue Type: Improvement
> Components: Collaborative Filtering
> Affects Versions: 0.5
> Reporter: Sebastian Schelter
> Fix For: 0.5
>
>
> When using a weighted sum for preference estimation on boolean data, the predicted preferences can only be 1 or NaN which is mathematically correct but not very useful for ranking them. The distributed recommender should therefore adapt the behavior of GenericBooleanPrefItemBasedRecommender in that case: use the sums of similarities to rank the recommended items.
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