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Posted to dev@mahout.apache.org by "Hui Wen Han (JIRA)" <ji...@apache.org> on 2010/04/19 18:51:50 UTC

[jira] Created: (MAHOUT-382) implement other recommendation

implement other recommendation
------------------------------

                 Key: MAHOUT-382
                 URL: https://issues.apache.org/jira/browse/MAHOUT-382
             Project: Mahout
          Issue Type: Wish
          Components: Collaborative Filtering
    Affects Versions: 0.4
            Reporter: Hui Wen Han
             Fix For: 0.4


I think that  recommendation has four types:

1)  recommend user with item (use case:content subscriber, generate the more  interesting content for user )
2)  recommend item to user (use case :advertisement pushing ,push the advertisement  to the people that is interested with)
3)  recommend item to item (use case; related content) 
4) recommend user to user (use case : people connection )
 
now org.apache.mahout.cf.taste.hadoop.item can recommend user with item,also can recommend item to user .
we have no off-line implement for 3) and 4). although we already implement the code in 1) and 2).



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[jira] Commented: (MAHOUT-382) implement other recommendation

Posted by "Jake Mannix (JIRA)" <ji...@apache.org>.
    [ https://issues.apache.org/jira/browse/MAHOUT-382?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12858601#action_12858601 ] 

Jake Mannix commented on MAHOUT-382:
------------------------------------

For 3) and 4), is there not methods currently like getSimilarUsers() in the recommenders?


> implement other recommendation
> ------------------------------
>
>                 Key: MAHOUT-382
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-382
>             Project: Mahout
>          Issue Type: Wish
>          Components: Collaborative Filtering
>    Affects Versions: 0.4
>            Reporter: Hui Wen Han
>            Assignee: Sean Owen
>             Fix For: 0.3
>
>
> I think that  recommendation has four types:
> 1)  recommend user with item (use case:content subscriber, generate the more  interesting content for user )
> 2)  recommend item to user (use case :advertisement pushing ,push the advertisement  to the people that is interested with)
> 3)  recommend item to item (use case; related content) 
> 4) recommend user to user (use case : people connection )
>  
> now org.apache.mahout.cf.taste.hadoop.item can recommend user with item,also can recommend item to user .
> we have no off-line implement for 3) and 4). although we already implement the code in 1) and 2).

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[jira] Resolved: (MAHOUT-382) implement other recommendation

Posted by "Sean Owen (JIRA)" <ji...@apache.org>.
     [ https://issues.apache.org/jira/browse/MAHOUT-382?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen resolved MAHOUT-382.
------------------------------

         Assignee: Sean Owen
    Fix Version/s: 0.3
                       (was: 0.4)
       Resolution: Not A Problem

I believe the discussion in MAHOUT-381 applies here too. You're right that the framework could be used for any such use cases. The naming in the code is intentional, to make it more intuitive and match literature.

> implement other recommendation
> ------------------------------
>
>                 Key: MAHOUT-382
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-382
>             Project: Mahout
>          Issue Type: Wish
>          Components: Collaborative Filtering
>    Affects Versions: 0.4
>            Reporter: Hui Wen Han
>            Assignee: Sean Owen
>             Fix For: 0.3
>
>
> I think that  recommendation has four types:
> 1)  recommend user with item (use case:content subscriber, generate the more  interesting content for user )
> 2)  recommend item to user (use case :advertisement pushing ,push the advertisement  to the people that is interested with)
> 3)  recommend item to item (use case; related content) 
> 4) recommend user to user (use case : people connection )
>  
> now org.apache.mahout.cf.taste.hadoop.item can recommend user with item,also can recommend item to user .
> we have no off-line implement for 3) and 4). although we already implement the code in 1) and 2).

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