[ 
https://issues.apache.org/jira/browse/MAHOUT-1004?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13704407#comment-13704407
 ] 

Saleem Ansari commented on MAHOUT-1004:
---------------------------------------

To understand how the user-based recommender would work, I have re-based the 
user-based recommender patch against trunk codebase. Now it compiles fine. 
However the tests are failing.


What I basically changed?

 * Use the latest API e.g. PriorityQueue instead of TopK, nonZeros.iterator() 
instead of iterateNonZero().

Test failures: http://pastebin.com/PxdQ4qw2

 * I think my ( Cygwin ) environment is not setup properly, hence the 
permission issues, due to which some tests are failing.


Please have a look at the updated patch: 
[^MAHOUT-1004-trunk-rebased-but-tests-fail.patch]. In the meantime I will 
understand what would need to be re-factored and try to fix the test cases.


                
> Distributed User-based Collaborative Filtering
> ----------------------------------------------
>
>                 Key: MAHOUT-1004
>                 URL: https://issues.apache.org/jira/browse/MAHOUT-1004
>             Project: Mahout
>          Issue Type: New Feature
>          Components: Collaborative Filtering
>    Affects Versions: 0.7
>            Reporter: Kris Jack
>            Priority: Minor
>              Labels: Recommender, User-based
>             Fix For: Backlog
>
>         Attachments: MAHOUT-1004.patch, 
> MAHOUT-1004-trunk-rebased-but-tests-fail.patch
>
>   Original Estimate: 336h
>  Remaining Estimate: 336h
>
> I'd like to contribute code that implements a distributed user-based 
> collaborative filtering algorithm.
> In brief, so far I've taken the code for the existing 
> org.apache.mahout.cf.taste.hadoop.item.RecommenderJob and created a new 
> org.apache.mahout.cf.taste.hadoop.user.RecommenderJob.  With help from Sean 
> Owen, I followed a similar approach to the item-based implementation, but 
> multiplied a user-user matrix with a user-item vector rather than an 
> item-item matrix with an item-user vector.  The result of the multiplication 
> then needs to be transposed in order to output recommendations by user id.

--
This message is automatically generated by JIRA.
If you think it was sent incorrectly, please contact your JIRA administrators
For more information on JIRA, see: http://www.atlassian.com/software/jira

Reply via email to