I think it would be better to add a parameter to the recommend() methods so that this can be decided on a per invocation basis.

--sebastian

On 05/02/2014 09:40 AM, dodi hakim wrote:
Thanks,

My proposed solution for this is to add  a method in Recommender interface
(e.g isUserItemInclude) and pass a Recommender class in method
  getCandidateItem in both CandidateItemStrategy and
MostSimilarItemsCandidateItemsStrategy interfaces. For example, in  method
doGetCandidateItems of PreferredItemsNeighborhoodCandidateItemsStrategy
class - that implements these two interfaces, it has line
possibleItemsIDs.removeAll(preferredItemIDs) to remove user's preferable
items.

In addition, we need to list which Recommender classes that including/not
user's item in returned recommendation.

Any advice and suggestions will be greatly appreciate.

Thanks,


Dodi








On 2 May 2014 16:53, Sebastian Schelter (JIRA) <[email protected]> wrote:


      [
https://issues.apache.org/jira/browse/MAHOUT-1428?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel]

Sebastian Schelter reopened MAHOUT-1428:
----------------------------------------


here you are

Recommending already consumed items
-----------------------------------

                 Key: MAHOUT-1428
                 URL: https://issues.apache.org/jira/browse/MAHOUT-1428
             Project: Mahout
          Issue Type: Bug
          Components: Collaborative Filtering
            Reporter: Mario Levitin
             Fix For: 1.0


Mahout does not recommend items which are already consumed by the user.
For example,
In the getAllOtherItems method of GenericUserBasedRecommender class
there is the following line
possibleItemIDs.removeAll(dataModel.getItemIDsFromUser(theUserID));
which removes user's items from the possibleItemIDs to prevent these
items from being recommended to the user. This is ok for many
recommendation cases but for many other cases it is not.
The Recommender classes  (I mean all of them, NN-based and SVD-based as
well as hadoop and non-hadoop versions) might have a parameter for this for
excluding or not excluding user items in the returned recommendations.



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