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From James James <recommendersys...@yahoo.com>
Subject Re: recommender on binary data
Date Tue, 03 Nov 2009 13:46:08 GMT
Hi, Thanks for the reply. In fact, the code I quote comes from the class BooleanUserGenericUserBasedRecommender.
I do not know if that is what you refer to as GenericBooleanPrefBasedRecommender. I could
not find a class by the name GenericBooleanPrefBasedRecommender under org.apache.mahout.cf.taste.impl.recommender.
 
Thanks again.




________________________________
From: Sean Owen <srowen@gmail.com>
To: mahout-user@lucene.apache.org
Sent: Tue, November 3, 2009 1:13:39 AM
Subject: Re: recommender on binary data

Not sure if I ever asked on this thread: are you using
GenericBooleanPrefUserBasedRecommender? this is the class that alters
GenericUserBasedRecommender with this abused notion of estimated
preference. The code you quote is not from
GenericBooleanPrefUserBasedRecommender.

On Tue, Nov 3, 2009 at 2:50 AM, James James <recommendersystem@yahoo.com> wrote:
> It has been a while since we talked about this topic, but the score returned is not just
adding up the similarity values that anybody in the neighborhood has to the item. IT is atucally
devided by the totalSimilarity. As result, I think the score is still 1.0. Did I miss something?
See the codes below.
>  for(User user : theNeighborhood) {if(!user.equals(theUser)) {// See GenericItemBasedRecommender.doEstimatePreference()
tooPreference pref = user.getPreferenceFor(itemID);
> preference += theSimilarity * pref.getValue();
> totalSimilarity += theSimilarity;
> }
> }
> }
> }
>



      
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