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 <[email protected]> To: [email protected] 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 <[email protected]> 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; > } > } > } > } >
