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From Alessandro Suglia <alessandro.sug...@yahoo.com>
Subject Re: Mahout recommendation in implicit feedback situation
Date Tue, 06 May 2014 05:51:44 GMT
I'm using the latest Mahout's release available in the Maven repository.

Thank you for your suggestion, I'll try it.

Alessandro Suglia

Il 06/mag/2014 07:10 Sebastian Schelter <ssc@apache.org> ha scritto:
>
> Alessandro, 
>
> which version of Mahout are you using? I had a look at the current 
> impl

ementation of GenericBooleanPrefUserBasedRecommender and its > doEstimatePreference method
returns the sum of similarities of users > that have also interacted with the item. So
that should be different > from either 0 or 1. > > --sebastian > > On 05/03/2014
05:00 PM, Alessandro Suglia wrote: > > Sorry Sebastian, maybe you haven't the possibility
to read the post on > > SO, so I'll report the code here. > > I've already used
the GenericBooleanPrefUserBasedRecommender in order to > > generate the recommendation
and the results are the same. > > > > |     DataModel  trainModel=  new 
FileDataModel(new > > File(String.valueOf(Main.class.getResource("/binarized/u1.base").getFile())));
> > > >      DataModel  testModel=  new  FileDataModel(new > > File(String.valueOf(Main.class.getResource("/binarized/u1.test").getFile())));
> > > >      UserSimilarity  similarity=  new > > TanimotoCoefficientSimilarity(trainModel);
> >      UserNeighborhood  neighborhood=  new  NearestNUserNeighborhood(35,
> > similarity,  trainModel); > > > >      GenericBooleanPrefUserBasedRecommender 
userBased=  new > > GenericBooleanPrefUserBasedRecommender(trainModel,  neighborhood,
> > similarity); > > > >      long  firstUser=  testModel.getUserIDs().nextLong(); 
// get the > > first user > > > >      // try to recommender items
for the first user > >      for(LongPrimitiveIterator  iterItem= > > testModel.getItemIDsFromUser(firstUser).iterator();
> > iterItem.hasNext();  )  { > >          long  currItem=  iterItem.nextLong();
> >          // estimates preference for the current item for the first user
> >          System.out.println("Estimated preference for item"  + > >
currItem+  " is"  +  userBased.estimatePreference(firstUser,  currItem)); > > >
>      } > > > > | > > > > Can you explain to me where is
the error in this code? > > > > Thank you. > > > > On 05/03/14 16:42,
Sebastian Schelter wrote: > >> You should try the > >> > >> org.apache.mahout.cf.taste.impl.recommender.GenericBooleanPrefUserBasedRecommender
> >> > >> > >> which has been built to handle such data. > >>
> >> Best, > >> Sebastian > >> > >> > >> On 05/03/2014
04:34 PM, Alessandro Suglia wrote: > >>> I have described it in the SO's post:
> >>> "When I execute this code, the result is a list of 0.0 or 1.0 which are
> >>> not useful in the context of top-n recommendation in implicit feedback >
>>> context. Simply because I have to obtain, for each item, an estimated > >>>
rate which stays in the range [0, 1] in order to rank the list in > >>> decreasing
order and construct the top-n recommendation appropriately." > >>> On 05/03/14
16:25, Sebastian Schelter wrote: > >>>> Hi Allessandro, > >>>>
> >>>> what result do you expect and what do you get? Can you give a concrete
> >>>> example? > >>>> > >>>> --sebastian >
>>>> > >>>> On 05/03/2014 12:11 PM, Alessandro Suglia wrote: >
>>>>> Good morning, > >>>>> I've tried to create a recommender
system using Mahout in an implicit > >>>>> feedback situation. What I'm
trying to do is explained exactlly in > >>>>> this > >>>>>
post on stack overflow: > >>>>> http://stackoverflow.com/questions/23077735/mahout-recommendation-in-implicit-feedback-situation.
> >>>>> > >>>>> > >>>>> > >>>>>
> >>>>> > >>>>> > >>>>> As you can see,
I'm having some problem with it simply because I > >>>>> cannot > >>>>>
get the result that I expect (a value between 0 and 1) when I try to > >>>>>
predict a score for a specific item. > >>>>> > >>>>> Someone
here can help me, please? > >>>>> > >>>>> Thank you in
advance. > >>>>> > >>>>> Alessandro Suglia > >>>>>
> >>>> > >>> > >> > > > > >
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