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 <[email protected]> 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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