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From Pat Ferrel <>
Subject Re: Mahout recommendation in implicit feedback situation
Date Sat, 03 May 2014 21:06:12 GMT
Actually the regular cooccurrence recommender should work too. Your example on Stackoverflow
is calling the wrong method to get recs, call .recommend(uersId) to get an ordered list of
ids with strengths.

It looks to me like you are getting preference data from the user, which in this case is 1
or 0—not recommendations.

On May 3, 2014, at 7:42 AM, Sebastian Schelter <> wrote:

You should try the

which has been built to handle such data.


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:
>>> <>
>>> 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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