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.
<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
