Raju,
like Sebastian said, it probably due to the default sampling restriction of
hadoop-based implementation.
<blockquote>
maxPrefsPerUserInItemSimilarity", "max number of preferences to consider
per user in the "
+ "item similarity computation phase, users with more
preferences will be sampled down (default: 1000)
<blockquote>
You could check your data to see if there are many users whose preferences
are over 1000?
On Fri, Mar 29, 2013 at 12:53 AM, ch raju <[email protected]> wrote:
> yeah, recommendations are completely different, out of 10 only one
> suggestion got matched..
> which neighborhoods are you asking about ? I am new to this, didn't
> understand..
>
> Thanks & regards,
> Raju
>
> On Thu, Mar 28, 2013 at 8:25 PM, Koobas <[email protected]> wrote:
>
> > Are the suggestions completely different, or somewhat different?
> > What about the neighborhoods?
> >
> >
> > On Thu, Mar 28, 2013 at 10:09 AM, ch raju <[email protected]> wrote:
> >
> > > Hi all,
> > > I am working on mahout-0.7 recommendations, ran following command
> from
> > > the command line
> > > ./bin/mahout recommenditembased --input UserData.csv --output output/
> > > --similarityClassname SIMILARITY_PEARSON_CORRELATION
> --numRecommendations
> > > 10
> > > got the recommendations for every user.
> > > I deployed the Mahout integration war in the localhost and executed the
> > > url(
> > >
> > >
> >
> http://localhost:8080/mahout-integration-0.7/RecommenderServlet?userID=47639&howMany=10
> > > ),
> > > got the results, but when i compare the recommendations of above and
> this
> > > for the 47639 user then results are completely different.
> > >
> > > I am using GenericItemBasedRecommender with Pearson Correlation
> > similarity
> > > and the same input file. I would like to know why i am getting
> different
> > > results? Both are item based only right? Which recommender is
> > > recommenditembased using?
> > >
> > > --
> > > Thanks & Regards,
> > > Raju Chinthala
> > >
> >
>
>
>
> --
> Thanks & Regards,
> Raju Chinthala
>
