It looks reasonable to me; what works best for your data will only be
revealed with some testing of different algorithms. For example try
LogLikelihoodSimilarity.
On Fri, Nov 12, 2010 at 3:41 PM, bejoy ks <bejoyks@hotmail.com> wrote:
>
> Thanks a lot Owen. One more small favor,hope its fine for you.
> I'd like to get your suggestion on my implementation of my Item
> based recommendation over the same data set.(data set with no
> preference value).
>
> The sample code i have used is given below, it works fine with
> recommendations being produced. Could you please look into it and just
> verify whether the use of ItemSimilarity and ItemBasedRecommender are the
> best suited ones for Boolean data sets.
>
>
>
> //item similarity recommendation based on User Id
>
> FileDataModel dataModel = new FileDataModel(new File(recsFile));
>
> ItemSimilarity itemSimilarity = new
> TanimotoCoefficientSimilarity(dataModel);
>
> ItemBasedRecommender recommender =new
> GenericItemBasedRecommender(dataModel, itemSimilarity);
>
> List<RecommendedItem> recommendations
> =recommender.recommend(userId, noOfRecommendations);
>
> System.out.println(recommendations);
>
>
>
> //item similarity recommendation based on Item Id
>
> recommendations= recommender.mostSimilarItems(itemId,
> noOfRecommendations);
>
> System.out.println(recommendations);
>
>
>
> Please let me know you suggestions and comments on the code snippet. Is
> this the right way to so Item based recommendations on Boolean data
> sets?
>
> Thanks and Regards
> Bejoy.K.S
>
>
>
>
> > Date: Fri, 12 Nov 2010 15:34:03 +0000
> > Subject: Re: Mahout - Help needed - files with no preferences and
> integarting mahout with Hadoop
> > From: srowen@gmail.com
> > To: user@mahout.apache.org
> >
> > http://manning.com/owen
> >
> > On Fri, Nov 12, 2010 at 3:16 PM, bejoy ks <bejoyks@hotmail.com> wrote:
> >
> > >
> > > Ok that'd be great Owen , if you could point me to the book 'Mahout in
> > > Action' . I'm bit interested to know more on the possibilities
> available
> > > with mahout and also the right usage of similarities, recommenders
>
>
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