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From Sean Owen <sro...@gmail.com>
Subject Re: Recommender with ratings takes a long time to process
Date Fri, 11 May 2012 17:50:21 GMT
Yes, you want the sampling one so you can reduce the number of
neighbors you consider.

On Fri, May 11, 2012 at 6:47 PM, Emilio Suarez <Emilio.Suarez@intela.com> wrote:
> Thanks Sean,
>
> So, do you suggest something like this?
>
>        LogLikelihoodSimilarity similarity = new LogLikelihoodSimilarity(fileDataModel);
>        PreferredItemsNeighborhoodCandidateItemsStrategy candidateStrategy = new PreferredItemsNeighborhoodCandidateItemsStrategy();
>        recommender = new GenericItemBasedRecommender(fileDataModel, similarity, candidateStrategy,
candidateStrategy);
>
> or this?
>
>        LogLikelihoodSimilarity similarity = new LogLikelihoodSimilarity(fileDataModel);
>        SamplingCandidateItemsStrategy candidateStrategy = new SamplingCandidateItemsStrategy();
>        recommender = new GenericItemBasedRecommender(fileDataModel, similarity, candidateStrategy,
candidateStrategy);
>
>
> -emilio
>
> You need to apply a CandidateItemStrategy to reduce the number of
> elements you consider, or else it will take a very long time because
> almost the entire model is a candidate for recommendation.
>

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