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From Sean Owen <>
Subject Re: Taste-GenericItemBasedRecommender
Date Thu, 10 Sep 2009 08:59:50 GMT
Great discussion. My take-aways are that the current implementation is
more or less the same as a matrix-based implementation. It's been
pretty specialized and probably works as fast or faster than a simple,
clean matrix implementation. But we need a matrix-based implementation
since that is distributable and the current implementation can't
really be distributed. So it won't really work past a scale of maybe
100M ratings. And that implementation is likely to be relatively
efficient, even given the mapreduce overhead, and can incorporate
familiar concepts like log-likelihood similarity, etc.

I'd like to put this on my to-do list, for after two things happen:
1. Hadoop gets sorted. Right now I can't really make progress on
Hadoop 0.20.0 period
2. Our matrix implementation is finalized -- understand we're probably
switching to some other library?

On Thu, Sep 10, 2009 at 8:39 AM, Gökhan Çapan<> wrote:
> So, these algorithms are nearly same, in terms of pattern of computation,
> and this speed up is not enough, right?
> --
> Gökhan Çapan

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