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From Ted Dunning <ted.dunn...@gmail.com>
Subject Re: Recommendation scores from LogLikelihood Similarity recommender
Date Sun, 06 May 2012 19:53:10 GMT
As Sean points out, cosine should pick up on this.  You will have the usual
problems with small counts that any rating based system has.

And in spite of your last comment, I would strongly recommend that you test
a boolean approach where in *any* action is considered positive and another
where you consider only your positive actions and ignore your negative
actions.  If necessary, consider the negative actions at the presentation
tier.

On Sun, May 6, 2012 at 10:48 AM, Will C <will@infomofo.com> wrote:

> So I've taken another try at using recommendations values.  However, unlike
> something that a user is explicitly rating on a scale of 0-5. I am using a
> user's activity.  Certain activities of a user toward an item are negative,
> and certain are positive.
>
> If I have users 1 and 2 and 3, and product X, and their preferences are as
> follows:
>
> 1, X, -1
> 2, X, 1
> 3, X, 10
>
> Clearly 2 and 3 are closer than 2 and 1, because they both like product X,
> just to varying degrees.  However, most distance algorithms I've tried are
> incorrectly showing 1 and 2 closer because their difference is less.
>
> Am I approaching this wrong?  Other than switching to boolean preferences,
> is there a better way to approach this?
>

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