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From Ted Dunning <ted.dunn...@gmail.com>
Subject Re: Discrete Rating Scale
Date Mon, 14 Jul 2014 18:30:38 GMT
You can already do a form of multi-modal collaborative filtering.  The way
you would do this is to create three item codes for every item, one for
positive rating, one for negative rating and one for buying or whatever
conversion you have.  You might even create a fourth code for any rating,
positive or negative.  Then translate your original data so that you lose
the rating and change the item to be the positive or negative version.
 Likewise, convert your sales lines to use the sale version of the item id.

When you run this through the ItemSimilarityJob, you will get indicators
for different combinations of items and actions.  You probably only care
about the conversion version of the items.  In the indicators for the item
+ conversion combos, you should see items with positive and negative
ratings and also item conversions.  You can push these indicators into a
amalgamated field or separate them in to separate fields when you push the
data into a search engine.

The general method for recommendation using a search engine is described in
this itty bitty book that Ellen and I wrote:

http://www.mapr.com/practical-machine-learning

This isn't as good as full-on multi-modal recommendations because one kind
of action can crowd out other kinds of action.  Pat is fixing this so that
we won't need the work-around.




On Mon, Jul 14, 2014 at 11:07 AM, Floris Devriendt <
florisdevriendt@gmail.com> wrote:

> Hey Ted Dunning,
>
> What is already possible on multi-modal recommendation in the
> non-hadoop-implementation of the Mahout recommenders?
> And if it's still under development, do you perhaps have a different
> suggestion (within the possibilities of Mahout)?
>
> Best regards,
> Floris Devriendt
>
>
>
>
>
> 2014-07-14 18:45 GMT+02:00 Ted Dunning <ted.dunning@gmail.com>:
>
> > I would separate the two interactions.  Type 1 is like.  Type 2 is
> dislike.
> >  They will have different correlations to different predicted
> interactions.
> >
> > This is an ideal use case for multi-modal recommendation.  Pat is working
> > on bringing that into the DSL as we speak.
> >
> >
> >
> > On Mon, Jul 14, 2014 at 7:21 AM, Floris Devriendt <
> > florisdevriendt@gmail.com
> > > wrote:
> >
> > > Hey all,
> > >
> > > When using a discrete rating scale (e.g. likes / dislikes), what are
> the
> > > things that I should consider when using Mahout for Collaborative
> > > Filtering?
> > >
> > > If I'm not mistaking I've read a mail a week or two ago from this
> mailing
> > > list stating that one should avoid using 0 (dislike) and 1 (like) as
> > > scores, because Mahout would not be able to take into account the
> > dislikes
> > > properly.
> > > If this is true, what scores should I give to my like/dislike scale?
> > (e.g.
> > > is -1/1 better than 0/1, or should I use 1/2 with 1 = dislike and 2 =
> > > like?)
> > >
> > > Best regards,
> > > Floris Devriendt
> > >
> >
>

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