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From Ted Dunning <ted.dunn...@gmail.com>
Subject Re: Recommeding on Dynamic Content
Date Tue, 01 Feb 2011 21:00:37 GMT
Low cost access for this paper is here:
http://www.deepdyve.com/lp/association-for-computing-machinery/regression-based-latent-factor-models-1ebJXMCs0K

(shameless plug.  I used to work at Deepdvye and am still an advisor)

On Tue, Feb 1, 2011 at 12:27 PM, Dmitriy Lyubimov <dlieu.7@gmail.com> wrote:

> There's also a paper from Yahoo! research "Regression-based Latent Factor
> Models" http://portal.acm.org/citation.cfm?id=1557029
>
> What i like about this is that it doesn't focus on a particular method to
> combine the models to regress on static profile data + side info. I think
> it
> might be combined with methods ALS-WS  which unlke SGD are
> hadoop-parallelizable to do stage computations. It also serves pretty good
> in situations when there are dyadic interactions but different types
> interaction context (side info) are available (or sometimes none at all)
> but
> static profile information is always available. I think we'll have to get
> on
> this problem pretty soon .
>
>
> On Tue, Feb 1, 2011 at 8:24 AM, Ted Dunning <ted.dunning@gmail.com> wrote:
>
> > And the Mahout-525 github branch of mahout that I started has an
> apparently
> > working version for this algorithm.
> >
> > I would love to support anyone who wants to do last mile work on that
> > stuff.
> >
> > See https://issues.apache.org/jira/browse/MAHOUT-525 for more info
> >
> > On Tue, Feb 1, 2011 at 1:52 AM, Sean Owen <srowen@gmail.com> wrote:
> >
> > > That Elkan / Menon paper has an elegant theoretical formulation of a
> > > recommender that uses both ratings and side info at the same time.
> > >
> >
>

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