Awesome!  Thank you very much Ted.  I'll try that

As I am just getting started with Mahout, can you recommend any good
example code that does something similar?

On Sat, Sep 13, 2014 at 3:38 PM, Ted Dunning <[email protected]> wrote:

> Rebuilding every day works very well in practice, but it captures a moving
> average, not a good estimate of the current popularity of items.
>
> A simple hack is to implement a search based recommender and simply put an
> empirically scaled boost on items which are rising rapidly in popularity.
>  Of course you should also have specialized pages that show popular items
> and another that shows rapidly rising items.
>
> The simplest approach to marking rapidly rising items that I know is to use
> the log of recent plays over less plays, offsetting both counts in a manner
> similar to Laplace correction.  The philosophy behind the score is that for
> power law play counts, log play count is proportional to -log rank.  Then,
> the thought is something that rises from 2000-th rank to 1000-th rank is
> rising as significantly as something going from 100-th to 50-th.
>
>
>
>
>
>
> On Sat, Sep 13, 2014 at 11:25 AM, Peter Wolf <[email protected]> wrote:
>
> > Thanks Dmitriy,
> >
> > Is anyone working on an open source version of RLFM?
> >
> > For the moment, I have few enough classes of users that I can just build
> > multiple recommenders.  For example, one for men and one for women.
> >
> > What about adaptive on-line algorithms?  Just like Agarwal's Yahoo
> research
> > my items may rise and fall in popularity over time.  In fact, time may be
> > more important than user preferences in my application.
> >
> > Do I just rebuild every day with a window of recent data, or does Mahout
> > have something better?
> >
> > On Sat, Sep 13, 2014 at 12:26 PM, Dmitriy Lyubimov <[email protected]>
> > wrote:
> >
> > > Afaik mahout doesnt have these algorthms. Agarwal's RLFM is one of the
> > more
> > > promising while sitll simple enough things to implement  at scale that
> > does
> > > that.
> > > On Sep 13, 2014 9:07 AM, "Peter Wolf" <[email protected]> wrote:
> > >
> > > > Hello, I am new to Mahout but not ML in general
> > > >
> > > > I want to create a Recommender that combines things I know about
> Users
> > > with
> > > > their Ratings.
> > > >
> > > > For example, perhaps I know the sex, age and nationality of my users.
> > > I'd
> > > > like to use that information to improve the recommendations.
> > > >
> > > > How is this information represented in the Mahout API?  I have not
> been
> > > > able to find any documentation or examples about this.
> > > >
> > > > Thanks
> > > > Peter
> > > >
> > >
> >
>

Reply via email to