[mlpack] GSOC 2016 "Alternatives to neighbour-based collaborative filtering"

[Zhaoduo WEN]

Hi Ryan,

Thanks for your advice. I would follow your suggestion and see what I can
find.

Best,
Zhaoduo

2016-03-18 13:08 GMT+08:00 Ryan Curtin <ryan at ratml.org>:

> On Thu, Mar 17, 2016 at 10:21:33PM +0800, Zhaoduo WEN wrote:
> > Hi Ryan,
> >
> > I want to figure out one thing. Does this project intend to expand the
> > existing mlpack_cf? Could I write a new algorithm that is different from
> CF?
> >
> > I've read the API of CF, though not all of them. I find that it's not
> easy
> > to fit with the existing other factorizers and algorithms for CF, as the
> > key component of SLIM is learning W matrix from A. However, the CF
> > algorithm doesn't need this. Do you have any ideas of fitting with the
> existing
> > other factorizers and algorithms for CF? I need some inspiration. Thanks.
>
> Hi Zhaoduo,
>
> I glanced at the paper and I see what you mean; instead of decomposing
> the data matrix into two low-rank matrices W * H, the SLIM algorithm
> instead simply learns a large sparse matrix W.
>
> I think it would be very useful to allow the SLIM algorithm to fit
> inside the CF code, but clearly the code that is currently in CF will
> not work and it will need to be refactored to handle more models than
> just a low-rank decomposition.
>
> Probably the right way to go about this will be to refactor the CF class
> so that the logic for the model is contained in the FactorizerType or
> something else, not in the CF class itself.  So it may be necessary to,
> e.g., define a ModelType class associated with each FactorizerType which
> contains the logic for applying the model to make a prediction.
>
> I haven't thought through all the details there, but I think that should
> be a good direction for how to resolve this problem.  Let me know what
> you think.
>
> Thanks,
>
> Ryan
>
> --
> Ryan Curtin    | "I know... but I really liked those ones."
> ryan at ratml.org |   - Vincent
>



-- 
Best Regards,

Zhaoduo
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