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

Zhaoduo WEN wenzhaoduo at gmail.com
Tue Mar 15 03:10:14 EDT 2016


The link to the paper is:
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6137254

I've tried to use look through the code. If you have any opinions on my
proposal, please feel free to contact me. I am willing to contribute to
this project. Thanks.

Best,
Zhaoduo

2016-03-14 21:52 GMT+08:00 Ryan Curtin <ryan at ratml.org>:

> On Sun, Mar 13, 2016 at 05:38:22PM +0800, Zhaoduo WEN wrote:
> > Hi, Ryan,
> >
> > I just knew about GSOC today and I hope it is not late to introduce
> myself.
> >
> > I am Zhaoduo Wen, a senior student from Beijing University of Posts and
> > Telecommunications.I've been working on data mining and machine learning
> > problems for a year and had some experience on recommender systems.
> >
> > >From what I know, although collaborative filtering is faster in
> prediction
> > than matrix factorization framework, either itemKNN collaborative
> filtering
> > or userKNN collaborative filtering has some drawbacks. One major
> > disadvantage is that they suffer from low accuracy since there is
> > essentially no knowledge learned about item characteristics so as to
> > produce accurate recommendations. However, linear sparse model performs
> > better both in prediction accuracy and running time. I have read related
> > papers and I was lucky to listen to the author's presentation.
> > Consequently, I prefer to using a sparse linear model as the alternatives
> > to neighborhood-based collaborative filtering.
> >
> > I am enthusiastic for contributing to this project as I will be extremely
> > excited if I finish this project and someone uses it in future. I once
> used
> > a library for large linear classification (LIBLINEAR), which has a high
> > citation times on google scholar. I was impressed by its fast and
> accurate
> > performance. I wish I could write one someday. I believe GSOC would be a
> > good beginning.
> >
> > What is your opinion about my proposal? Hope to receive your reply.
> Thanks.
>
> Hi Zhaoduo,
>
> Can you provide a link to the paper that you are proposing to implement?
>
> Also, it would be a good idea to take a look through the existing CF
> code to see how the sparse linear model you are proposing would fit into
> the API.
>
> Thanks,
>
> Ryan
>
> --
> Ryan Curtin    | "Leave the gun.  Take the cannoli."
> ryan at ratml.org |   - Clemenza
>



-- 
Best Regards,

Zhaoduo
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