[mlpack] GSoC - 2013 Collaborative Filtering - Introduction and Initial thoughts

[Mudit Gupta]

Hello Everyone,

I am interested in mlpack project on* developing a collaborative filtering
package* for GSoC 2013. I am very* interested in Machine Learning* and have
done my thesis on the same. I have* relevant C++ experience* through my
contribution to ns-3.

I would like to start by introducing my self. I am Mudit Raj Gupta. final
year student of B.E.(H), M.Sc(H) at Birla Institute of Technology and
Science - Pilani (BITS-Pilani). I have been* selected for Google Summer of
Code, twice in 2011 and 2012* and worked for University of Michigan (USA)
and The network simulator - 3 project respectively. My contributions in
Repast Simphony and ns-3 can be checked here
http://code.google.com/p/cscs-repast-demos/wiki/Mudit and here
http://www.nsnam.org/wiki/index.php/GSOC2012HLA respectively. I am
presently working on my *thesis in the field on Machine Learning*. In my
thesis, I worked on developing a mathematical model in order to model
cognition and biases in individual with the help of Machine Learning. The
thesis report can be found here
http://code.google.com/p/multiagent-reinforcement-learning/downloads/list.
I am presently working on use of probabilistic algorithms for hand-gesture
recognition. My* coding profile* can be found here :
http://code.google.com/u/110675325175605367090/ . My* linkedIn profile *can
be found here:  http://www.linkedin.com/profile/view?id=79832898&trk=tab_pro
 .

I think a good point to start with would be by *defining the core
modules*of the package. This would include the data format/model,
similarity
measures, recommender system as a higher abstraction and output format
(similar nodes, predict degree of likeness etc). The algorithms that can be
considered can start from the ones implemented in other leading libraries
like:
1. *Item Based Collaborative Filtering*
2. May be look into something like this(listed and implemented in some
other software) :
http://www.hpl.hp.com/personal/Robert_Schreiber/papers/2008%20AAIM%20Netflix/netflix_aaim08(submitted).pdf
Finally, completing* testing and documentation *along with high quality *
examples* cold be looked into.

I a looking into coding standards and practices used in mlpack would try
some features of mlpack. I would like to request the mentors and people
from the community to please provide any details/pointers to resources
which could be helpful for the project. Moreover, it would be great if the
mentors provide details about the project and their views on design or
choice of algorithms.


Best Regards,

Mudit Raj Gupta
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