Link Recomendation in GitHub using a variant of supervised random walks

This is the CS224W Fall 2013 project on link recommendation in GitHub.

To create data -

1. cd db
2. Run sqlite3 test.db < create.sql

To load data into db

1. python load.py -date1:2012-10-04-00 -date2:2012-04-12 -db:db/test.db -stream:online

To generate edge lists

1. cd analysis
2. ./gengraphs.sh ../db/test.db false

Setting the second argument to true above will also plot the graphs

To get graph properties Prereq - Must have edge lists ready - See how to generate edge lists

1. python properties.py ../data/collaborators.out

PREREQS - Installation

This project depends on the following modules. Their installation instructions are also presented below.

1. Install Numpy git clone git://github.com/numpy/numpy.git numpy cd numpy python setup.py install --user

2. Install SciPy wget "http://downloads.sourceforge.net/project/scipy/scipy/0.13.1/scipy-0.13.1.tar.gz?r=&ts=1386460361&use_mirror=iweb"_ cd download python setup.py install --user

3. Install mlabwrap from BitBucket (latest source) wget https://bitbucket.org/nikratio/mlabwrap/get/d61f299e7887.zip unzip d61f299e7887.zip cd nikratio-mlabwrap-d61f299e7887 python setup.py install --user