Linear programming solver for paper-reviewer matching and mind-matching
Paper-Reviewer Matcher
A python package for paper-reviewer matching algorithm based on topic modeling and linear programming. The algorithm is implemented based on this article). This package solves problem of assigning paper to reviewers with constrains by solving linear programming problem. We minimize global distance between papers and reviewers in topic space (e.g. topic modeling can be Principal component, Latent Semantic Analysis (LSA), etc.).
Here is a diagram of problem setup and how we solve the problem.
Mind-Match Command Line
Mind-Match is a session we run at Cognitive Computational Neuroscience (CCN) conference.
We use a combination of topic modeling and linear programming to solve optimal matching problem.
To run example Mind-Match algorithm, you can clone the repository and run the following
python mindmatch.py data/mindmatch_example.csv --n_match=6 --n_trim=50