https://github.com/titipata/paper-reviewer-matcher
Linear programming solver for paper-reviewer matching and mind-matching
https://github.com/titipata/paper-reviewer-matcher
ccn-conference paper-reviewer-matcher papers python reviewers topic-modeling
Last synced: about 1 month ago
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Linear programming solver for paper-reviewer matching and mind-matching
- Host: GitHub
- URL: https://github.com/titipata/paper-reviewer-matcher
- Owner: titipata
- License: apache-2.0
- Created: 2016-08-10T16:14:04.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2022-09-24T02:18:43.000Z (over 2 years ago)
- Last Synced: 2023-08-23T03:12:07.831Z (over 1 year ago)
- Topics: ccn-conference, paper-reviewer-matcher, papers, python, reviewers, topic-modeling
- Language: Python
- Homepage:
- Size: 1.08 MB
- Stars: 79
- Watchers: 9
- Forks: 28
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 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](http://www.cis.upenn.edu/~cjtaylor/PUBLICATIONS/pdfs/TaylorTR08.pdf)). 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 on sample of 500 people, you can clone the repository and run the following
```sh
python mindmatch.py data/mindmatch_example.csv --n_match=6 --n_trim=50
```
in the root of this repo. This should produce a matching output `output_match.csv` in this relative location.
However, when people get much larger this script takes quite a long time to run.
We use pre-cluster into groups before running the mind-matching to make the script runs faster.
Below is an example script for pre-clustering and mind-matching on all data:
```sh
python mindmatch_cluster.py data/mindmatch_example.csv --n_match=6 --n_trim=50 --n_clusters=4
```
## Example script for the conferences
Here, I include a recent scripts for our Mind Matching session for CCN conference.
- `ccn_mind_matching_2019.py` contains script for Mind Matching session (match scientists to scientists) for [CCN conference](https://ccneuro.org/2018/)
- `ccn_paper_reviewer_matching.py` contains script for matching publications to reviewers for [CCN conference](https://ccneuro.org/2019/), see example of CSV files in `data` folder
The code makes the distance metric of topics between incoming papers with reviewers (for `ccn_paper_reviewer_matching.py`) and
between people with people (for `ccn_mind_matching_2019`). We trim the metric so that the problem is not too big to solve using `or-tools`.
It then solves linear programming problem to assign the best matches which minimize the global distance between papers to reviewers.
After that, we make the output that can be used by the organizers of the CCN conference -- pairs of paper and reviewers or mind-matching
schedule between people to people in the conference.
You can see of how it works below.
## Dependencies
Use `pip` to install dependencies
```sh
pip install -r requirements.txt
```
Please see [Stackoverflow](http://stackoverflow.com/questions/26593497/cant-install-or-tools-on-mac-10-10) if you have a problem installing `or-tools` on MacOS. You can use `pip` to install `protobuf` before installing `or-tools`
```sh
pip install protobuf==3.0.0b4
pip install ortools
```
for Python 3.6,
```sh
pip install --user --upgrade ortools
```
## Citations
If you use Paper-Reviewer Matcher in your work or conference, please cite us as follows
```
@misc{achakulvisut2018,
author = {Achakulvisut, Titipat and Acuna, Daniel E. and Kording, Konrad},
title = {Paper-Reviewer Matcher},
year = {2018},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/titipata/paper-reviewer-matcher}},
commit = {9d346ee008e2789d34034c2b330b6ba483537674}
}
```
## Members
- [Daniel Acuna](https://scienceofscience.org/) (original author)
- [Titipat Achakulvisut](https://github.com/titipata) (refactor)
- [Konrad Kording](http://kordinglab.com/)