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FairMC - fair Markov Chain rank aggregation methods

Welcome to the code for our paper, FairMC - fair Markov Chain rank aggregation methods, published at DaWaK 2024. We encourage you to read the full paper.

Citation

If you found this work useful, please cite our paper:

@inproceedings{FairMC,
  author    = {Chiara Balestra  and
               Antonio Ferrara and
               Emmanuel M\"uller},
  title     = {FairMC - fair Markov Chain rank aggregation methods},
  booktitle = {DaWaK},
  publisher = {Springer},
  year      = {2024}
 }

Example and code

The aggregators_OURS.py contained the our Markov chains based fair ranking aggregation methods and getResultsSeparated.py includes examples of how to call the various algorithms.

Requirements

Code tested under:

  • python 3.7.6
  • numpy 1.18.5
  • pandas 1.4.0

Questions

You can reach out to chiara.balestra1@gmail.com with any question