Giter Site home page Giter Site logo

fairrec_www_2020's Introduction

Two-Sided Fairness for Personalized Recommendations in Two-Sided Platforms

Running FairRec

python fairrec_algorithm.py google_local_fact.csv 10 0.5

There are three arguments here.

  • path to csv file with relevance scores (rows: customers, columns: producers) like google_local_fact.csv above.
  • size of recommendation or k like 10 above.
  • value of α (our producer-side guarantee will be α×MMS. The value of α can be in between 0 and 1) like 0.5 above.

It saves the recommendations in zipped pickle file (dictionary format { customer : list_of_recommended_products }).

Relevance Scores

You can use the relevance scores estimated in your dataset in csv format (rows: customers, columns: producers) for your application scenario. Alternatively you can test with ours. The relevance scores calculated for the datasets (used in the paper) can be found in the following links in zipped csv format.

Citation Information

If you use this repository in your research, please cite the following paper.

You can use the following bibtex.

@inproceedings{10.1145/3366423.3380196,
author = {Patro, Gourab K and Biswas, Arpita and Ganguly, Niloy and Gummadi, Krishna P. and Chakraborty, Abhijnan},
title = {FairRec: Two-Sided Fairness for Personalized Recommendations in Two-Sided Platforms},
year = {2020},
isbn = {9781450370233},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3366423.3380196},
doi = {10.1145/3366423.3380196},
booktitle = {Proceedings of The Web Conference 2020},
pages = {1194–1204},
numpages = {11},
keywords = {Fair Allocation, Fair Recommendation, Maximin Share, Two-Sided Markets, Envy-Freeness},
location = {Taipei, Taiwan},
series = {WWW ’20}
}

fairrec_www_2020's People

Contributors

gourabkumarpatro avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.