Fighting Fire with Fire: Using Antidote Data to Improve Polarization and Fairness of Recommender Systems

Bashir Rastegarpanah
Bashir Rastegarpanah

Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, Volume abs/1812.01504, 2019.

Cited by: 18|Views26
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Abstract:

The increasing role of recommender systems in many aspects of society makes it essential to consider how such systems may impact social good. Various modifications to recommendation algorithms have been proposed to improve their performance for specific socially relevant measures. However, previous proposals are often not easily adapted t...More

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