Abstract
An open-source and greedy approach to individually fair re-ranking is presented, evaluated and tested. Previous literature on individually fair search suggested greedy-style heuristics, but no such designs or implementations were introduced before this writing. We release our re-ranker as a zero-dependency utility compatible with all major operating systems. We publish our re-ranker under a permissive software license (GPLv3). By explicitly considering individual fairness a post-processing (re-ranking) task, we implement the notion of individual fairness as a microservice, de-coupled from specific IR systems. Our software package works on commodity hardware, and finds application in small-to-medium-sized businesses, federated social networks, and under the broader open web search initiative.
Original language | English |
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Journal | CEUR Workshop Proceedings |
Volume | 3744 |
Publication status | Published - 2024 |
Externally published | Yes |
Event | 1st Workshop on AI Bias: Measurements, Mitigation, Explanation Strategies, AIMMES 2024 - Amsterdam, Netherlands Duration: 20 Mar 2024 → … |
Keywords
- fairness
- individual fairness
- open source
- ranking