@inproceedings{9db199030aff4ffa81a9228f1b1b898f,
title = "Dexer: Detecting and Explaining Biased Representation in Ranking",
abstract = "With the growing use of ranking algorithms in real-life decision-making purposes, fairness in ranking has been recognized as an important issue. Recent works have studied different fairness measures in ranking, and many of them consider the representation of different {"}protected groups{"}, in the top-k ranked items, for any reasonable k. Given the protected groups, confirming algorithmic fairness is a simple task. However, the groups' definitions may be unknown in advance. To this end, we present Dexer, a system for the detection of groups with biased representation in the top-k. Dexer utilizes the notion of Shapley values to provide the users with visual explanations for the cause of bias. We will demonstrate the usefulness of Dexer using real-life data.",
keywords = "explanations, ranking fairness, representation bias",
author = "Yuval Moskovitch and Jinyang Li and Jagadish, \{H. V.\}",
note = "Publisher Copyright: {\textcopyright} 2023 Owner/Author.; 2023 ACM/SIGMOD International Conference on Management of Data, SIGMOD 2023 ; Conference date: 18-06-2023 Through 23-06-2023",
year = "2023",
month = jun,
day = "5",
doi = "10.1145/3555041.3589725",
language = "American English",
series = "Proceedings of the ACM SIGMOD International Conference on Management of Data",
pages = "159--162",
booktitle = "SIGMOD 2023 - Companion of the 2023 ACM/SIGMOD International Conference on Management of Data",
}