Equitable Top-k Results for Long Tail Data
Summary: Equitable top-k for long-tail data via theta-Equiv-top-k-MMSP; formalizes two subproblems: theta-Equiv-top-k-Sets and MaxMinFair. Generates many utility-equivalent top-k sets and a MaxMinFair distribution to equalize exposure; presents exact and scalable methods (random-walk, greedy, adaptive) and validates on six datasets. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Md Mouinul Islam (New Jersey Institute of Technology)
- 2. Mahsa Asadi (New Jersey Institute of Technology)
- 3. Senjuti Basu Roy (New Jersey Institute of Technology)
BibTeX Citation
@inproceedings{islam_sigmod23,
title = {{Equitable Top-k Results for Long Tail Data}},
author = {Islam, Md Mouinul and Asadi, Mahsa and Roy, Senjuti Basu},
series = {{SIGMOD} '23},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3626727},
url = {https://dl.acm.org/doi/10.1145/3626727},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,023 | Fairness in Preference Queries: Social Choice Theories Meet Data Management | 2024 | VLDB | 5.4035905e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5 | Optimal Aggregation Algorithms for Middleware [Extended Abstract] | 2001 | PODS | 0.0010679903 |
| 1,379 | Designing Fair Ranking Schemes | 2019 | SIGMOD | 0.00010859038 |
| 1,476 | Diversifying Top-K Results | 2012 | VLDB | 0.00010546498 |
| 1,917 | Formal Models of Web Queries | 1997 | PODS | 9.3796466e-05 |
| 3,130 | MithraCoverage: A System for Investigating Population Bias for Intersectional Fairness | 2020 | SIGMOD | 7.6113732e-05 |
| 4,721 | OmniFair: A Declarative System for Model-Agnostic Group Fairness in Machine Learning | 2021 | SIGMOD | 6.451752e-05 |
| 4,969 | Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles | 2022 | VLDB | 6.3324754e-05 |
| 6,275 | Page Quality: In Search of an Unbiased Web Ranking | 2005 | SIGMOD | 5.8253421e-05 |
| 7,595 | Rank Aggregation with Proportionate Fairness | 2022 | SIGMOD | 5.4860018e-05 |
| 7,784 | Efficient Indexes for Diverse Top-k Range Queries | 2020 | PODS | 5.4520677e-05 |
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