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Identifying Rank-Happiness Maximizing Sets Under Group Fairness Constraints

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Web and Big Data (APWeb-WAIM 2024)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14963))

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Abstract

The happiness or regret based query has been another important tool in multi-dimensional decision-making besides the top-k and skyline queries. To avoid the happiness ratio being perceived as “made up” numbers which are often confused by users, we merge the concept rank into happiness ratio and study the rank-happiness maximizing set problem (RHMS). Also, it is crucial for RHMS to fairly represent different groups of candidates without bias and discrimination. In this paper, we solve the rank-happiness maximizing set problem under group fairness constraints (FairRHMS) from a submodular perspective. By introducing the concept of rank-happiness ratio and modeling the group fairness constraint proportionally along with upper and lower bounds for each group, we convert the FairRHMS problem into a submodular maximization problem under matroid constraints. Further, a bi-criteria approximation algorithm with multiple rounds of greedy processes named BMGreedy is proposed to solve the problem. Experiments on real and synthetic datasets confirm the effectiveness and efficiency of our BMGreedy algorithm.

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Notes

  1. 1.

    https://archive.ics.uci.edu/ml/datasets/adult.

  2. 2.

    https://archive.ics.uci.edu/ml/datasets/statlog+(german+credit+data).

  3. 3.

    https://github.com/propublica/compas-analysis.

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Acknowledgments

This work is partially supported by the Fundamental Research Funds for the Central Universities under grant NS2024056 and the National Natural Science Foundation of China under grant U1733112.

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Authors and Affiliations

  1. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Kaiqin Zhu, Jiping Zheng, Zhengchen Yang & Jie Dong

  2. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China

    Jiping Zheng

Authors
  1. Kaiqin Zhu
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  2. Jiping Zheng
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  3. Zhengchen Yang
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  4. Jie Dong
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Corresponding author

Correspondence to Jiping Zheng .

Editor information

Editors and Affiliations

  1. University of New South Wales, Sydney, NSW, Australia

    Wenjie Zhang

  2. National University of Singapore, Queenstown, Singapore

    Anthony Tung

  3. Zhejiang Normal University, Jinhua, China

    Zhonglong Zheng

  4. University of New South Wales, Sydney, NSW, Australia

    Zhengyi Yang

  5. University of New South Wales, Sydney, NSW, Australia

    Xiaoyang Wang

  6. Zhejiang Normal University, Jinhua, China

    Hongjie Guo

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Zhu, K., Zheng, J., Yang, Z., Dong, J. (2024). Identifying Rank-Happiness Maximizing Sets Under Group Fairness Constraints. In: Zhang, W., Tung, A., Zheng, Z., Yang, Z., Wang, X., Guo, H. (eds) Web and Big Data. APWeb-WAIM 2024. Lecture Notes in Computer Science, vol 14963. Springer, Singapore. https://doi.org/10.1007/978-981-97-7238-4_21

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  • DOI: https://doi.org/10.1007/978-981-97-7238-4_21

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  • Print ISBN: 978-981-97-7237-7

  • Online ISBN: 978-981-97-7238-4

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