FairUP: A Framework for Fairness Analysis of Graph Neural Network-Based User Profiling Models

Author:

Abdelrazek Mohamed1ORCID,Purificato Erasmo2ORCID,Boratto Ludovico3ORCID,De Luca Ernesto William2ORCID

Affiliation:

1. Otto von Guericke University Magdeburg, Magdeburg, Germany

2. Otto von Guericke University Magdeburg & Leibniz Institute for Educational Media | Georg Eckert Institute, Magdeburg, Germany

3. University of Cagliari, Cagliari, Italy

Publisher

ACM

Reference35 articles.

1. Solon Barocas Moritz Hardt and Arvind Narayanan. 2019. Fairness and Machine Learning. fairmlbook.org. http://www.fairmlbook.org. Solon Barocas Moritz Hardt and Arvind Narayanan. 2019. Fairness and Machine Learning. fairmlbook.org. http://www.fairmlbook.org.

2. Fairness in Criminal Justice Risk Assessments: The State of the Art

3. Dan Biddle . 2017. Adverse impact and test validation: A practitioner's guide to valid and defensible employment testing . Routledge . Dan Biddle. 2017. Adverse impact and test validation: A practitioner's guide to valid and defensible employment testing. Routledge.

4. Simon Caton and Christian Haas . 2020. Fairness in machine learning: A survey. arXiv preprint arXiv:2010.04053 ( 2020 ). Simon Caton and Christian Haas. 2020. Fairness in machine learning: A survey. arXiv preprint arXiv:2010.04053 (2020).

5. Weijian Chen , Fuli Feng , Qifan Wang , Xiangnan He , Chonggang Song , Guohui Ling , and Yongdong Zhang . 2021. CatGCN: Graph Convolutional Networks with Categorical Node Features . IEEE Transactions on Knowledge and Data Engineering ( 2021 ). Weijian Chen, Fuli Feng, Qifan Wang, Xiangnan He, Chonggang Song, Guohui Ling, and Yongdong Zhang. 2021. CatGCN: Graph Convolutional Networks with Categorical Node Features. IEEE Transactions on Knowledge and Data Engineering (2021).

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. FUGNN: Harmonizing Fairness and Utility in Graph Neural Networks;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

2. Transparent Learner Knowledge State Modeling using Personal Knowledge Graphs and Graph Neural Networks;Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization;2024-06-27

3. Paradigm Shifts in User Modeling: A Journey from Historical Foundations to Emerging Trends;Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization;2024-06-27

4. First International Workshop on Graph-Based Approaches in Information Retrieval (IRonGraphs 2024);Lecture Notes in Computer Science;2024

5. Leveraging Graph Neural Networks for User Profiling: Recent Advances and Open Challenges;Proceedings of the 32nd ACM International Conference on Information and Knowledge Management;2023-10-21

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3