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Many-to-one stable matching for prediction in social networks

  • Beihang University
  • University of Toronto
  • Codemao

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Stable matching investigates how to pair elements of two disjoint sets with the purpose to achieve a matching that satisfies all participants based on their preference lists. In this paper, we consider the case of matching with incomplete information in a social network where agents are not fully connected. A new many-to-one matching algorithm is proposed based on the classical Gale-Shapley algorithm with constraints of given network topology. In simulated experiments, we find that the matching outcomes in scale-free networks yield the best average utility with least connective costs compared to other structured networks in one-to-one problems. But in many-to-one matching cases, network structure has no significant influence on matching utilities. We also apply the new matching model to a real-world social network matching problem and we find a significant increase of accuracy in matching pair prediction comparing to classical methods.

源语言英语
主期刊名Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices - 33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020, Proceedings
编辑Hamido Fujita, Jun Sasaki, Philippe Fournier-Viger, Moonis Ali
出版商Springer Science and Business Media Deutschland GmbH
345-356
页数12
ISBN(印刷版)9783030557881
DOI
出版状态已出版 - 2020
活动33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020 - Kitakyushu, 日本
期限: 22 9月 202025 9月 2020

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12144 LNAI
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议33rd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2020
国家/地区日本
Kitakyushu
时期22/09/2025/09/20

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