Proceedings of the Korea Information Processing Society Conference (한국정보처리학회:학술대회논문집)

  • 2022.05a
  • /
  • Pages.9-11
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  • 2022
  • /
  • 2005-0011(pISSN)
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  • 2671-7298(eISSN)
Korea Information Processing Society (한국정보처리학회)
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Absolute-Fair Maximal Balanced Cliques Detection in Signed Attributed Social Network

서명된 속성 소셜 네트워크에서의 Absolute-Fair Maximal Balanced Cliques 탐색

  • Yang, Yixuan (Dept. of Software Convergence, Soonchunhyang University) ;
  • Peng, Sony (Dept. of Software Convergence, Soonchunhyang University) ;
  • Park, Doo-Soon (Dept. of Software Convergence, Soonchunhyang University) ;
  • Lee, HyeJung (Institute for Artificial Intelligence and Software, Soonchunhyang University)
  • 양예선 (순천향대학교 소프트웨어융합학과) ;
  • 펭소니 (순천향대학교 소프트웨어융합학과) ;
  • 박두순 (순천향대학교 소프트웨어융합학과) ;
  • 이혜정 (순천향대학교 AI.SW 교육원)
  • Published : 2022.05.17
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Abstract

Community detection is a hot topic in social network analysis, and many existing studies use graph theory analysis methods to detect communities. This paper focuses on detecting absolute fair maximal balanced cliques in signed attributed social networks, which can satisfy ensuring the fairness of complex networks and break the bottleneck of the "information cocoon".

Keywords

Acknowledgement

This research was supported by the National Research Foundation of Korea (No. NRF-2022R1A2C1005921) and BK21 FOUR (Fostering Outstanding Universities for Research) (No.5199990914048).