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

한국정보처리학회 (Korea Information Processing Society)
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서명된 속성 소셜 네트워크에서의 Absolute-Fair Maximal Balanced Cliques 탐색

Absolute-Fair Maximal Balanced Cliques Detection in Signed Attributed Social Network

  • 양예선 (순천향대학교 소프트웨어융합학과) ;
  • 펭소니 (순천향대학교 소프트웨어융합학과) ;
  • 박두순 (순천향대학교 소프트웨어융합학과) ;
  • 이혜정 (순천향대학교 AI.SW 교육원)
  • 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)
  • 발행 : 2022.05.17
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초록

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".

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과제정보

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